# data[].attributes.body
research method- by using quantitative data I am able to get long responses off participants. however it Is very time consuming and I will have to go through all written responses to find out key information then transfer that to a table. where qualitative data is easier to be transferred into tables as all the information is infront of you and you can't get full statistics.

research design- by only using a small amount of coaches and athletes my data is specific to one area of age group in which athletes are in the 15-21 age and doesn't represent the rest of the population or a huge variety of sports.

data collection methods - due to covid 19 all my info will be taken from online surveys using opens questions the limitation of this is that I can't use interviews etc to get a full detail of answers from participants and ask questions with regards to the answers given.

participants/ environment- as I only have access to people around me I will have to use a smaller proportional of coaches and athletes.

variables limitations- the variables in my research project is coaches and athletes by using different coaches and asking their opinions then athletes and their opinions. I am unable to use the coaches of the athletes for their opinions so instead using coaches who are willing to be involved.

# data[].attributes.headline
Remember: It doesnt have to be one or the other, could your project be benefitted by both ?

# data[].attributes.subject
Remember: It doesnt have to be one or the other, could your project be benefitted by both ?

# data[].attributes.body
reliability is important in my research this is because the results need to be accurate and repeatable if someone tried to repeat my research the results would be close.

I have considered this factor and in order to see the accuracy of my research I will be comparing to journals and scientists who have looked into the effects of coaching styles. I will be looking for answers through open questions and removing any answers which don't answer the question given which could change my results.

once collecting all my data I will be asking my participants yes and no questions to see if they agree with the conclusions I have come up with from their responses. so using inter rater reliability. if the results comeback that majority agree with my statements it will show the data is reliable.

# data[].attributes.body
the effects on different coaching types on various athletes

qualitative data-
data collection: online via questionnaires by open and closed questions.

raw data process;
first of all I am going to use open coding and find the most common answers given to my questions then place these into a table.
next I will use axial coding manually to find the most common answers to each of my questions. then place these into categories based on male and female responses and the coaches responses.
selective- then I will identify three of the most popular responses of my participants and link that to other responses.

displaying the data-
initially I will be using a table to put the key parts of responses into a diagram so I am able to find trends in my data collected.

displaying the data two- next I will use a Venn diagram for example to display the three best qualities of a coach given by both the athletes and the coaches then section off coaches responses and athletes responses. I am able to compare the most common answers and the least common data given by the participants.

displaying the data 3- I feel that using a thematic analysis will be the best for my research as I will be able to compare the most common themes in my research and compare them. I will be able to conclude the most common answers and show what type of coaching qualities is the most effective in sport.

data verification- I will be collecting my results and synthesising them then asking the participants to see how much they agree with what has been given. then showing the coaches the results of the athletes answers and seeing how this will then effect their coaching from now on and if they agree.

# data[].attributes.body
quantitative data so is limited and direct/outlined as dont gain pts opinions and outlook
research design, observation and recording of performance results meaning they could be biased from pts point of view on certain bowls
data collection, my research could be very expensive if i did not have the equipment prior to investigation as sets of bowls can be around or over £100. meaning to do research with many sets would be extremely expensive
pts involved in the research may have work or other activities on the day meaning that they are not fully energised/focused on my investigation 100%. so my research may not be truly accurate with all the pts trying to a different amount

# data[].attributes.body
reliability in my research is important as it makes sure that my research can be depended on to be accurate. to make sure my research is accurate is why im using as many particitpants as possible to ensure that anomalies in my results can be outlined and noted. so for reliabilty i will be test-retesting with many participants.

# data[].attributes.body
•Data Collection - data will be collected as observation as well as with date, density/weight of bowl with a performance outcome (score of the game)against a base player

•Raw Data: data will be set out in a table of results  showing the individuals performance, it will be across the top, bowl weight, density, name of individual, score, who played

•Descriptive Statistics: using descriptive statistics such as mean and standard deviation will be for looking at the average performances of all individuals with same weight/density bowl. to see if there are any similarities or differences to potentially try and look if there are any individual differences that could impact results

•Display the data: id use a scatter graph with score on the left and weight/density of bowl along the bottom, using a key to be able to determine which cross/dot/colour for eg refers to which individual thats taken part

•Statistical testing:

•Data verification - What method would you adopt ? I would use member checking to gather the opinion of the individuals in the study which could help or be a valid point which could be used in conclusion of results as well.

# data[].attributes.body
why is considering validity important?
this is important as it shows the quality of the research undertaken. if I had results with lots of anomalies it would mean that the data isn't valid so the conclusions that would be made from the research would be inaccurate. overall I wouldn't be able to tell you exactly what it is that coaches can do to effect sports performance so it would be wasted.

what validity  issues am I facing-

due to covid being able to reach more peoples means that the amount of people I can allow to be part of my research is smaller and I am unable to conduct interviews to get more detailed responses off participants.

as I am going to be using various peoples opinions validity will be mixed due to the variety of people within the project. I am going to be using a smaller age range to make it more reliable with the athletes as the age group are at an impressionable age where coaching is important.

external validity-
this is the way in which my results could be taken and compared and used with the wider public. my results would have to be used with people who have been coaches as they is the only way that you could get valid results that aren't bias.  if you used the general public then it would have a low validity as they wouldn't be able to answer the questions well

# data[].attributes.body
1.     you need to make sure you have ethical clearance from derby college and tutors before you start your questionnaire

2.     all of your participants that you chose need to have completed a consent form to say they agree to be part of your research.

3.     Make sure there is a balance of participants eg half women and half men

4.     Research into the best questionnaire website to complete your research with

5.     Create the first questionnaire for the athletes covering the type of sports they do and find out things such as how many coaches they have. this is needed to get a deeper understanding how they feel.

6.     Next create a questionnaire for the coaches’ important questions to include are things such as what they coach and how long they have coached for.

7.      Make sure that all participants fill out every question on the form.

8.     Complete a coding process to begin to start highlighting and identifying trends/patterns/key terms.

9.     You need to split the responses based on gender so that there can be a comparison of different types of coaching on different people.

10.  Using your data, you need to compare the answers given by the different people so you should compare all the answers given by each participant for the athletes.

11.  With this make a list of the similarities of what the athletes have said and the differences and then analyse this to understand why there is this difference.

12.  This should be repeated for each question asked on the survey.

13.  You should then compare these athletes’ answers to those from the coaches. The coaches will be asked different questions, but you should compare their answers to those of the athletes.

14.  Create a chart for example a pie chart for answers given by the athlete for example the best qualities of a coach from your research. By putting it in a chart it is able to show a reader easily the best qualities of a coach.

15.  Compare the answers given by both females and males this is important as coaches treat genders differently and you want to see the effect of this.

16.  Create multiple graphs and diagrams to sh9ow the results of your research.

17.  Share the answers/ findings back with the participants to see how many agree – this will help to verify the information (100% agreement = reliability)

18.  Compare results to previous studies and highlight key notes and possible reasoning

19.  Summarise the main findings

20.  Write a conclusion to explain what your results show and make sure to compare the responses given.

# data[].attributes.body
1. Gain ethical clearance form
2. Gain consent form of each individual taking part in my study
3. Health screening, just a simple has anyone you know/live with had COVID-19? Have you had to isolate? Should you be isolating now?
4. To begin with I’ll have as many sets of bowls I can collect, run every bowl down a ramp of some sort (the same ramp for every bowl) too see distance travelled of bowl and amount it curled.
5. Have the weight of bowl outlined as well as the density
6. Make note/ include in the table both 4 & 5 in the results table.
7. I’ll have 2 base players involved
8. Try to get as many pts involved as is possible, want at least 25 to ensure detailed results
9. Base players must be playing with the same set of bowls every game they play.
10. Have every participant play at least 1 of the base players for a duration of 7 ends and mark score at the end.
11. Have each pt repeat step 10 with as many sets of bowls they are happy to, make sure bowls are sanitised and wiped if swapped between different individuals
12. Then disinfect the bowls after use as well
13. Make a table of results
Name   Bowl weight  Bowl density  Score  Base player name
14. Make conclusions from results, is there any patterns eg certain bowls perform better for everyone. If not, why?

# data[].attributes.body
transgender individuals in sport

Data Collection - Both qualitative and quantitative from questionnaires and online resources

Raw Data: There will be both open and closed questions in my questionnaire which will determine the understanding of the people i have asked on how aware they are about the topic of transgender individuals in sport and the sporting policy along with this.
Open questions-
Open- i will highlight key words the participant has mentioned in their answer
Axial- The key words picked out will be placed into categories of same or similar key words
Selective- Any key words that don't link to the data I'm set out to analyse and support my topic i will remove these categories
Closed questions-
I will create tables to put the data in and calculate totals and percentages for each set of collected answers for each question. With this i will then calculate it to set it up in a bar chart on edexcel so i can easily compare and analyse my answers.

# data[].attributes.body
1.I will create a plan of the questionnaire and decided what kind of questions need to be asked.

2.These ideas will then be developed in the correct wording for questions.

3.The questions will be straightforward and unbiased

4.I will then design the questionnaire that will provide me with detailed answers making it easy to evaluate.

5.The questionnaire will be sent to the participants for them to complete.

6.All participants will be given the choice to take part in the study and will be told that they can drop out whenever they want.

7.They will be asked to complete a consent form which will be checked by my teacher.

8.It will be optional for the participants to put their name on the questionnaire because they may answer the questions more honestly if they were anonymous.

9.They will be asked to complete the questionnaire and submit it back to me.

10.The results will be analysed

11.They will then be used as a part of my research project.

# data[].attributes.body
•Research method: Quantitative cannot gauge people opinion on the subject and is very set and direct.

•Research design: Experimental case study: this doesn’t allow me to get a wider selection of data and therefore anomalies might effect the average more causing inaccurate results.

•Data collection: My method of data collection might be expensive if I didn’t already have the equipment. There may also be human error involved in the collection of data in some aspects, the wattbike app will record most of the data. The heart rate monitor sometimes isn't reliable because sometimes it is faulty, this may reduce the accuracy of the true results.

•My chosen subjects: these may have limitations based on their activities outside the testing day that could effect the results, such as level of training, also their motivation during the challenge may alter results as it differs from participant to participant.

# data[].attributes.body
Is passive recovery more effective than active recovery?

1. Data Collection - observation sheet/table

2. Raw Data Process -  2 tables on edexell, 1 for passive and 1 for active recovery. They will have the headings of heart rate before exercise, heart rate after exercise and also heart rate after recovery.

3. Descriptive Statistics -  I will find the mean and standard deviation for men doing passive recovery and the women doing passive recovery and the same for active. I will also find the mean and standard deviation for all participants doing  passive  and active recovery, and then compare the percentage difference of the heart rate from straight after exercise to after recovery

4 . Displaying the Data - I will make a line graph for each recovery type, and then separate line graphs comparing passive and active recovery for both men and women.

5. Statistical Testing - I will use a t-test to show the difference between heart rate immediately after exercise and then after recovery.

6. Data Verification - I will use member checking to verify my data to see if the participants agree with my findings.

# data[].attributes.body
Is passive recovery more effective than active recovery?

1. Data Collection - observation sheet/table

2. Raw Data Process -  2 tables on edexell, 1 for passive and 1 for active recovery. They will have the headings of heart rate before exercise, heart rate after exercise and also heart rate after recovery.

3. Descriptive Statistics -  I will find the mean and standard deviation for men doing passive recovery and the women doing passive recovery and the same for active. I will also find the mean and standard deviation for all participants doing  passive  and active recovery, and then compare the percentage difference of the heart rate from straight after exercise to after recovery

4 . Displaying the Data - I will make a line graph for each recovery type, and then separate line graphs comparing passive and active recovery for both men and women.

5. Statistical Testing - I will use a t-test to show the difference between heart rate immediately after exercise and then after recovery.

6. Data Verification - I will use member checking to verify my data to see if the participants agree with my findings.

# data[].attributes.body
1.Have an even number of participants that are active

2.Half of them take creatine in their daily protein shake, half do not

3.Participants will complete a 1k challenge each week

4.Attach a heart rate monitor to the participants

5.Log them into a wattbike account (so data can be saved)

6.Get them to complete the 10-minute warm up

7.Get them to complete the 1k challenge where they push as hard as they can till it is complete.

8.Get them to complete a 5-minute cool down (for personal safety)

9.Repeat this every week on the same day for each participant.
10. Repeat for at least 4 weeks to see improvements.

# data[].attributes.body
Research Method: Using qualitative data by itself may not fully indicate how much of an effect the diet had on the performance, as it can only show us how the subject felt when performing, rather than a statistical figure as to how well they performed. It can also make the results slightly bias, as the research will be based purely off of how the athlete thinks performance went, rather than data coming from elsewhere. Using quantitative data by itself. Quantitative data, as much as it is simple to record, and to then use and display, does not take into account personal opinion, which could help record results in the most accurate way. In my research project, this would mean that factors such as how the subject felt they fatigued could not be taken into account. This is why I used a mix of them both.
Research Design: Using comparative data only allows for two distinct different variables to be analysed against one another (in this case animal vs plant based diet), and doesn't necessarily allow for a third variable between the two, which for my research could be a mix of both animal and plant based protein, to be taken into consideration.
Data Collection Method:
an interview, by itself will not give enough of an indication as to how well the athlete performed, as it will be purely the subjects opinion on themself, without taking into account any statistical data, or fact, and this can skew results to make them bias, and therefore not accurate or reliable. Using field-based data will allow the athlete to perform in their natural sporting environment, but  however this method alone would not have given enough of an indication as to the subjects feel of the performance-how easily the athlete was able to overcome fatigue as an example. This would mean that data is not detailed enough, and cannot give enough of an insight as to the effect and benefits of the diet. This is why I have combined the use of both.
Chosen Subjects/Environment: ■The number of subjects could be a limitation in the sense of having a larger number due to COVID-19. This will limit the number of performers I will be able to use for my research project, which could then impact my results through them being completed to a smaller scale, making them less accurate and reliable. Also the subjects I have chosen to use are all from a similar background as are all regular swimmers. This could mean that a narrower range of data will be produced by this research project.

# data[].attributes.body
Qualitative Data
Data Collection - How will you collect your data ? I will use online questionnaires which will consist of open and closed ended questions.

Raw Data Process: How might you use coding to start highlighting key aspects of your information ?

1. Step 1: Open - i will highlight key words used by the participants within their answers

2. Step 2: Axial - the highlighted words will then be put into categories

3. Step 3: Selective - i will see how these categories can relate to one category and i will be able to remove any categories that do not support the data

for the closed questions - i will put the data into tables so they can be easily compared

Displaying the data 1 : Would you use a table to display your initial coded information ? To display this data I could use a radial diagram to so the results from each question. This will allow me to see any similarities as well.

Displaying the data 2 : How else might you display the data eventually? (x4 choices = Venn, Network, Radial, Cycle)
I could also use a venn diagram to show the difference and similarities in the results. This will allow me to analyse the different information and see how the participants perspectives differ.

Displaying the data 3 : Could you use a "Thematic Analysis" method to display your data ?
Using thematic analysis will allow me to

Data verification - What method would you adopt ? i will use member checking to see if the participants agree with the results

# data[].attributes.body
Data Collection - I will collect my data through questionnaires by open and closed questions.

Raw Data Process:

Step 1: Open = I will start off by highlighting the key words that the participants have used in their answers.

Step 2: Axial = When I find the key words, I will put them in categories so they are in groups, so I will be able to identify the combine themes easier.

Step 3: Selective = I will then identify one singular category and will then use it as my main theme/ topic area. Once I've found the main topic area in a category, I will then link it to the other categories for further research.

Displaying the data 1 : I will use a table because it will help me find the categories/ themes easier which will help me when transferring the information into diagrams.

Displaying the data 2 : I will display my data in a variety of methods such as pie charts, bar charts, a Venn diagram and in a line graph. I will use these as it sets out the data in an easy way so I am more likely to spot patterns easier for the analysis part. I would use a line graph because it will be helpful when finding the relationships and differences injury prevention rates have changed over time.

Displaying the data 3 : A thematic table might not be suitable for my research as it can lead to a lack in coherence with my researched topic areas/ categories I have found in my research.

Data verification - I will not be doing a double entry method as it won't be needed with the research I'm investigating therefore I will be using proofreading because it will ensure that all my data will be reliable to use.

# data[].attributes.body
Qualitative data:
Data collection - I will collect my data using online questionnaires (open and closed questions).
Raw data:
Open coding - I will highlight the key words in the answers from the open questions.
Axial coding - I will put the most common answers into subcategories.
Selective coding - I will select one of the categories to be the core category and relate all the other categories to the main one.
Displaying the data 1 - I would use a table to display my information as it will be simpler and easier to read than writing paragraphs.
Displaying the data 2 - I will display my data using a bar chart as it easily shows each category and allows me to compare the categories to each other without being confused.
Displaying the data 3 - A thematic analysis may not be appropriate as a way to display my data.
Data verification - I will proofread my work to ensure I haven't made any mistakes.

# data[].attributes.body
1.       Gain Ethical Clearance

2.       Each candidate will be asked to complete a consent form

3.       Each candidate will be asked to complete a physical assessment to avoid injury

4.       Each Individual must complete baseline vertical jump test

5.        Each Individual must complete baseline broad jump test

6.        Each Individual must complete baseline squat 1RM

7.        Each individual will be asked to Take their initial Bodyweight

8.       Start phase 1 of strength programme (Flexibility + Stability) (Week 1 + Week 2)

9.       Phase 2 (Week 3 + 4) Strength phase

10.   Phase 3 (Week 5 + 6) Power + Plyometric Phase

11.   Phase 4 – De-load Phase (Week 7)

12.   Complete Vertical Jump Test

13.   Complete Broad Jump test

14.   Complete Squat 1 RM

15.   Take Bodyweight

# data[].attributes.body
considering validity is important to ensure my results are factually correct. a set of results that are not factually correct would be a problem as results would not be believable or publishable, it would come across as the researcher has just made up the results to suit their own preferences. it is difficult to ensure validity is portrayed with covid-19 as participants may rush their involvement and not perform to their best to get it done and over with
internal validity involves pts changing and not performing their best in certain aspects of the research so may gain not truly accurate results as pts havent put their best effort across
external validity is how easily the results can be applied to other groups/cultures. therefore this research has high external validity because bowls is a sport only played in england so having a large quantity of players from around the country will give high external validity

# data[].attributes.body
1. Gaining ethical clearance and permission from derby college and tutor

2. Get all participants to complete the consent forms which will be checked and confirmed

3. Ensure your understanding of the project and the aim of collecting the data

4. Research previously used questionnaires to evaluate the questions

5. Design an online questionnaire with suitable questions for the participants to collect suitable data

6. Verify all questions in the questionnaire to check they are valid and understandable

7. Introduce the participants to the research project and why they are beneficial in collecting the data

8. Provide instructions for the participants to follow when completing this process on the day

9. Answer any questions the participants have about the study

10. Provide them access to the online questionnaire

11. Allow the participants sufficient time to complete and fill out the questionnaire

12. Create a table to present the online questionnaire results in, containing all the participants answers

13. Outline/ summarise the main results, trends and patterns from the table

14. Compare the current research project ideas to past journals

15. Present the data as graphs, charts and tables which visually represents the findings of the research project

16. Calculate descriptive statistics: mean, standard deviation, mode, and range

17. Calculate Chi test and T test values

18. Use Chi test and T test to evaluate results further

19. Compare the final results to other research projects around this subject

20. Create a document to feedback the results to the participants, supporting the key findings and their input by participating in the questionnaire

# data[].attributes.body
1. Write down the title of the study you are going to carry out.

2. Find journals to use for secondary research.

3. Find participants to use for collecting your primary data.

4. Create an introduction for why you are choosing this title.

5. Make an ethical clearance form

6. Gain an ethical clearance form from tutor, and from Derby College.

7. Give participants consent forms, so it is ethical.

8. Create a questionnaire format and think of the questions, for primary data.

9. Ask the questions to the participants involved in your study.

10. Once the questions are answer, collect the findings, and code it.

11. Put the findings in a format so they are easier to read, such as a bar chart, a pie chart, or separating the answers into categories to observe them easier.

12. When the findings are in a format to use, analyse the data.

13. Write an overview of these findings.

14. Find secondary research, through the internet or the journals selected.

15. Get that information and put the findings into a format again so it is easier to compare and observe.

16. Analyse this research, linking back to your chosen topic, using coding.

17. Overview this topic and its findings.

18. Create a conclusion.

19. Add references throughout the work.

20. Add a bibliography.

# data[].attributes.body
1.) On day one of the research, the participant will undertake a diet based on animal protein. It will be high in meats and eggs, and they would need to consume approximately 2000 calories per day, as well as drinking 3 litres of fluid.

2.) The participant will continue this diet for a week.

3.) On day seven of the diet, the participant will take part in a timed 50m freestyle and butterfly swim

4.) They will need to consume 2000 calories worth of energy during the day, BEFORE doing the event

5.) They will need to start the event from a dive off a starting block

6.) When ready to do so, the participant will be set off to swim the 50m freestyle, someone will need to start a stopwatch as they are set off.

7.) The participant will finish the event, and the stop clock will be stopped, and the time recorded

8.) The performer will then be asked a set of questions asking how they felt whilst swimming, and the answers to these will be written down.

9.) The participant will rest for five minutes before repeating steps five to eight again for butterfly instead of freestyle

10.) Following this, the participant will finish the rest of the seventh day consuming animal based products

11.) On the eighth day, the participant will begin a diet that is plant based-a vegan diet. They will also need to consume 2000 calories a day, and consume the same 3 litres of fluid a day.

12.) On the fourteenth day of research, the participant will once again perform the same two 50m events

13.) They will need to consume, again 2000 calories that day BEFORE participating in the timed events

14.) The timed performance will need to be under the exact same conditions as steps five to nine.

15.) These times need to be recorded and the answers to the questions recorded separately, and clearly marked which diet the performer was on for the data.

# data[].attributes.body
Research method = research method is qualitative, which creates data that is difficult to produce however I can get round that by using Venn diagrams to show the data I find.
Research design = I am using comparative designs which means operationalising variables may interfere therefore it might change the results linking injury rates with prevention programmes.
Data collection = I am using questionnaires. Limitations of this is that individuals might get distracted and divert their attention so the results I collect might not be reliable to use.
Chosen subjects/ environment = Because of the corona virus, giving out questionnaires to individuals will be harder than usual.
Chosen variables = I'm doing it on prevention programmes and injury rates, which could be a topic where there has been little data on so for secondary data it will be difficult finding some if it isn't popular.

# data[].attributes.body
Quantitative data

Data Collection - To explore the relationship between socio economic group and participation in sport, I will create an online questionnaire. It will ask the participants the same  closed questions with  the same choice of answers.

Raw Data:  Once the date is collected, I will transfer data from each question into an individual table so they can be compared for data analysis. As well as all the data in one table so I can evaluate the overall results of the questionnaire.

Descriptive Statistics:  I will use the means of each question to work out the overall general response to each question. Standard deviation will be calculated to work out how spread the data results are. Mode will evaluate the most frequent response to each question and the percentage of participants who answered with the most popular answer.

Display the data: I will create bar charts to display the data collected, showing how many participants picked each answer, in comparison to others. In addition to line graphs which could be used to show the relationships between questions ad be shown visually.

Statistical testing:  I will calculate a chi-square test as I can use it to compare observed results with expected results. It will determine the difference between the data collected and can suggest relationships between different variable in the questions.

Data verification: I would adopt triangulation as member checking may lead participant to feel exploited as the questions asked should be kept confidential due to exploitation of individuals backgrounds.

# data[].attributes.body
Research method: Qualitative data may be time consuming as it requires the participants to answer the questions in detail. Because of this they could get bored and decide not to continue with the questionnaire.

Quantitative data will not provide me with as much detail compared to qualitative data which may cause difficulties when coming to evaluate the reasoning for these result. This could also be misleading because if I do a scale of 1-10

question participants may have different views on the value of each number. This could cause the results to be unreliable.

Research design: I will be using a comparative research design

Data collection method: I will be collecting all my data using questionnaires due to COVID-19 restrictions. There will be a mixture of open and closed questions. Limitations of this is that there is no face to face interaction meaning the
participants may not be able to put what they think all down onto the questionnaire. There will be less explanation for the answers and may be hard to understand what the participants mean.

Chosen subject: due to limitations with COVID-19 the participants will have to be contacted online which could cause issues if there are any problem with technology.

Chosen variables:

# data[].attributes.body
1.     Gain ethical clearance for my research from college and teacher

2.     Get consent forms signed by the participants

3.     Health screening – has anyone been in contact with anyone with COVID-19, have you tested positive for COVID-19 in the last 2 weeks, have you had symptoms but not been tested?

4.     Get permission from my teacher to conduct the study

5.     Create a table/observation sheet to collect my findings

6.     On the day of the research, I will instruct the participants as to what exercise they will be doing, and how I will collect data

7.     Measure their heart rate using a pulse monitor before exercise

8.     Individuals will then take part in High Intensity Interval Training (HIIT)

9.     Once completed the exercise measure hr again immediately

10.  6 individuals take part in passive recovery, and 6 will do active recovery

11.  After recovery measure hr to see how much it has decreased by

12.  Create two tables for my findings, one for passive recover and the other for active recovery
13. I will do the same thing once every week for 3 weeks to ensure that my results are reliable.

14.  Put my results into these tables, and create a line graph for each recovery type

15.  Work out the average decrease in heart rate for each method

15.  Compare the averages on a Bar chart

17.  Create a t-test for my results to shoe the difference in heart rate immediately after exercise and after recovery

18.  I will then feedback my results to the participants and get their opinions on the data

# data[].attributes.body
1.Data Collection – Data will be collected from a field based environment, monitoring the time it takes for each subject to do a 50m sprint. This will be recorded on an observation sheet, alongside the stroke rate for the first ten, and last ten meters of the 50m.
2.Raw Data: Data will be set recorded in a table, with three individual times per diet, with a  mean time following this, and then the stroke rates for each of these times in the next columns, aside a mean stroke rate also. 
3.Descriptive Statistics: A mean can be used to show the average time it takes to complete the 50m, and will make it easier to compare the animal based diet versus the plant-based diet, rather than having six different values. Percentage difference between the plant diet, and animal diet could also be used. This would mean we can see the direct effects of each of the diets quite simply. Standard deviation could also be used (if the time is in seconds) to show how far each of the individually recorded times differs from the average, which could display if one diet results in a quicker fatigue (if the results are further from average).�4.Display the data: The data for stroke rate could be displayed as a bar chart-the first 10m stroke rates in one colour, and the final 10m stroke rates in another colour. From there the differences between plant vs animal diet will be obvious, but also the difference between start and end will be visible, and we can see whether the plant or animal based diet produced a greater level of fatigue. A pie chart may also be used to show the percentage change with stroke rate, from start to finish of each performance, and then also for the mean stroke rates for plant based and animal based diets.

# data[].attributes.body
1.     Note down the name of the study and what I am researching

2.     Make an ethical clearance form

3.     Make a consent form

4.     Gain ethical clearance from my tutor and from Derby College.

5.     Find 10 participants to use to answer a questionnaire.

6.     Give the participants of my study a consent form.

7.     Create a set of questions for my questionnaire on survey monkey.

8.     Hand out the survey to the participants

9.     Give the participants the right to withdraw at any time

10.  Collect the results from the survey

11.  Categorise participants in terms of gender, age or sport played.

12.  Write an overview of what the questions were to introduce the topic

13.  Compare the results found by categorising the data into sections and putting it into a format like a bar chart

14.  See if there is any correlation between mental health and injury in sport

15.  Conclude the findings of the experiment if there was any difference found and in how many participants

16.  Find secondary research which for elite athletes

17.  Put research into a format such as a bar chart to make it comparable

18.  Compare my findings to other research found and see if there is a difference or whether it is the same

19.  Write a conclusion about my findings and how they are similar or different to previous research such as in the journals

20.  Write references for the secondary research used

# data[].attributes.body
Impact of sport injury on athletes mental health and wellbeing

Qualitative data
Data collection - Online questionnaire (mixture of closed and open)

Raw data -
Step 1. Coding -  Highlight key words found from the questionnaire in each answer

Step 2. Axial - I will find common themes across the answers found from the questionnaire and make categories for them to group them.

Step 3. Selective - identify a single category which is the main focus and then relate this towards other themes found and link it to the other categories found to form a correlation

Displaying the data 1- I would put my coded information in a table to find out the frequency found of results
Displaying the data 2 - I would then display the data using a bar chart to show the frequency of a theme found as well as a pie chart, Venn diagram and a scatter graph to show mental wellbeing before and after a sport injury.
Displaying the data 3 - A thematic table wouldn’t be suitable to use for my aim because it can cause a confusion between whether mental health is the reason for a decline in sport performance

Data verification - I will adopt the proofreading data method and get another person to check over my data and ensure it has been written correctly.

# data[].attributes.body
1.       I will be creating a questionnaire to ask 10 individuals what they think about my research project and the issue it is investigating.

2.       I will ensure no questions could possibly be taken offensively and research the best wording for the questions as it is a very current topic and issue.

3.       I will research appropriate questions to ask regarding my topic and what will give me the best results and opinions.

4.       I will perform systematic sampling in asking participants to answer the questionnaire, so I get a less biased general opinion. They will be asked age to inform me with different opinions and knowledge across different ages.

5.       Closed questions will be taken and converted into percentages to be able to compare answers. Open questions, I will break down and collect specific terms that are commonly used, and which are relevant to my topic. With this I will then convert to percentages again for later comparison

6.       I will compare my data to previously collected data by collecting results from similar questionnaires and research projects

7.       I will discuss my results and compare to the research I have undergone to compare how much the audience knows and understands about the sporting policy around my topic, however, their personal opinions will be analysed in a way that will help me understand their views on the topic and whether things should change

# data[].attributes.body
I am using a mixed research method of both qualitative and quantitative data. This may have limitations as both data resources will be different and may be difficult to compare. Due to the topic being current, individuals answering the questionnaires may not have much knowledge and will therefore not be able to give clear, definite answers. This will limit the analysis and overall results.
Regarding the questionnaire, sampling strategies may be a limitation, i will be using systematic sampling to get my results, however, this is not fully random sampling. Therefore, there could be limitations of answers being biased due to the population answering the questionnaire will be biased.
I am also taking data from articles and online resources, due to my topic being a new and current topic, this may have limitations as there may be limited data collected on this topic. Therefore, i will not be able to have a massively wide variety of opinions and research to include.

# data[].attributes.body
20 step guide for my research project.
How does stress and anxiety effect sport performance for students.

1. Research key areas to help me word my questions allowing me to gain the best answers from my participants.
2. Start to write out my questions taking time to ensure they are completely aimed towards answering my question.
3. Ensure my survey has enough questions to gain the correct amount of research which will allow my project to hold a good amount of information.
4. Send my survey to all of my participants.
5. Ensure that they know I have sent it to them and that they need to fill it in with a good amount of detail ensuring it is relevant to my topic.
6. Receive the surveys back.
7. Check through the surveys and ensure that they all include useful information.
8. Analyse all the information within the surveys to ensure it will be useful for my project and there is enough to use.
9. If there was any areas within the surveys that could include more useful information, send it back to those participants and ask if they could clarify that information.
10. Once all surveys are completely finished and I have received all the data, go through it and highlight any important information which is key for my project
11. Create a word document and make a table,  writing down all the key information that I have chosen to include in my project, under each participants name.
12. Highlight the information within the table under each participant which seems to differ between them and also the information that is the same. This will help me make the conclusion to my research project.
13. Begin to come to a conclusion of how each student felt that their stress levels affected their sporting performance.
14. Analyse the differences between the two genders and see if there was a clear difference between the affect of stress on males and females.
15. Analyse the differences between students studying a-levels and students doing a degree and see if there a clear difference between the affect of stress on college students and university students.
16. Complete a conclusion for my research project as to how stress and anxiety affects sports performance for students, whether this be a clear conclusion or a conclusion where the a multiple different answers.

# data[].attributes.body
•Reliability in my research is important because it makes the results more accreditable and means that they are more accurate. It makes the investigation more consistent and valuable.

•This is considered in many parts of my study since I won't be monitoring training or diet just intake of creatine and 1k test results.

•To test for reliability I will be using test-retest. We will be completing the test over many different occasions to see if the results are on track and like previous tests with little to no anomalies.

•I will get the participants to complete the 10-minute warm up and the 1k sprint test over at least 4 weeks to get an idea of improvement and reliability.

# data[].attributes.body
How does stress and anxiety affect sport performance for students?

1. Data collection- how will you collect your data?

Online survey/questionnaire using mainly open ended questions.

2. Raw data process- how might you use coding to start highlighting key aspects of your information?

Step 1: open

I will read through my participants surveys thoroughly and begin to pick up any similarities within their answers. Also, I will get a clear idea of their mood towards the question, whether they mainly agree or disagree. I think many of my participants will think that their stress and anxiety does effect their sporting performance, making them not perform as well as they could when they aren’t as stressed

Step 2: axial

Again, I will thoroughly read through each person’s survey and try to find their main idea about each question that I have asked them.

Step 3: selective

This is the stage where I will bring together the individual’s ideas and take into account the similarities and differences between their answers.

3. Displaying the data 1- would you use a table to display your initial coded information?

I think a table would be useful when I initially code my information because it will keep each participants data separate and allow me to fully analyse it without confusion.

4. Displaying the data 2- how else might you display the data eventually? (4 choices= venn, network, radial, cycle)

I could use a Venn diagram to display my data taking the points where students agree with the fact that stress and anxiety effect their sporting performance and then the opposite. This will also allow me to include those participants who don’t give a clear answer on if they believe that mental struggles decreased the level of their performance.

5. Displaying that data 3- could you use a “thematic analysis” method to display you data?

This would be very helpful for my project as it will allow me to identify the majority of participants who either agree or disagree with the fact that stress and anxiety effects sporting performance.

6. Data verification- what method would you adopt?

Member checking would be useful for my project because the participants will not know what the others have put, therefore, when I have fully analysed my data I can see how many of the participants agree with the final result. This will also allow me to identify any anomaly’s in my data.

# data[].attributes.body
Research method - qualitative data
A limitation of this method is that it may be hard to draw comparisons between the answers gained because they will be from open questions. This means that I will have to categories answers into sections and then compare them.
Research design - I am using the comparative research method. A limitation of this could be that it may be difficult to measure the change of mental health in participants because I am measuring data after the injury occurred and not collecting data on what they were like before. I can only ask them the question of what they think has changed in it.
Data collection method - Questionnaires and interviews are my collection methods. A limitation of a questionnaire is that it is time consuming to analyse the data and so I will have to categories all answers to be able to compare them.
Chosen subjects - If I am using participants from just Derby then the results could differ to other areas of the UK depending on the competition levels of teams in sport, which could have additional pressure on athletes and for example make them feel more scared if competing at a higher level.
Chosen variables - My chosen variables are mental health and sport injury. The limitations of this is that different individuals have different levels of what they consider a big injury and therefore different types of injury impact other people in different ways. This can be also affected by what sport they play, for example if a footballer has a leg injury it will impact them a lot more than if a table tennis player had a leg injury.

# data[].attributes.body
1. The limitations of my chosen research project is that I am not guaranteed to have an average result in the end due to the fact that I have picked to use quantitative data. This means that my research may end up confusing and without a useful conclusion.
2. The limitations to this research design could be that my participants may struggle to remember a time when they felt stressed, and how this emotion affected them through their sporting performance. Also, I have chosen comparative data when analysing my research which could cause a limitation as only two ideas can be compared from one and another. If each participant has a different idea to the questions I have asked them, this may make it a hard and lengthy process to compare them all to each other.
3. My chosen way of data collection may not be completely successful as all of my participants will need access to the internet as this is where my survey will be. Also they may struggle to find the time to fill the survey in if they are busy with their studies.
4. There may be limitations to my project through the environment as there is no physical activity included within my research. This would be impossible to include as my all of my participants are unlikely to be under a substantial amount of stress at the same time, therefore my data collection would become inaccurate however, it may have been useful for my project because I could include a primary view on how their sporting performance had altered due to stress and anxiety.

# data[].attributes.body
Why is considering reliability in your research important?

Reliability is ​the degree to which the result of a measurement, calculation, or specification can be depended on to be accurate. Therefore, the research carried out must be reliable as it used throughout the project. This then means there is no negative impact on the overall results of the project as the sources of research and main research is trustworthy.

How have you considered this in your study?​

This is an important factor to consider in this study. When relating to my literature reviews, I have compared the date to make sure it is relevant to the current project. When collecting the data, I have also checked there is no complete anomaly which differentiates itself form other participants majorly.

How are you testing for reliability ?​

I will test for reliability by comparing sets of data and analyzing the data which will give me different sets of numbers. These can be compared to previous research project results as well as calculated results across the internet to check the similarity and reliability.

Could you / will you look to use any of the following?

Inter-rater reliability could be beneficial in this research project as it can measure the consistency between each participants as it is the agreement of the same data obtained between individuals. If my results produced are similar, it will demonstrate a high reliability within my project as similar answers will be inputted by participants.

# data[].attributes.body
Research method- A limitation could be the data may not be robust enough to develop a complex explanation in my results form the project idea. This mean detailed comparisons need to be made from the calculations and graphs to provide an overall effective summary.
Research design-
Data collection method-  A limitation is people can understand the context of questions differently, therefore impacting their answer. The questions are closed so the participants are very specific and certain, they can't express their opinion or state a situation which was behind their reasoning for the answer. This means the questions must be understandable for all participants to be able to answer them confidently online, having a positive impact on the overall results. Also, participants answers might be dishonest as questions are personal to them
Chosen subjects-
Chosen variables-

# data[].attributes.body
Why is considering validity important?​

Validity is the quality of being logically or factually reasonable which is important. A complete set of anomaly results wouldn’t be valid as they wouldn’t be believable, therefore decreasing the level of reliability. This has a negative impact as the research project is viewed upon as pointless and the final results aren’t very beneficial.

What validity issues are you having ?

Due to the current situation of COVID19, carrying out primary research face to face would be debatable. Therefore, the participants taking part in the collection data process must provide truthful, valid information giving the view of the overall results to be valid and reliable. In addition. I have no access to expensive methods to collect data​, so the data collected may not be 100% valid due to the method not being as professional or accurate.

Internal Validity ​

The validity of this project is debatable as the participants answers can differ majorly, so one answer can have a negative impact on the overall results which could be seen as wrong in comparison to predictions and previous calculations from projects. For example, if every participants chose the category of yes but there was an anomaly of no, my overall results will be impacted. All participants will be given the same knowledge, understanding and time limit of this project so they all have the same interest and idea when answering the online questionnaire.

External Validity

This is the extent to which the results can be generalized to other contexts such as different groups of people and situations. Therefore, this study has high external validity as the results are very generic and can be applied to different cases as participation rates in other subjects can be affected by the factors I am investigating throughout this project. Factors such as geographic location of individuals, or previous college financial situations could possibly used to evaluate other studies like income spent on extra curricular activities.

# data[].attributes.body
1. Reliability is important for my project because it allows my data and overall conclusion of my research project to become more believable and credible. It will make others who look over my research project believe that my work is likely to be true.
2. Throughout my research project, I will use journals as a form of secondary data to provide a reliable source to my project. I can link my findings to the journals conclusions and see how precise and therefore reliable our findings are.
3. I’m going to use member checking as a form of inter rated reliability. When the participants have completed the survey and I have analysed them to gain an overall conclusion, I will ask them if they agree or disagree with the overall answer. Also, by analysing my participants answers I will check for reliability to ensure I’m not including irrelevant information within my research project.

# data[].attributes.body
Qualitative research – the volume of data produced can make analysing time consuming, and also the influence of having the researcher there may throw the participant off and affect hard they work, which will affect the results, and make the end results less accurate.

Data Collection – Using this type of data only allows for two types of recovery methods to be analysed against one another and doesn’t allow for a third method to be considered. Therefore, if I were able to introduce low-frequency electrostimulation my project would be more accurate as to which recovery technique is the most effective, however this is not possible.

Data Collection – It isn’t guaranteed that the heart rate monitor that I will be using won’t be faulty, and there is the aspect of human error, as if the researcher sets it up wrong or misreads the monitor this will make my results less accurate.

Chosen Subjects – There will be 10-12 subjects with equal numbers of men to women, however the age range of my study is very wide, and if an individual is injured or ill they may not work as hard as they would if they were 100% fit.

# data[].attributes.body
1&2. Reliability is important in my research project as there are several variations of the research i am doing. Therefore, i need to be able to separate each one into their own topics to be able to analyse accurately. As this is mostly a psychological research project, the reliability has to be done well as it must show if it has fulfilled any hypotheses and to make sure that the results don't answer any outside topics that aren't relevant.
3. I am testing for reliability by analysing my data to ensure that questions from my questionnaire doesn't lead the participant to give an irrelevant answer that does not relate to my project.
4.

# data[].attributes.body
•Considering validity is important because it shows to what extent your research project is measuring what it claims to measure, this is important because it allows other people to apply and interpret it.

•Some validity issues that I am having is the fact that my participants are free eat and train how they want if they are consuming the 5g extra of creatine, this may cause different invalid results.

Internalvalidity:

•Low internal validity, I am combatting this by having a smaller test group size so and persuading them to continue with regular training and similar diets besides creatine intake. (Their own personal choice impacting this).

External validity:

•High external validity because it can easily be applied in other settings, as this investigation is easily reproducible (with relatively similar results) on any demographic or group, if the external environments were the same.

# data[].attributes.body
Reliability is vital in my research project as this allows for my research to be accepted, and for my overall judgement on which diet is more effective, to be credited and possibly used by amateur level athletes. If unreliable, then my result of the project will not be seen as true, and so will be disregarded. Reliability in my project may also provide a base for more research on similar, or the same idea, to be completed in different sports, or contexts.

This has been considered in my method. Through repeating the timed performance, and then being able to gain an average, this means that my results are less likely to be skewed, or contain any anomalies, thus increasing the reliability. Further to this, I have also used academic journals to make sure that my ideas coincide with already existing research, so that I do not stray from having bias data, which can be caused by having a completely different approach than other people to my idea.

I am testing for reliability through calculating means and standard deviations for stroke rate and time, which can show how accurate my results by displaying how far the data tends from the “normal”.

If any times or stroke rates provided by the research seem overly high or low compared to what is deemed “normal”, I could possibly look to retest for that performance, to see if a different result is provided, as the first may be an anomaly. This will increase the reliability of my research, as it decreases the risk of anomalies contaminating the data.

# data[].attributes.body
1. Validity is important to consider through my research project because it will allow me to choose specific questions within my survey that will help me the most to gather an overall conclusion. Also,  it will ensure that my questions are relevant to my topic and that my survey overall is guaranteed to give me enough useful information.
2. The validity issue that I am having is that, it may be helpful for all my participants to meet after they have completed the survey to talk through the overall conclusion which I have made through their data. This cannot happen due to COVID and therefore I will have to speak to each participant individually rather than as a whole group.
Internal validity:
1.  My study has low internal validity due to the fact that my participants are telling me how their sporting reform aces was affected in the past by the feeling of stress and anxiety. I am not physically observing this and so I have to take my participant’s word for what they are telling me. As a student, stress and anxiety isn’t felt all year round and so it would be unreliable to observe all participants at the same time, when their stress levels are at different points. This means the survey will ask them about a time when they did feel overly stressed or anxious so, it cannot be confirmed that what they are telling me is the truth.
2. I’m controlling my variables by using participants who I know and trust to tell the truth throughout the survey that I will ask them to fill in. Due to this, my data will increase in validity because although it cannot be guaranteed that they aren’t lying, I can trust them not to.
External validity:
1. The external validity within my research project is at a high level due to the fact that there are many journals and other research methods out there that explain how stress and cognitive anxiety affect sporting performance. My research project is essentially mirroring this research, however I have made it more specific by solely focusing on students and how their high levels of stress and anxiety alter sporting performance.

# data[].attributes.body
-       This is important in my research as it means that my results are credible, and means that it fulfils it’s aims and ensures that the results are due to the study and now extraneous variables.

-       To ensure that my project is reliable I will be comparing it to data found in the journals in my literature review, which is make sure that my results are coinciding with data that has already been found.

-       I am going to be using a test-retest to confirm that my results are accurate and therefore reliable. This will be over the course of three weeks, to make sure that every week the results are of a similar standard, and highlight any inconsistencies in my results.

# data[].attributes.body
-        This is important in my research as it means that my results are credible, and means that it fulfils it’s aims and ensures that the results are due to the study and now extraneous variables.

-       To ensure that my project is reliable I will be comparing it to data found in the journals in my literature review, which is make sure that my results are coinciding with data that has already been found.

-       I am going to be using a test-retest to confirm that my results are accurate and therefore reliable. This will be over the course of three weeks, to make sure that every week the results are of a similar standard, and highlight any inconsistencies in my results.

# data[].attributes.body
The relationship between supplements and sports performance  compared to the source within real food

Quantitative data:

Data Collection - How will you collect your data ? (e.g. observation sheet)

To record how energetic people feel throughout the day based on their intake of either supplements or 'real food', I will use a questionnaire with numerical values. The questionnaire will represent energy levels eg from 1 being exhausted to 10 being over energetic. To monitor the effect of foods on sport performance I will be recording running times using a stopwatch.

Raw Data: How will you set out your data once collected ?

Once the raw data has been collected for both I will display this just simply in a table. For energy levels I will have 'energy levels across the top and time down the side. For performance times I will also use a table to record the data with time across the top - sub divided into supplements and real food- and the names of participants down the side. This will allow me to clearly understand the data ready to be displayed later on.

Descriptive Statistics: How might you use descriptive statistics and why ? (e.g. means, standard deviation, %’s etc..)

I will work out the range (using performance times as a percentage increase/ decrease) to show how supplements can impact people differently - whether it greatly impacts some peoples performances or whether little difference is noticed at all.

I will also find the mean of percentage difference before and after supplements intake on performance. This will give me an average affect of supplements on sports performances making it more generalisable to a large population.

Display the data: How might you display the data ? a. (bar/scatter graphs/pie charts etc…)

One I've collected the energy levels data throughout the day I will display the results on a line graph. With time on the x axis and energy on the y axis it will shows a clear and visual representation of how foods vs supplements affects people over time. Also, with the performance times data I will work out a percentage increase or decrease after intaking supplements, and display this using a column chart. This will clearly show the direct impact of supplements on sports performance at a glance (increase/ decrease in running times).

Statistical testing: What statistical testing will you apply and why?

Data verification - What method would you adopt ?

# data[].attributes.body
Considering the reliability in my research is important for producing credible results. Using results that are credible provides evidence that my study is valid and that findings answer the aim of the study.

This has been considered in the study as I will use a candidate to start and stop the stopwatch as the start and finish of participants performances. This will ensure high internal consistency and stable results ensuring good reliability.

# data[].attributes.body
1. Gain ethical clearance from Derby college before taking any further actions into the study
2. Ensure consent from all participants is recorded
3. Complete a health screening to ensure that participants haven't got symptoms, been with 2m of somebody who has had covid-19 recently or have tested positive for the coronavirus in the last 14 days
4. Follow up with a briefing to inform participants of what they will be completing and know that they have the right to withdraw from the study at any point
5. Create a table to record time taken to run 2.5km in minutes and seconds
6. Create an additional questionnaire to collect quantitative results of participants 7. Provide the participants with the resources needed for the study and email them the tables required to input their data
energy levels throughout the day
8. Inform participants that the study needs to begin and allow them the time to complete it
9. Collect the borrowed resources and ensure their data collected is emailed back to me
10. Analyse the recored data of energy levels and input into the form of a line graph for easy interpretation of the information
11. Use the two sets of running times and calculate a percentage increase or decrease in times
12. Input this data into the form of a comparative bar chart
13.  Identify the relationship food consumption and sporting performance
14. Finalise a conclusion on the findings of the study and evaluate the aims, objectives, reliability and validity etc.

# data[].attributes.body
Quantitative Research:  As this only involves numbers, the results that I find within my research may be misleading as numbers do not explain the bigger picture (e.g. background in training etc.). This will affect the end result as the numbers may lead me to believe one thing although that may not be the case.

Research Design:  I chose to do a case study (record of research into the development of a particular group). A disadvantage of this is there may be a bias within the study as I have to interpret and analyse my findings. Also, a case study is very time consuming and may provide little basis for generalisation of my results.

Data collection method: I chose to do field based data collection as I have to carry out tests on each individual athlete. A limitation of this is that I do not have access to developed equipment in order to measure the vertical jump of each athlete accurately. This means that my results may not be 100% accurate, leading to my end result also not being accurate.

Chosen Subjects: I have chosen 6 16-19 year old male athletes. This may be a limitation to my study as the subjects have a background in training, meaning they may not see significant results as they have already built a baseline of strength/power.

# data[].attributes.body
The Effect of Strength Training on Vertical Jump and Power Production.

Quantitative Data:
Data Collection - How will you collect your data ? (e.g. observation sheet)

Raw Data: How will you set out your data once collected ?

Descriptive Statistics: How might you use descriptive statistics and why ? (e.g. means, standard deviation, %’s etc..)

Display the data: How might you display the data ? a. (bar/scatter graphs/pie charts etc…)

Statistical testing: What statistical testing will you apply and why?

Data verification - What method would you adopt ?

Data Collection - Observation sheet stating the measurements recorded before and after the programme.

Raw Data - The data will be shown in a table which shows the weekly measurements for each candidate.

Descriptive statistics - percentage change in measurements from week 1 to week 6. Mean and standard deviation.

Display the data - Show how measurements increase/decrease weekly in a bar chart/ line graph.

Statistical Testing -

Data verification -  Member checking to see if participants feel as if their measurements have increased/decreased.

# data[].attributes.body
Considering reliability in my research is important as it refers to the consistency of the results. This is important as it tests if the study fulfils its predicted aims and objectives. I have considered this in my study by ensuring each athlete does the same amount within the training program. This makes sure each athlete has an equal amount of potential to reach maximal results.
I will use internal consistency reliability to measure the overall satisfaction of each participant. This will test if each participant agrees/disagrees that they were equally trained in order to reach maximal results.

# data[].attributes.body
Considering validity is important because it refers to how accurately a method measures what it is intended to measure. This allows the method to produce results that can be compared to a more general population. One issue I will have with validity is that I do not have access to expensive measuring equipment, meaning that the results will not be 100% accurate.

Internal validity - My study has high internal validity as I am producing a a program that each athlete will follow for the 6 weeks. However, something that can impact this is maturation. This is normal changes over time (e.g. fatigue). This will impact my study because if an athlete becomes fatigued, this will negatively affect their results as they may need to have time off etc.

External Validity - My study has relatively low external validity. This is because although my subjects may see positive results, it does not mean everyone in a more general population will have the same results. This is because vertical jump progression can also be determined by other factors such as genetics.

# data[].attributes.body
Research method - The chosen method of research I have decided on is quantitative, collecting only numerical data throughout the study. Deciding on a quantitative method, allows me to easily analyse objective findings throughout the project. However the data in this format is simple and undescriptive, and could lead to a lack of participant details in the evaluation stage of the study.

Research design - my research will be an experimental design as it involves repeated measures as the run will be carried out twice. Due to this order effects may begin to take place due to previous practice affecting the validity of results.

Data collection method - I'm carrying out research collecting quantitative data as my results will be in numerical values (time). This data will be collected using to two methods: questionnaires (to collect energy levels) and field based (to carry out the running exercise). questionnaires may lead to participant bias when giving answers (giving answers they think the experimenter wants, rather than their 'real' answer)

Chosen subjects/ environment - I will choose participants with a large age range and of both genders. This will allow me to compare the sports performances, and if supplements have a stronger/ lesser effect on different ages ranges an/ or gender. The study will take place as a park run where a simple flat circuit is required to be completed. As this will take place in the winter months the effects of weather may affect participants performances or the ability to perform normally.

# data[].attributes.body
1.      Collect a consent form from participants saying they agree to being part of this study.

2.      Get permission from derby college to conduct this research.

3.      I will be using field-based research in this study. This means I will have to record the times that the participants take to complete a 400m run. By comparing this technique with other research using similar techniques, I can get a good idea of how to conduct it, what the results are likely to be and also if the data I will be collecting will give me the results I need.

4.      I will also need to decide on four different diets that have varying proportions of carbohydrates, fats, proteins, and fibre.

5.      I will then split my group of ten participants in half and allocate a different diet to each half to counterbalance the research. They will then each this diet for exactly a week.

6.      At the end of the week the participants will arrive at a set place to complete a 400m run. I will set them off individually.

7.      I will time the participants doing their run and record the results onto an observation sheet.

8.      I will then swap the groups around and get them to eat the other diet for a week to compare collect the results from the other half of the group.

9.      Once both groups have eaten two diet, get then to repeat this process and eat the other two diets in the same order as before.

10.   Repeat steps 6 and 7.

11.   I will then calculate the mean results for each group doing each diet at a particular interval.

12.   Then I will put this information into a table to present the data.

13.   I can compare my results by finding another set of data from similar results and compare the scores with my own. This will show me if my results make sense and if I have conducted the research properly.

14.   Give a conclusion about the results table and suggest what it means. For example, a high carbohydrate diet increases endurance while performing.

# data[].attributes.body
1.      I will record the participant times and record them on an observation sheet.

2.      I will record the times based on the participants who eat specific diets. There will be four diets and the one group. This group will be split in half and one half will do one diet the first week and another diet the second week and vice versa with the other group.

3.      Once I have collected my raw data I will calculate the mean for each diet group. This will show me the average time of the groups, making the data easier to display.

4.      I will display my data in a table with the diets in the columns and then each group with their results, in the groups with raw data in the rows.

5.      For the statistical analysis I will use the chi-squared test because I am using independent groups, so the data is unrelated, and the data is nominal.

6.      I could use member checking to increase the validity of my data. This will mean showing the participants the results of the test to ensure there is nothing they see that seems unusual. For example, if one person who is usually better at running than average gets a lower than average time then this will suggest the data is inaccurate.

# data[].attributes.body
Validity is important to ensure the aim of the study and what has been set out to be measured has actually been measured. My validity may be effected by the only option to use a stopwatch to record running performance times - this can be slightly inaccurate if the reaction time of the additional candidate is slow.

# data[].attributes.body
Reliability is important in my research because it will mean my results are valid and accurate so they can be generalised and used, when analysing the data. I have considered this is my study by making sure the questions give the answers I need for my data results. I am testing for reliability by comparing the answers I get, to see if any anomalies occur so I can find out why. I will be using inter-rater reliability to see if there is a consistency in the results.

# data[].attributes.body
Validity is important because it makes sure my results are accurate. Validity issues could be due to covid-19 as I might not be able to get the results I initially wanted. My research will have low internal validity because the participants could change their answers due to other factors. It will have low external validity because it is just on football so it cannot be generalised for every sport, however it is high because of the number of journals about this topic.

# data[].attributes.body
Considering reliability in research is important because it improves the validity of results. It will mean that the results will provide consistent findings if someone else wants to redo the experiment in the future. This will allow them to be generalised to the wider population. I have considered this in my research by giving all of the participants the same set of questions on the questionnaire and the right to be anonymous so they can put true feelings down. I am testing for reliability by doing inter rather reliability to see if the same outcome is received by both people checking the results.

# data[].attributes.body
Considering validity is important because it shows that the study measures what it claims to measure to show that it is accurate. The issues with validity are that because of corona it may be hard to go out and physically speak to people to gather primary data. This may mean online methods of data collection may be necessary to replace going up to the participants and as a result less detailed answers given. Some participants may not have access to some technology so fewer participants may be acquired.
Internal validity- My internal validity would be high because I am asking the participants themselves about their personal experiences without my subjective opinion altering the results.
External validity - The external validity may be low because I am asking a small sample of participants, 10, so the results may not be generalised to the wider population. Also because the sample is small there could be anomalous results which will make it difficult to establish what the real results should look like.

# data[].attributes.body
1.      Research method- quantitative, does not give very much detail about why the participants results showed what they did. There may be crucial details missing that would have increased the validity of the study.

2.      Research design- experimental design, may lack ecological validity because the situation is unnatural, and the participants may perform differently under different circumstances. This also means it lacks generalisability because it is harder to apply to the rest of the target population.

3.      Data collection method- field based, cannot get a very big sample because it takes time to get the results for everyone, meaning it lacks generalisability. Taking observations may cause the data to decrease in reliability because the researcher may not be able to measure everything, meaning some details may be missed.

4.      Chosen subject/environment- structured observation, limitations may be that it lacks validity because the time the participants take to complete a run may not tell us everything we need to find the results we are looking for in the study. If any one the participants are not feeling completely normal they may perform differently to how they would normally, e.g. someone has pulled a muscle so they run slower than they normally would. This would affect the study because it means there is a variable that has not been controlled, meaning the reliability will be reduced.

5.      Chosen variables- diet, peoples bodies are all different, meaning they all use food differently. For example, some people have a higher metabolism, which means they would process the food quicker into fuel, so they use the food more efficiently for performance. Another limitation is that the proportions given may be too much for some people but too little for others.

# data[].attributes.body
1.      It is important to consider reliability in research because it makes the research consistent, this is because if a study has high reliability it can be repeated easily and the results can be confirmed, improving the accuracy.

2.      I have ensured that there a limited number of variables in the study to avoid confusion and decrease the likelihood that any variables will interfere with the results. For example, I have not used leading questions in a questionnaire to gather my data as this may influence participant answers.

3.      I will use inter-rater reliability in my research to check my data is consistent. I can do this by looking into other similar research and comparing the results with my own. Another way I could have tested reliability would be the test-retest method. This involves repeating the experiment to compare the first set of results with he second, this will show how consistent the data is.

# data[].attributes.body
1.      Validity is important because you need to make sure you are testing what you intend to. This ensures the data is reflecting the aim of the research, and this improves the accuracy of the study.

2.      Some validity issues in my research include the fact that it is field research. This is because there may be other contributing factors that influence the data too strongly. For example, the levels of motivation may be different in the participants so the research may be actually finding the effect of motivation on performance instead of the true aim.

3.      Internal validity- I believe it has quiet high internal validity because diet is scientifically proven to have an impact on performance, and this means what I am testing has already been proven. I am just testing how much the diet can impact the performance. For example, it has been proven that carbohydrates help give the body energy, and I am testing how this links in with sporting performance.

4.      External validity- this is lower because I am only using ten participants meaning it is harder to generalise to the rest of the target population. This may impact the research because it reduces validity, and this reduces the accuracy of the study.

# data[].attributes.body
1. Reliability refers to the consistency of the results in research. As a result, my research must be reliable in order for it to fulfil the correct criteria. This ensures that the research is correct and was not effected by any extraneous variables.
2. This has been considered into my research because it will ensure that the results are valid and the majority of the participants have similar results. Therefore, all participants will receive the same questionnaire and will be asked to complete it by a specific date.
3. To test for reliability, I will analyse the results and check for any anomalies. If there are any I will see what could be done to fix it. I will also use interrater reliability to see if they agree with the results or not. This will test for reliability as if they agree with the results, it shows that the data is correct and therefore reliable.

# data[].attributes.body
Why is considering validity important?
Considering validity is important because it ensures that my research is measuring what it is meant to be measuring.

What validity issues are you having?
Due to COVID-19, there will be no face to face interaction with the participants. This means that I will have to rely on the participants to provide honest and truthful answers when completing the questionnaires. This is in order for the research to be valid.

Internal validity
Internal validity is the extent to which a piece of evidence supports a claim about cause and effect, within the context of a particular study. As a result, my research project may not have much internal validity because answers may vary from what was predicted. Therefore, results could be affected by any anomalies.

External validity
External validity is the validity of applying the conclusions of a scientific study outside the context of that study. This shows that my research will have high external validity as the results can be applied to most parts of cricket and can also be applied to women in other sports.

# data[].attributes.body
Validity is important for my research project as it will show that I am accurately measuring which diet provides the better sprinting performance. If my research is not measured accurately, my projects findings would be deemed invalid, and so the research would be pointless.

Some limitations I am having are due to COVID-19. The number of subjects is limited, and so is the equipment I can use. As an example, I may not be able to use starting blocks as this will increase the risk of the virus spreading, and so this may slightly affect my results in the sense that the performance isn’t in a natural racing environment. This could mean the subjects do not perform as well, or to their optimum level, affecting the data produced.

Internal validity is low, as each subject is not set to a strict meal plan, they have a loose basis of calorie count and fluid intake. However, each subject will not be consuming the same meal at the same time, and so this may affect my results, as different plant based foods will have varying levels of sugar, proteins, fats, etc., and this may affect the rate of fatigue and performance level. By giving a value for how many calories are consumed however, will provide an equal level of energy consumption amongst subjects.

External validity is high, as my intended method could be applied to different sports, as well as subjects of varying sporting level, and backgrounds. This means that results can easily be reproduced, across different environments.

# data[].attributes.body
1.  Gain ethical clearance

2.  Make a consent form

3.  Design my questionnaire

4.  Find 10 participants that will participate in the study and will answer the questionnaire

5.  Introduce the participants to the research project and why they are wanted

6.  Give the consent form to the participants and let them know that they have the right to withdraw at any time

7.  Once they all answered the questionnaire, I will collect the results

8.  I will put the participants into different categories: gender, age, if they play sport and if so what sport do they play and how often they use social media

9.  I will highlight the key words in the answers from the open questions

10. I will put all of the data (participants answers) into a table

11. Compare the results between the participants that are athletes and the participants that are non-athletes

12. Write an overview of what questions were used and what I found out from the results

13. Create a conclusion about who is impacted the most by social media (athletes or non athletes)

14. If athletes are the most impacted by social media, what is their gender, age and what sport do they play?

15. See if there is any relevance with the sport they play and how they are impacted as they all may be impacted the same, no matter what sport they play.

# data[].attributes.body
Research method - qualitative data
- A limitation of qualitative data is that it is more difficult to assess and compare to the rest of results as you will have to transform the data to make it easier for you to compare. Another limitation is it is time consuming. It takes a lot of time to analyse the data you receive as the answers are a mixture of long and short (as the questionnaire I will be using will include a mixture of open and closed questions).
Research design - comparative
-  A limitation of comparative research design is that
Data collection - questionnaires
- A limitation of questionnaires is that is is time consuming.
- Another limitation is that the participants may give socially desirable answers. This means they will give the answer they think I want or expect from them instead of their own. This can reduce the reliability of the data.
Chosen subjects - The participants that I will be using to answer my questionnaires are all from England. This is a limitation because I cannot generalise this to the whole population (e.g other countries in the world).
Chosen variables - social media
- A limitation of this is the hours spent on social media every day for each participant may differ. Some of them may spend 2-3 hours on social media a day whereas others may spend more time or even less time. By spending more time on social media, this could perhaps affect/impact the participant more than the ones that spend less time on social media.

# data[].attributes.body
Considering validity in a research project is important because a valid measurement and result is seen to be most reliable and accurate.
In my research project, i do not have too many issues as validity is mainly considered to be important with quantitative data. The quantitative data i will be using is closed questions in my questionnaire, these will be valid as they will be limited multiple choice answers.
1. My research will have quite low internal validity, this is due to it not investigating a program or how it would change the end outcome. There will be no possible changes during my research that may have improved or decreased.
4. I think my research has quite high external validity, this is because my findings and results will ultimately result in a generalized conclusion which will be linked to a larger, general context of my title. Due to me using qualitative data, it is hard for me to identify one answer and set of figures as i am having to generalize and categorize some of my results. This will help me with my final conclusion, however, will possibly be difficult to understand the direction of my research.
5. The accessibility and wide range of articles around my topic will impact the external validity, this is due to not being able to have a full, wide range of articles as i must limit the amount of data i am able to collect.

# data[].attributes.body
Considering reliability in research is important because the results need to be accurate. I have considered reliability within my study

# data[].attributes.body
Considering validity in research is important because you need to make sure that the results are accurate. Due to covid-19, there will be validity issues. This means I may not be able to travel to the participants and meet them in person and speak to them about my questionnaire. Therefore, I would have to give them the questionnaires electronically and gather my data online.