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Question 1:
a) Probability sampling methods (explain the peculiarities and give examples):
1. Simple Random Sampling

2. Cluster Sampling

3. Systematic Sampling

4. Stratified Random Sampling

Question 2:
b) Non-probability sampling methods (explain the peculiarities and give examples): 1. Convenience Sampling
2. Judgmental or Purposive Sampling
3. Snowball Sampling
4. Quota Sampling

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a)Probability sampling uses random sampling techniques to create a sample. Probability sampling is based on the fact that every member of a population has a known and equal chance of being selected. It helps reduce discrimination and bias . It is more objective also . Question 1:

1.   Simple random sampling is considered the easiest method of probability sampling. Respondents are chosen randomly and everybody has equal chance to be chosen. For example BMW wants to learn attitudes of its customer about a new car idea. The company randomly chooses its respondents among the customers

2.   Cluster sampling is conducted when the size of a population is too large to perform simple random sampling. In this method you choose the participants on the basis of some criteria such as gender, age, nationality etc. For example we can conduct a research about use of bicycles in traffic in the Caucasian countries. So we just have to ask the drivers for an answer.

3.   Systematic sampling is a research method in which the participants are chosen at certain intervals. For example if you are examining a hospital that has 100 patients about the quality of healthcare, you will have to choose the first respondent firstly. For instance I choose patient N4. Then I choose patient number 10, 16, 22, 28… As can be seen I chose my respondents at a predefined interval.

4.   In this method, members divided into small groups and small groups are formed in the basis of the some common features such as socioeconomic status, level of education and so on. For example we can conduct a survey among graduates of law faculty about their current economic position.

Question 2

1.   Convenience sampling is a non-probabability sampling method. When there is time constraint this method is used. It is important how easy it is for you to get in touch with respondents. For example I conduct a survey about life in quarantine and I can just get in touch with my family, friend etc.

2.   Judgmental sampling is a method in which participants are chosen by the researcher himself. For example if I conduct a research about traffic problems in Baku, I will not ask anybody who doesn’t drive a car any questions.

3.   Snowball sampling is a method in which sensitive topics are discussed. For example if you conduct a research about something that considered a taboo in a particular society (of course I’ll not give an example for tabooJ) and participants of the research will demand to be anonymous naturally. So in such hard situations, this method is used.

4.   Quota sampling is a useful method as well. In this method the researcher chooses participants on the basis of a pre-set standard. For example I choose people under 18 to take a survey about crimes and to find out their attitude to that issue.

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Question 1.
1.In simple Random sampling, selection of members completely depends on the chance or probability,members of the population are chosen randomly. Example: A researcher wants to conduct survey about the career goals of students at a single university. All students in the university is my population and everyone has the same opportunity.
2. In cluster sampling, subjects of the sampling are divided into different groups according to the concret criterias (age, gender, location and etc). Examle: The percentage of the usage of Apple in Europe. We can conduct survey in different countries of Europe. (location criteria)
3. In systematic sampling, subjects of the sample are chosen by regular intervals. For example, reseachers choose every 100th persons (100, 200, 300...) >out of the population of 10000.
4. In stratified sampling, the population is divided into small groups. Division is primarily decides by the researcher. These small groups represent entire population. Example: Researcher is interested in the income of graduates one year after graduation in America and he chooses 340 Caucasian, 460 are African-American, and 200 are Asian-American people and chooses members randomly.
Question 2.
1. In convenience sampling the main thing is the proximity, it does not consider whether members represent the entire population or not. Example: New company wants to establish itself in 10 cities. When it chooses cities, It selects the 10 cities based on the proximity to where they are located.
2. In judgmental sampling, researcher's knowledge is primary. Members are not randomly chosen, they are chosen on the basis of the researcher's judgment and knowledge. Example: If researcher wants to know the thoughts of the people about the importance of the laws on cybercrime. He has to choose persons who has knowledge about cybercrime or who works in this field.
3. Snowball ball research starts with only one subject and it is continued until enough subjects are available for the sample. For example, I need a research about cybercrime and I know only one person who has information about this field of law. So firstly I communicate with him, then he advices another person who can help me. And this process continues until I get enough person and information.
4. In quota sample, researcher is free to choose individuals according to his will. Individuals are chosen on the basis of the pre-set standards. Example: I start a survey about the positive sides of the Internet. I think that, young people have more information about this. I conduct my research among the youth, not old people.

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Question 1
a) probability sampling method is the method that participants are selected randomly and it is useful to get accurate answer and diminish bias. Unlike,non-probability method, the hypotesis exists and you try to verify it.
1.in simple random sampling, participants are chosen by chance,not exclusively,for example if you start query in the boulevard about the coronavirus, you can ask everybody (but if you find any people,except police)
2. İn this method you choose participants based on age,gender,location,etc (you start a query about the situation in the country after coronavirus, then you choose people, from different cities- regions are clusters)
3. Systematic sampling method, you choose people with certain intervals, (for example, from 500 people you choose every 5th people (5th,10th,15th people, etc).
4. In this method, you divide people into some groups and choose from them,but they reflect the thought of entire people. For example,when you want to know the impact of coronavirus on people, totally you use 500 people from 10 million. You choose 200 young  and 300 elder people (cause they are more become ill) and divide them such as 100 young men and 150 old men and 100 young women and 150 old women then you can select from them randomly
Question2
b) non-probability sampling method based on researcher's will,rather than random. Using this method, you can formulate the hypothesis and it is very useful when there are time and financial constraints.
1. This method is exclusively used in constraints and researcher takes the use of proximity. If you want to start a query about the level of education in the universities of Azerbaijan and you live in Elmler and have no more time, then you start to investigate the universities located there, such as Baku State University, Technical University,etc
2. In judgmental or purposive sampling, the researcher use tools for reaching its purpose. For example, you want to know about the situation at the university,then you ask the participant: "Do you study at the university?", if the answer is "No", then the people is out of questionnaire
3. In this sampling method, firstly you must find the subjects who can show the way to reach other needed sources. For example, you want to know the history of Garabakh war, you can start to interview with history teachers, then you can be directed to professors, refugees, veterans,etc.
4. In quota sampling method,you have pre-standard. For example, if you want to know about pensions you have the standard "the people above the age of 60" or about scholarships you have the standard "the university student"

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a) Probability sampling methods: it is a sampling technique in which sample from a larger population are chosen using a method based on the theory of probability. This type of sampling is entirely unbiased and hence the results are unbiased too and conclusive. It creates an accurate sample. There are 4 types of probability sampling methods:
1. Simple random: every person is chosen randomly and every person has the same chance to be a part of a sample. For example, this method is used  when you choose one student randomly from the register book.
2. Cluster sampling: in this sampling method there are certain criterias or parameters such as age, gender, location that researchers divide the population into sections according to these criterias. Example: you can use this method when you study thoughts of elderly people who are 65+ years old about the restriction to go out in quarantine mode. In this example, there is age criteria which I mentioned it above.
3. Systematic sampling: Members of this sample are chosen regularly. You choose one person  at the starting point and other persons are chosen according to certain interval. For example, when we are selected  to  subgroup of any teacher that teacher select odd or even numbers from the register book. It is systematic sampling method. This sampling method is the least time-consuming.
4. Stratified random sampling: in this sample, members are divided into smaller groups and samples are taken from each group separately. Let's say, 100 workers of a company having 1000 workers are asked questions about their wages. It is a fact that wage of cleaning worker is not the same with wage of senior consultant. For the survey to deliver precise results, the ideal manner is to divide each position into various strata.
Question 2
b) Non-probability sampling methods: this sampling is a sampling method in which the researcher chooses samples based on the subjective judgement of the researcher rather than random selection. Where there are cost and time constraints for conducting research, these methods will be much more effective than the other type. This sampling is entirely biased hence the results are biased too rendering the researcher speculative. There are 4 types non-probability sampling methods:
1. Convenience sampling: this method depend on the ease of access. It's carried out on the basis of how easy is it for a researcher to get in touch with the subjects. Researchs select  elements of the sample on the basis of proximity and not representativeness. When there are time and cost limitations in collecting feedback this method is used. For example, when you research about quality of the internet you send a questionnaire to individuals on your mobile phone's contact list, to persons you are connected to via social networking websites such as Facebook, Instagram, Twitter and to individuals whom you know in person.
2. Judgemental or purposive sampling: this method is also known as deliberate sampling. The method is formed by the discretion of the researcher purely considering the purpose of study along with the understanding of target persons. In this sampling the participants are selected only on the basis of research requirements and elements who don't fit to the purpose are kept out of the sample. For example, when you research about the impact of oil price decline on the economy you will take an  interview only from the economists whom you know.
3. Snowball sampling: this method is used in studies which need to be carried out to understand persons which are difficult to trace. It is implemented in situations where the topic is highly sensitive and not openly discussed. For example, it may be difficult to obtain a list of homeless persons in Baku. However, researchers can find a few homeless individuals and then ask them to recruit more individuals they know who are homeless to be involved in the study.
4. Quota sampling: in this method members are selected on the basis of a pre-set standard. In this case, as a sample is formed on basis of particular feature, the created sample will have the same features that are found in whole population. It is an extremely fast method of collecting samples. For example, a researcher wants to survey persons about what smartphone brand they prefer to use. He considers a sample size of 200 respondents. The researcher can divide the population by quotas:
1. Gender: 100 males and 100 females
2. Employment status : 150 employed and 50 unemployed people
3. 40 respondents each between the ages of 16-20, 21-30, 31-40, 41-50 and 51+

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Question 1) Probability sampling methods
1) Simple random sampling- Members of a sample are selected randomly. And each member has equal probability. Example:  Researcher want to conduct query about current living condition: Are you satisfied with current living conditions? And researcher can ask this question from anybody.
2) Cluster sampling- Members of a sample are selected according to some criteria such as age, gender, location etc. Example: Again the same question. But I choose only young people or I make a query among capital citizens.
3) Systematic sampling- Members of a sample are chosen at regular intervals. Every member is listed with number. Example: The same question is asked by researcher. He chooses starting point: 10. Every 10th person is selected for query.
4) Stratified random sampling- In this method, members divided into small groups and the small groups is formed in the basis of the some common charactericts. Because they reflect all people’ thoughts. After dividing into small groups, the researcher selects the members randomly. Example: The people are divided into some groups in market. And the researcher asks the same question randomly.

Question 2) Non- probability sampling methods
1) Convenience sampling- This sampling is taken from a group of people easy to contact or communicate. Example: I want to survey about instructors’ wage. I take a query from only my teacher.
2) Judgmental or purposive sampling- The members are chosen only on the basis of the researcher’s knowledge and judgment. And also it is based on purposive and subjective approach. Example: again instructors’ wage. But I take a query from other university teachers not. I compare with my teachers’ wage. Because I want to achieve raising wages in BSU.
3) Snowball sampling- This method is used when the study is difficult. It is like asking member to nominate another person with the same trait for researcher query. Example: Researcher who is lawyer wants to survey about instructors’ wage. But he doesn’t know anybody except one man. This man helps to him taking a query.
4) Quota sampling- The researcher chooses the members according to specific traits and qualities. That is, it happens on the basis of a pre-set standard. Example: The researcher wants to know about master degree students’ stipends. And he has the standard that master degree students can be the members of that query.

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Question 1.                                                       Probability sampling methods- population or members are selected at random.This reduces bias and more objective than non-probability, in this sampling method the research question or problem is known and it is researched, but in non-probability sampling research is carried out to find out the problem.                                              1)Simple random-memebers are selected by chance. For example,if I wanna know people's opinions about minimum salary in our country,I can select people randomly, there isn't any pre-standart.                                                         2)Cluster sampling - population is divided into clusters that represents entire population. For example,  I wanna find out effectiveness of law about equality of men and women,if I select only women,this is cluster method.                             3) Systematic sampling- people are selected in a certain interval and it requires certain starting point. For instance,I wanna find out people's opinions about "Corono is policy or not",if I select each 2nd one from one hundred people, this is systematic method.                                           4) Stratified random sampling- population is divided into some smaller groups that can reflect total opinion. E.g. I wanna find out the role of social media in our life,I can select twenty people who are close each other.                                    Question 2.                                                     Non-probability- population isn't selected at random. The results of this research depend on researcher's capacity. This method is subjective that's why there is a bias problem. We can get different results for the same issue in this type.      1) Convenience sampling-the main issue is "ease of access to subjects". Namely, researcher apply convenient people ,İI mean the people are selected according to proximity.For example, I wanna know students' opinions about  temporary stopping of education,I can apply my groupmates,because it's easy to conduct with them for me.                                                    2) Judgemental sampling-in this type there is target audience, if I wanna find out effect of lifetime imprisonment to their families.So other families are out of the question. (I inspired from teacher's facebook post :)).                                3) Snowball sampling- members increase by one by. I mean that if I wanna know why changes have been done to the sanction of financing of terrorism,I will apply to expert who I know,then this expert shows other professions in this field and members will increase so.                                   4) Quota sampling- there is pre-standart. For instance I wanna know what the secrets of longevity are,I will apply to the people who are above 70 or 80

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A) Probability sampling method is the selection method that gives the equal oppotunitues to members, because it based on the selection of random members of society with the help of some criterias. Its main pecularity is that there is no bias.
1.Simple random sampling is the selection of members randomly. It means the selection chance of members is equal. E.g.  In a company there is 200 employees and we have a limited time for selection ,then we choose the 25 of them randomly for our experiment.
2. In Cluster sampling the popoulation is divided into sections and cluster because of their demopraphic pecularities,such as age, location, gender and etc. E.g. i want to know the thoughts of the people on 18 about "should education be cheaper". It is cluster sampling,because there is age parametr here.
3.Systematic sampling method :before the researh it requires predefined interval. That is why it is the least time consuming method. And this method requires a starting point . E.g. I want to learn the people's opinion about Donald Trump and before the interview I think I will chose every 5th people in the street.
4.Stratified Sampling. The population is divided into the groups because of their similar characteristics that were chose by researcher. For example, I want to learn statistic about acces score of the students to unversity in my country and I choose 100 student from Baku, 80 student from Ganja, 90 student from Qebele and I take their results for my statistic.
Question 2
Non-probability sampling is based on the subjective judgement of researcher and so it contains bias.  In this method,before the research there is not any hypothesis,and this research is conducted for its creation so we can say it has a explarotary character.
1. Convenience sampling. The key word of this sampling is "ease of acces". I depends on ease of acces to subject. Its essence is conducting the research according to proximity and easy for communication.E.g. If I want to learn the opinion of the people about quarantine, because of proximity and easy to communicate I will do this research with my groupmate.
2.Judgemenatal or purposive sampling is also know deliberate sampling method .In this sampling the research members are chosen because of the research requirements.E.g: I want to research about the pepople who have a pat. In that case I will apply my inqury to them.
3.Snowball sampling method : it is mostly used for to get deeped knowledge or deeped information about a topic. With the help of this research we can reach the "hard to-reach group"(more specalized).E.g.I want to investigate the reason of emergence of dependence of social media. Firstly I will investigate among people,then with pschologysts and then specalisez ones.
4.Quota sampling .There  are pre- set standart in this sampling. The members of selections are selected on the basis of these standarts. E.g. I want to do a survey among the female teenegers between 12-18 years old.

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Probability sampling method- Every member are selected randomly and they have equal opportunity and chance for being the part of the sampling. It is an unbiased method. Because the researcher doesn’t have any thought about participants and issue in advance.1)Simple random sampling- This sampling is effective for some situations which you have to learn opinions of the total population and groups. So you choose every member randomly and each member has an equal chance being a part of sampling. For example, You want to learn opinions of the population about this question-“Were elections held transparent or non-transparent  in our country this year?”  So we can select 500 or more people by this way.2)Cluster Sampling-  People are distinguished due to their race, gender, age, location etc. there are predefined criteria. So you can learn the opinions of people who have appropriate features. Example: if you want to know that cash assistance is satisfactory or not which is only applied to low-income families, you must only explore opinions of low-income families. 3) Systematic Sampling-  There is a certain interval and people are chosen due to this interval. For example, an interval is 5. If there are 100 people, participants are selected after each 5 people. This sampling is very fast for investigation.  4) Stratified Random Sampling- We choose participants in the groups. They must be aware of the issue. For example, you want to investigate the cleanliness of buses and drivers' compliance with the rules. So you can get on the bus and choose 5 people from the front row. Non-probability sampling methods- Researcher has subjective judgement and participants are selected arbitrarily. This method is biased. Also, researcher has a certain opinion about proper issue in advance.1) Convenience Sampling- The main issue is to facilitate accession to information. For Example: if you want to arrange charity organization in the company and if you have to collect 100 consent and want to know people’s opinions about this organization, you can acquire these consents from employees of the same company.2) judgmental sampling- Participants are selected due to requirements of research. Others will be left out.  So you know in advance who can give you information. Example, If you want to search about equipment which is used in the oil industry, you only need to inquire from oil engineers 3) Snowball Sampling- Very sensitive issues can be researched by this way which they can’t discuss openly. For example, I work in the company and I want to search people who are atheist in the company. So I can’t know everybody in the company. Firstly, I will ask from my acquaintances, then they will ask others. 4)Quota Sampling- There is a pre-set standard. These standards are different from cluster sampling. You know participants and their features.  Example: Every 3rd, 5th days, there is a theft in the factory. I know that 10 previously arrested people work in the factory on each 3rd, 5th days. So firstly if I want to know who is robbery, I will begin to search thief with these 10 people.

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Probability sampling method- Every member are selected randomly and they have equal opportunity and chance for being the part of the sampling. It is an unbiased method. Because the researcher doesn’t have any thought about participants and issue in advance.1)Simple random sampling- This sampling is effective for some situations which you have to learn opinions of the total population and groups. So you choose every member randomly and each member has an equal chance being a part of sampling. For example, You want to learn opinions of the population about this question-“Were elections held transparent or non-transparent  in our country this year?”  So we can select 500 or more people by this way.2)Cluster Sampling-  People are distinguished due to their race, gender, age, location etc. there are predefined criteria. So you can learn the opinions of people who have appropriate features. Example: if you want to know that cash assistance is satisfactory or not which is only applied to low-income families, you must only explore opinions of low-income families. 3) Systematic Sampling-  There is a certain interval and people are chosen due to this interval. For example, an interval is 5. If there are 100 people, participants are selected after each 5 people. This sampling is very fast for investigation.  4) Stratified Random Sampling- We choose participants in the groups. They must be aware of the issue. For example, you want to investigate the cleanliness of buses and drivers' compliance with the rules. So you can get on the bus and choose 5 people from the front row. Non-probability sampling methods- Researcher has subjective judgement and participants are selected arbitrarily. This method is biased. Also, researcher has a certain opinion about proper issue in advance.1) Convenience Sampling- The main issue is to facilitate accession to information. For Example: if you want to arrange charity organization in the company and if you have to collect 100 consent and want to know people’s opinions about this organization, you can acquire these consents from employees of the same company.2) judgmental sampling- Participants are selected due to requirements of research. Others will be left out.  So you know in advance who can give you information. Example, If you want to search about equipment which is used in the oil industry, you only need to inquire from oil engineers 3) Snowball Sampling- Very sensitive issues can be researched by this way which they can’t discuss openly. For example, I work in the company and I want to search people who are atheist in the company. So I can’t know everybody in the company. Firstly, I will ask from my acquaintances, then they will ask others. 4)Quota Sampling- There is a pre-set standard. These standards are different from cluster sampling. You know participants and their features.  Example: Every 3rd, 5th days, there is a theft in the factory. I know that 10 previously arrested people work in the factory on each 3rd, 5th days. So firstly if I want to know who is robbery, I will begin to search thief with these 10 people.

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When a researcher wants to do a research on any topic and wants to learn thoughts of population about this topic, sampling will help him, because it is impossible to learn ideas of the whole population. Then we use sampling methods. Sampling is the process of selecting a part of the population in order to get information from them and to define thoughts of the whole population. There are two types of sampling: probability and non-probability sampling.
Question 1:
Probability sampling is the process of selecting members of the population randomly by selecting a few selection criteria. İt is based on theory of probability and reduces sample bias. İn this sampling method every member has equal chance to be a part of a sample. There are four types of probability sampling: Simple Random, Cluster, Systematic and Stratified Random Sampling
1. Simple Random Sampling is the easiest way of sampling. İn Simple Random Sampling the members of the population are selected randomly and each member has an equal chance of being selected in the sample. For example, You make giveaway (gift competition) and you select 10 winners out of 100 randomly.
2. Cluster Sampling- İn this method members are divided into clusters on the basis of some characteristics e.g age, location, gender etc. Example: We want to do a survey of town governments, then we can select several towns and do a survey instead of covering the entire state.
3. Systematic Sampling- İt is the process of selecting members of a sample at regular intervals. İt is important to select a starting point and sample size. Example: An instructor takes a list of student names and picks random starting point. Every seventh student is selected (7th, 14th, 21th etc.)
4. Stratified Random Sampling- Firstly, the population is divided into groups and then members from each group are selected randomly. Example: We survey 100 people about the influence of social media in our life by getting random samples of 50 of the young and 50 of the elder.
Question 2:
Non-probability sampling is the process of selecting members of a sample not randomly, on the basis of researcher’s selection ability. İt does not depend on the probability theory. İn non-probability sampling, we may not represent the population well in contrast to probability sampling. There are  fpur types of non-probability sampling too: Convenience, Judgmental or Purposive, Snowball and Quota sampling.
1. Convenience Sampling- This method depends on ease of access to subjects. İt is usually done on the basis of proximity and not representativeness. Example: A researcher visits the college and takes surveys from volunteer students.
2. Judgmental or Purposive Sampling- İn this method samples are selected with a purpose in mind. Example: İf a researcher wants to study computer graphics, every member cannot be the best respondent for it. Only people who are interested in computer graphics or specialists of it can be respondent for this study.
3. Snowball Sampling- İn this sampling method one subject identifies other subjects. Example: A researcher wants to study problems faced by homeless people, then he cannot know number of homeless people. İn this case, a researcher may take a survey from one homeless person and ask a person to help him find other homeless people.
4. Quota Sampling- İn Quota sampling members are selected according to some specific characteristics. İt is more fixed than Cluster sampling. Example: A researcher wants to find out what age group prefers what brand of phones. Then he/she will apply quotas on the ages 20-30, 30-40, 40-50 and 50+.

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Question 1)
a) Probability sampling methods.
1) Simple random sampling
Is based on randomly selection and each of the candidates has the same chance for to be chosen. For example you want to learn people's thoughts about  the quarantine regyme ( of course after it finished) , you can go to boulevard ask everyone you want about it.
2) Cluster sampling is also one of the probability methods in which people are divided into groups- age. gender. location. nationality and etc.For example you want to get information about Baku population's  thoughts about caronavirus, you will do research only in Baku
3) systematic sampling is based on a defined criteria and interval  For example for to look at the exam results of the school, from 300 student in the list the teacher can choose 3.6.9 and etc.
4) stratified random looks like simple random sampling but it is not totally random. In this method the choosen members totally represent whole members of the research.

Question 2.
Non- probability methods.
1) Convenience sampling is mainly based on comfort and proximity. For example, If I want to get information about some important issue and I have time and traffic limitations, I will do research among only my friends or family.
2) judgemental or purpossive sampling is based on certain purpose.  For example you want to learn the difficulty degree of the Legal Theory exam,you will ask the question to only English-9 students.  Because you have information that only they can answer this question.
3) Snowball sampling. Snowball effect: for example you want to get information about the financial situation of presidential retirees. You Will ask one of them and then he will show you others.  So you will get information more easily.
4) quota sampling is based on the main idea, thought. It depends on your idea on that issue. For example you want to learn are the people satisfied with retirements? You Will think that you can ask it to only elderly people not young people.(maybe 65+)

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Question 1
a) Probability sampling: İn this method, the samples are selected randomly and impartially. Another feature is that it gives members equal opportunities to be part of samples. Using probability sampling means that you can verify statistical techniques like confidence intervals and margins of error to validate your results.
1. Simple Random Sampling is the most convenient and simplest method of selection. As the name implies, the samples are selected randomly. This method is very useful for saving resources and time. For example, this method can be used when conducting a survey among the people about on the importance of censorship to limit hate speech on social networks.
2. In Cluster Sampling, the researcher divides the population into certain groups . These groups or sections are created based on the demographic parameters of the samples. This sampling method is convenience and ease of use. But might not work well if unit members are different from each other. For example, a researcher wants to select 1000 samples in Azerbaijan but it's not possible to list everyone. In this case he/she can choose  within the boundaries of any district.
3. In Systematic Sampling, samples are selected basis on regular intervals. It requires a random starting point and also is the least time-consuming sampling method. For example, if you want to select a random group of 1000 people from a population of 30,000 using systematic sampling. Once the list is formed, every 30th person on the list would be chosen as a sample.
4. In Stratified Random Sampling, the population is divided into certain groups, but these groups must represent the entire population. Its disadvantages: this method is tedious and time-consuming, especially when creating larger samples. For example, you want to learn about the income of Oxford graduates. And the population will be 11,000. To facilitate sample selection, you choose based on the country of birth of the graduates ( USA-1736, Germany-739, France- 251 and etc.) In this case, you are using stratified random sampling.

Question 2
b) In the of non-probability sampling, the samples are selected on the basis of the researcher's feedback, and in this case the chances of selecting the samples are not equal.
1. In convenience sampling, the samples are selected because they are accessible to the researcher. Also, it is very easy to recruit the subjects. The biggest problem with convenience sampling is dependence. This means that the samples are all connected to each other in same way. For example, if a student wants to know what people think about the importance of knowing our rights, he/she will conduct a survey among his/her fellow students to save money and time.
2. In Purposive sampling, the selection of samples varies depending on the purpose of the researcher, and these samples are selected according to the requirements of the study. For example, if you are researching indicators of the coronavirus, you can get more accurate information from medical workers instead of surveying the entire population.
3. Snowball sampling is used where potential participants are hard to find. The researcher uses another sample to find the sample. For example, the researcher wants to take an interview with families who need help. Other examples can be learned from a number of poor families.
4. Quota sampling is also based on the researcher's judgement. The population is divided into strata and samples are taken from each group to meet a quota. For example, a researcher wants to know if the working population is satisfied with their wages.  In this case, it can divide the population into age groups.  Knowing that the population aged 25-45 is more involved in the work, he can choose an example from these age groups

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Question 1.
A)İn probabilty sampling method , people are chosen at random . They have the equal opportunities in sampling .It helps reduce discrimination and bias . İt is more objective also .
1. In simple random sampling , the members are selected randomly , by chance . And each of them has equal chance , opportunity . Such as : I want to know , are people satisfied with the modern lifestyle? And I can ask this to anyone I meet .
2. İn cluster sampling , people or population are divided into clusters or sections . And main parameters are age , gender and location.
Example :  Again  I want to know are people satisfied with the modern lifestyle. But I only choose people between the ages of 17-35.
3.İn systematic sampling ,  people are selected in a  certain  interval and it requires starting point .and it requires starting point .Example : I am interviewing the population and I want to ask every 5th person I come across .
4. İn stratified random sampling , population is divided into some small groups .But it should cover everyone's mind.  Example : the people are divided some groups in  school and and they are asked a random question .
Question 2.
B)İn non- probability sampling method , people aren't chosen at random . This method is subjective and allows for more in-depth research . But we can get different results in the sama issue . This method is used to create a hypothesis .
1. In convenience sampling , the main element is 'ease of access to subjects '. Proximity andconvenience are the key factor for the reseacher . Such as : if I want to find out if students are satisfied with this course system . First , I'll ask from my groupmates . Because it is easy for me .
2.In judgmental or purposive sampling , the researcher knows with whom to conduct the research , have target audience . We can say it is also deliberate sampling . Such as : I want to know BSU's teachers'  style of teaching . And this university's teachers are enough for me .
3.In snowball sampling , we use it when the study is difficult .Also we can use it for the topic , which is not openly discussed . S.a : I want to know , how is the oil sector inAzerbaijan . But I know only 1 people  in this sector and   I'll find more people in the research process .
4.In quota sampling ,selection of members are  basis of a pre-standard . The researcher chooses  the members according specific qualities . Example : I want to know if the elderly are satisfied with the pension . It is better to ask pensioners.

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1. Question
Probability sampling method- samples chosen on the basis of some criteria.
Characteristics:
1. It covers entire population, so every people have chance to participate.
2. It doesn't lead bias
3. Every person is chosen randomly
If there is no time or budget constraints, to use this methods is more effective.
1. Simple random sampling- Each target has equal opportunity to become the sample of research. It is fulfilled randomly.
E.g If researcher is eager for learning thoughts and opinions of every member of society about social media and its effect, simple random sampling is appropriate for this.
2. Cluster sampling - People are divided into groups or clusters in order to represent Entire population. This can be based on location, age, gender etc. For example, While taking interview of local people who live near Hazi Aslanov station about constructing process which continues about 10 years, we can apply cluster sampling.
3. Systematic sampling- There is pre-defined intervals for choosing each target. This method create opportunity for saving time. e.g If researcher has a limited time, he/she can use it.
Choosing each 3rd person crossing in front of him he can conduct interview. Topic can be different.
4. Stratified sampling is a method where population can be divided into groups that don't overlap, but can indicate opinions of the whole.
E.g If researcher wants to get information about transparency of election, first in A, B, C region takes interview of 10% of every local population and then exact idea will be formulated.
2. Question
Non-probability sampling methods are used in conditions when researcher has constraint or limitations about budget,time etc. In contrast to probability sampling methods, before starting research,you have pre-determined, accurate idea.
1. Convenience sampling - As it seem, convenience or comfort of research is provided in this method. It takes account of proximity.
For example, the study of Psychology and psychological assistance at schools can be surveyed and children may be involved to the research as samples.
2. Judgemental or Purposive sampling- Samples are chosen purposefully by research conductor. Example: While preparing article about signing contract about marriage, you can appeal a lawyer who deals with Family law.
Question: What does it mean? Is It necessary in marriage?
So, this can be repeated as you get what you want.
3. Snowball sampling - When conducting research can't be traced and there is time limitations, the best method is snowball sampling. Example: Is it neccessary to pay "unemployment wage" unemployed persons? Or will it lead to diminishing of efficiency of work and employers begin to avoid from responsibility? It is major issue nowadays. Me as a researcher ask this question,chosen target will continue and assign this work another .
4. Quota sampling - It looks like Cluster sampling, but there is a pre-forming idea beforehand.Also,it can be called pre-set standards.However, to be aware of thoughts of person and purposefully questionnaire can lead bias.
Example : Researcher knows where majority of jailed persons who were prisoned without any reason are. His work is about uncertain and inaccurate and even ridiculous justification and judgement in trials. He purposefully get an interview of prisoners about reopening documents that belongs to unsolved or partially solved matters or issues.

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Probability sampling is the method which uses random sampling techniques to create sample. This group of sampling methods give all the members of a population equal chances of being selected. This method helps us to reduce sample bias. This method covers diverse population.
1) Simple random sampling is a sampling that helps us to save time and resources.All members are selected by chance.For example: if researcher wants to know people' opinions about sales of drinks , we will use simple random sampling and we must select people randomly.There isn't any pecularities in this sampling
2) Cluster sampling is a sampling that the researcher divided population into cluster that represent population. For example: If researcher wants to know the opinion of the people of Baku on any topic, researcher will use this sampling.There are some pecularities for instance: location, gender and age
3) Systematic sampling is a sampling that researcher researchs samples which are chosen at regular intervals of a population.For example: if researcher wants to know the opinion of one in every thousands people about violence against women, researcher will use systematic sampling. This sampling method is the least time consumuning
4) Stratified random sampling is the sampling that members are divided into small groups that must reflect total opinion.For example: if i want to know opinion of people within 1 km about role of law in our life, i will use stratified random samoling
Question 2
Non probability sampling method is the method that population isn't selected at any random.Selection depends upon situtation in this method. Researcher selects samples based on the subjective judgment of the researcher rather that random selection
1) Convenience sampling is accidental sampling is accidental sampling which is a type of non probabilitu sampling which involves the sample being drawn from that part of the population which is close to hand. For example: If i less time and i must learn people' opinion on any topic, i refer to close people
2) Judgemental or Purposive sampling is the sample which known judgemental, selective or subjective sampling. This sampling reflects a group of samplings techniques that rely on the judgement of the researcher. For example: If i research crime law and i know experts of crime law and i will contact them
3) Snowball sampling used in studies which need to be carried out understand subjects which are difficult to trace. This sampling isn't determined beforehand. If i research crime law and i know one expert, and i contact him or her and he or she says me other experts, this sampling will be Snowball sampling
4) Quota sampling is selection of members in this sampling technique happens on basis of a pre-set standart. This sampling have same pecularities with cluster sampling, but there are different, because we don't know members' opininons in cluster sampling, but we know member's opinion in Quota sampling. For example: researcher can choose males under 50.

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First question: Probability Sampling method selects random  members of a population by setting a few selection criteria, cover all population and reduce bias. There are 4 types of it: Simple Random, Cluster, Systematic, Stratified Random.
1.Simple Random Sampling- In this method everybody has equal chance-We want to research the level of lawful behavior of population(socially active behavior, law-abiding, conformist, marginal, habitual), it is available to selects members of population randomly without any criteria.
2.Cluster Sampling- This method is also randomly, but there are some criteria (age, gender,location) We are interested in women’s thoughts about gender equality in our country-Cluster Sampling.
3. Stratified Random Sampling- Population is devided to smaller groups and this group can represent all populatin-Level of welfare of population is researched and some people from different groups of population (poor, rich, highly-paid, low paid) are addressed and these people can represent  all population.
4.Systematic Sampling-Members of sample are chosen at regular intervals of population, this method predicts waste of time.-We study people’s sensitivity to nature conservation and we don’t have enough time and decide to address to every fifth person who we meet(5th, 10th, 15th).
Second question: Non-Probability Sampling. It is necessary to address specialists about some subjects and for this, non-probability sampling method is available. There are 4 types of it: Convenience, Snowball, Quota, Judgmental or Purposive Sampling.
1.Judgmental or Purposive Sampling- known as delibarate sample, researches know who to contact, who is helpful for this topic- I wanted to do research on China’s international legal responsibility for the pandemic,  someone who wrote about it and he is the only person I know who has researched it, I appealed to him.
2.But then he informed me of others doing research on this subject and they also informed about others.- Researcher address individuals to inform about others, it is used about more sensitive topic, researcher need help of member of sample to find other individual.- Snowball Sampling.
3.Convenience Sampling- Researcher address individuals who are available in terms of place, it is a easy method- I research on Postmortal law in Azerbaijan and I appeal to my teachers.
4. Quota Sampling- In this method there are some pre-standard, but this can cause some bias sometimes- University wants to research the levels of welfare of students and it only decides to interview students who live outside their families, as they may have more  problems.

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Sampling methods
Question 1:
a) Probability sampling methods :
Probability sampling methods use random selection to create a sample. İn these methods every member of the population has the same chances of being selected.
1. Simple Random Sampling- Each member is chosen randomly and by chance. And each member has the same probability of being chosen. This method is an unbiased method. For example; the school has 6000 pupils. And these pupils are our population. And researcher wants to make survey about bullying. And members of this survey are chosen randomly. Each member has the same chance.
2. Cluster Random Sampling- İn this method the researcher divide the population into groups based on a particular characteristic (gender, level of education, socio-economic status, age etc.). For example; a survey about natural disasters might divide a population into clusters according to region. And then choose a random cluster or clusters.
3. Systematic Random Sampling- The members are chosen at regular intervals of a population. For example; there are 100 people in cinema hall. And the researcher make a survey about the idea of movie with 10 people. And every 10th person is the member.
4. Stratified Random Sampling- İn this method the population are divided into small groups. And then the researcher draw a sample from each group seperately. This method is proportional, and gives statistical outcomes. For example; a researcher makes survey about religion among different ages groups. And then collect their feedbacks.
Question 2:
b) Non-probability sampling methods:
This method doesn't give all the individuals in the population equal chances of being chosen.
1. Convenience Sampling- İn this method members are chosen because of their convenient accessibility and proximity to the researcher. For example; a researcher makes survey in class. And he chooses the first 5 names from the list.
2. Judgmental Sampling- İn this method , a researcher thinks that some individuals are more fit for the survey than the others. And this method is knowns as Purposive Sampling. For example; a researcher makes a survey about religious beliefs. And a researcher chooses one tribe that has highly religious beliefs. And he will make a survey.
3. Snowball Sampling- The researcher asks the initial individual to identfy another individual. This method is applied when the topic is not openly discussed. For example; a survey about homeless people.
4. Quota Sampling- The researcher chooses members according to specific qualities. For example; a researcher can choose female members between the age of 45 and 60.

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Question 1.
1. In this selection form, the members of the selection are chosen by chance and do not have any bias. I consider it fair and objective.
2. This method takes into account the defining features of those to be selected. Age, gender, place of residence, etc. And this means that the elect are in a certain group.
3. This selection method requires you to select a starting point for the sample. This means that the choices are made in a system that depends on the beginning. Changing the starting point also changes the outcome of the selection. Doubts about justice arise.
4. In this method, the selection is made from groups. That is, the population is divided into groups according to certain criteria. And those who will be selected are selected from these divided groups. This method can be understood as a choice from the chosen ones. (This is my opinion)
Question 2.
1. This choice depends on the voter. Let's say I am a voter, I will fill out a questionnaire and I have very little time. Considering that I live in Icheri Sheher, I make my choice from the students of the University of Economics for the most comfortable choice. This will also reduce costs.
2. Judgmental or Purposive Sampling: In this type of selection, the voter considers whether the people to be selected meet his or her requirements. For example, when hiring a law firm, lawyers are hired as a selection group.
(I mean vacancies for lawyers)
3. This option is similar to the Judgmental or Purposive Sampling method. But it is different. Thus, the discussion of this form of choice is suitable for risky or sensitive issues. For example, let's say I want to learn the religious beliefs of my groupmates. But since religion is a sensitive issue, it is not possible to ask everyone in the same way. That's why I start with my close friends. Then they ask others, and others ask others.
4. The quota selection method is similar to the Cluster selection. But there is a pre-standard on it. For example, as you know, there is a coronavirus problem. And here the risk group is defined. It may not be a selection, but it looks like.
Okay, let me say more clear than : Let's say I'm a historian, and I need a lot of (early) memories and so on. About 70 years ago. In that case, I would not apply to someone 45 or 60 years old. Ie, I will appeal to people above 70 years old.

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Question 1
a) Probability sample method is a method that people are randomly selected. It is a fair method, because every person has the equal chance of being selected. Researcher doesn't have opinion about the research beforehand.
1. Simple random sampling - this method saves time and every member of population is randomly selected. E.g a researcher wants to know if people are satisfied with the education system in our country, he can use simple random sampling.
2. Cluster sampling - includes criteria such as age, gender, location and etc. Population can be divided into groups based on these criteria. Example, a researcher investigates uneducated people among women and will contact only with women.
3. Systematic sampling - in this method people are selected in a systematic way, at regular intervals. For example, there is a list of 300 teachers of school and every third teacher will answer the question about their salary.
4. Stratified random sampling - people are selected randomly by being divided into groups, but their ideas don't overlap, they own different ideas and represent the whole population. Example, researcher wants to know about adherence to the traffic rules in Azerbaijan. He chooses people from different regions or cities of the country.

Question 2
b) Non-probability sample is a method that people are not randomly selected, selection of them is predefined by researcher. Unlike probability sample method, in this method researcher has opinion about the research beforehand, knows which non-probability samplings he will use.
1. Convenience sampling - this sampling helps if researcher doesn't have enough time to conduct a survey. It is based on the proximity, even it doesn't reflect the ideas of whole population. For example, researcher wants to investigate the percentage of domestic violence in the country but he doesn't have enough time and investigates only in areas close to him.
2. Judgmental or Purposive sampling - there is a target audience in this type, researcher knows who to interview. E.g he wants to investigate how X disease patients fought with this disease. And he knows all of the patients that he needs.
3. Snowball sampling - it is used when researcher doesn't know all of the members that he needs in his investigation. It starts with one or few subjects that researcher knows and continues until all the other subjects are found with the help of the subjects that he already knows. For example, I mentioned X disease above, but here the difference is researcher doesn't know all of the patients and the ones that he knows help him to find the others.
4. Quota sampling - there are pre-set standards of choosing the members. Selection of people is left to researcher, he has his own ideas about them. E.g researcher wants to investigate moral values, better lifestyle or something about life. And we consider that the elderly people have more outlook than the young, so we can address to them when we need advice or wise ideas.

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I like your examples for example which about judmental sampling. But as Nezrin said you can give more exactly some patterns. As a result quality of context is good.

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Question1
a)a probability sampling method is any method that determines some form of random selection.Tis mechanism is suitable .Because this method simplifies the work to be done . There are some main types of probability sampling methods They are cluster sampling, systemactic random sampling , stratified sampling and simple random.
1)simple random sampling is easier than others .Because when we used simple random sampling we will choose the participants accidentally.For example in Baku, N.Narimanov we want to know people's opinion on the artificial rise in prices .Then we can ask everybody this question.
2)  cluster sampling is limitated form. Because when we use cluster sampling we can't ask any question from everybody. There are some crititeries in cluster sampling, for example age , location, gender and so on. For example we want to confuct survey among young people about giving seat to the elderly on the bus and metro. Then we can conduct survey only with young people
3) in systematic sampling method we can choose the participants at interval. Fpr example among 300 person ,we want to conduct survey at 1-100 interval
4) in stratified random sampling the population is divided into small groups and we choose the participants from the groups. For example we want to know people's opinion to the criminal world. Then we choose from the group ,for example 100 man , 50 woman, 200 young people ,120 elder people among 10000000 people .
Question2
b) Non-probability sampling doesn't based on random selection unlike probability sampling
1) if we have little time, we will use convenience sampling .This method is easy. For example I want to conduct survey about students'scholarships. And I study in BSU. Then I can ask from BSU's students
2)in judgmental sampling, the participants aren't chosen accidentaly.İat before  we defined the members who are professional own work. For example I want to know in country crime rates vary from year to year.And I know who to ask this question to
3)in snowball sampling the members are not known,exactly. it is more difficult than others. For example again I want to know in country crime rates vary from year to year and I don't know wha ask this question to exceps one or two person. Before I conduct survey with them and they recommend to me others for conducting survey about it, so the number of member increases one by one
4)Quota sampling method based on pre-standarts .The members are chosen according to qualities. For example I want to conduct survey about criminal world that's why I must speak the persons who are known as legal robber .

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Question: 1
1. Helps save time.  Random selection is applied.  Each member has equal probabilities.
For example:
The quality of school education is being checked.  Several of all students at the school are randomly selected.
2. In this example, members are divided into groups.  These groups are based on certain characteristics (age, location, gender).
For example:
The population of the European Union is being surveyed about this organization.  Initially, two states are chosen at random, and the entire population of those states is included.
3. Requires the selection of a starting point for the sample and is a sample size that can be repeated on a regular basis. This type of sampling method has a predetermined interval, and therefore this sampling method takes the least amount of time.
For example: each 10th person from 100 people are included in the selection.
4. The population is divided into groups in the prescribed manner.
For example:
In the United States, 5 representatives from 50 states are elected from each state.

Question: 2
1. The survey is conducted in a more convenient way.  Those who can communicate more easily are selected from the population.
For example:
An employee of the company is conducting an investigation into salaries.  He will first ask his colleagues for help.
2. The researcher selects the population taking into account the wishes of the sample.  Participants are selected only according to the research requirements.
For example:
In a study which needed to know what it takes to graduate summa cum laude in university. The only people who can give the researcher first hand advice are the individuals who graduated summa cum laude.
3. This sampling method is used in situations where the subject is not clear and is done.
For example:
A detective investigates a crime of unknown cause.  But he does not know anything about it. Therefore, he is following the event step by step.
4. In this method, the researcher knows in advance which group to conduct the survey.  He is free to choose.
For example:
The researcher conducts a simple research of the situation in the military.  He can use soldiers returning from military service.

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Question 1.

a) Probability sampling methods allow the researcher to select subjects of research randomly by setting a few criteria. In this kind of method, every member has the same chance of being selected. This method reduces sample bias; covers the whole population, thus creates diversity; creates an accurate sample. In the end, the research proves or disproves a previously determined hypothesis.

1. Simple random sampling is the most simple form of probability sampling. In this kind of research, the researcher chooses their subjects randomly from the whole population. Hence every single member of the population has exactly the same probability of being chosen. This method saves time and resources and is trustworthy. For example, if someone wants to learn attitudes of people for the current government, they will use this sampling method in order to cover the whole population.

2. In cluster sampling, the researcher divides people into clusters by previously determined criteria. The criteria can be age, gender, and etc. This method gives more detailed information about the research. For example, one can conduct this method if they want to determine whether the young are pro-government or the old.

3. In systematic sampling, the researcher chooses an interval beforehand and conducts the research by regular intervals. As the interval is predefined, this method is the least time-consuming. For example, the researcher can ask the above-mentioned question to every 5th person of the population.

4. Stratified random sampling is the last method of probability sampling and it likes simple random sampling. But instead of asking a whole population randomly, the researcher divides them into a few groups. These groups don’t based on any criteria. This sampling method simplify the researchers duty. Again, for example, we can use the ”government” question. The researches would divide the population; ask them separately, and in the end, they will collect all data in one.

Question 2.

b) Non-probability sampling methods are methods that don’t cover the whole population but limited. As opposed to probability sampling methods, there’s no previously determined hypothesis. As a contrast, these methods are used for creating a hypothesis. And these researches are not conclusive, but exploratory. Lastly, these methods can be used when there are budget and resource constraints.

1. Convenience sampling is a sampling method based on not representativity but proximity. The researcher conducts the research among the people who are easy to get in touch. The researcher has little control over choosing subjects. It is generally used when there are serious time and budget limitations. For example, conducting a survey about capital punishment among law students will not represent the whole population’s idea.

2. In judgemental sampling or also known as purposive sampling, the researcher chooses the subjects on purpose. This kind of research is good for exploratory and creating hypothesis. For example, one can conduct research about life sentence among not the whole ”law world” but only among judges.

3. Snowball sampling is used when subjects are too difficult to get in touch and/or the topic is not suitable to openly discussing. In this sampling, the researcher would get the information in a long way. For example, a dialogue between snowball sampler and the subject would be like that: ”would you be interested in the socialist revolution, comrade?” ”Yes, comrade, of course, I would” ”Great! Do you know any other comrades who share our cause?” “Of course, I know and they know a few people too. Let’s go, meet you with them”

4. In quota sampling the subjects are chosen on the basis of pre-set standart. Thid method is quick and helps to collect data from specific group. For example, if one would like to know what is the thoughts of 50+ aged people on global warming, this method would be the one the researcher use.

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Probability Sampling uses random sampling techniques to create a sample. In this method researcher considers some selection criteria. That's why every member of various sample have equal opportunity. As well as this method is unbiased and hence that's result conclusive and unbiased too. Probability Sampling Methods have 4 types of technique:

1. Simple Random Sampling: in this technique every member chosen by chance, randomly. This way is trustworthy and helps saving time and resources. For instance, we want to determine people's thoughts about Garabag issue we approach someone randomly. Because in this situation their gender age or location doesn't matter.

2. Cluster Sampling: Called like this because researchers divide population into clusters according to some features like age, gender location etc. It's easy for getting result from feedbacks for example, our research is about violence against women and men's approach to this issue that's why we ask only men.

3. Systematic Sampling: This technique requires to select starting point for samples and repeated it at regulary intervals. If you have little time this method is useful for example, when we choose students for answer questions we can select them with systematic sampling such as we can choose only single digits.

4. Stratified Random Sampling: in this method population is divided into smaller groups, these groups don't overlap but represent whole population together. Researchers choose sample from each predefined group for instance, we want search happiness level in Azerbaijan then we divide population for 4 group called east, west, south and north according to their regions. And select sample from each groups.

Non-Probability Sampling isn't randomly it based on researchers' sample selection capabilities or will that's why this method is biased and hence resualt of research is speculative. Also it is exploratory in nature. In contrast to the probability sampling its hypothesis derived after conducting research.
It has also 4 techniques:

1. Convenience Sampling: if researcher has limited time and cost this method is more useful. It depend on easy access to subjects. But it's based on proximity and not representativeness. I can give example that traditional "person in the streets" interviews. We saw frequently in television programs jurnalist ( or research ) close to some group int he street and ask one by one all member of this group this is easy way for saving time but as i said it's not representativeness.

2.Judgmental and Purposive Sampling: formed by discretion of researchers such as researcher doesn't choose samples or respondents randomly he or she choose predefined samples. For example: I research treatment of epidemic diseases and I need deeply information not other's ideas and I know who are experts on this issue and I only work with them.

3. Snowball Sampling: This is like purposive sampling but there are some differences. Such as researchers know one or two experts and begin research with them then they advise other one and the others direct different expert and research samples are enlarged like snowball) For example, I am interested in
cybersecurity strategy and I only recognize Elvin Balajanov for get exact information and he advises others.

4. Quota Sampling: in this method samples are choosen according to some criterias (age or gender) like cluster but their difference is that quota sampling happens on basis of pre-set standart. It's an extremely quick method but it's biased. For instance, researcher thinks that fur wearing people don't care of any animal and want know their approach to violence against animal.
‌Ps: During research we can use more than one technique and which one is more suitable is depend on research question.

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Question 1:
a) Probability sampling methods:
1. In simple random sampling members of population are chosen by incidentally. Every individual has the same chance, so it means that this method reduces bias more than other methods. Example: I want to research society’s thoughts about Nagorno-Karabakh conflict and peace process, I go to somewhere(for example, a park) and choose anyone randomly.
2. Cluster sampling: The population is divided into groups (clusters). The members of group are also selected randomly, but there are several criteria; age, gender etc.
Example: In the same situation, I want to know only men’s opinions and select men for research.
3. Systematic sampling: In this method members of group are listed and selected with a defined technique, for example every 20th person of group is selected. But there can be bias, because everyone doesn’t have the same chance for choosing.
4. Stratified random sampling: It is similar with cluster sampling, because in both of them population is divided into some groups, subgroups. But unlike it, in this method individuals are chosen proportionally, because they represent all members of group. In this sense, I want to emphasize that, it demands more attention in order to ensure that the chosen people can represent others.

Question 2:
b) Non-probability sampling methods:
1. Convenience sampling: It is the easiest method among all sampling methods. But the consequence of the research can be no accurate and can’t show the real situation. The main point of this method is geographic proximity and easy access. For example, I don’t have enough sources and can’t go another place, so I choose my neighbours for my research.
2. Judgmental or purposive sampling: It is used for gaining more detailed information. So the researcher selects someone who can be answer his/her questions. For example, I want to learn about some topics of business law, and I choose experts of this field.
3. Snowball sampling: In this method, the researcher finds initial person who can be relevant for survey. Then with information received from that person, the researcher will make other contacts and will extend the scope of research.
4. Quota sampling: There is beforehand thought about the selected people and the researcher chooses people with his/her own judgment that they are more appropriate. When compared to other methods, there can be more bias. For instance, the interviewer selects the people who have the same opinions for showing the result as he/she wants.

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Question 1.
a) Probability sampling methods- in probability sampling methods members are selected randomly, population have equal probabilities of being chosen. That's why this reduces non-objectivity and bias. Probability sampling methods are more accurate and rigorous than non-probability sampling methods.
1) simple random sampling- members of this sampling are selected randomly by chance and all members have equal opportunities. For example: let's assume that we are doing some research with university students about the quality of education at universities. We can select any university student.
2) cluster sampling- this method divide population into clusters according to age, gender, geographic boundaries. For example: let's say that we have to do a survey of regions that to what extent the quarantine is observed by regions. If we do a simple random sample we will have to cover the entire state geographically, instead we decide to a cluster sampling of five region
3) systematic sampling- members of sampling are selected between certain intervals. For example: we have a population that only has 100 people in it and we want to take a sample of 20. We can select every 5th person of 100.
4) stratified sampling- this method dividing population into groups and then taking a simple random in each group. For example: we are doing research with the population of Caucasus about their attitude toward Russia. The population can be divided into three groups: Azerbaijanis, Armenians, Georgians. And then we can take a sampling in each group.

Question 2.
b) Non-probability sampling methods-in contrast to probability sampling methods, non-probability sampling doesn't involve random selection. These methods depend on researcher and not everyone has equal chance to participate.
1) convenience sampling- this method depend on proximity. Researcher choose this sampling just because they are easy to recruit. This sampling is used when there is time and other limitations. For example: we are doing research about teachers. We can send the survey to students belonging to a particular school or university.
2) judgemental sampling- this sampling reflect a group of sampling techniques that rely on the judgement of researcher. For example: in a study wherein a researcher wants to know what it takes to graduate summa cum laude in collage. The only people are selected wo graduated summa cum laude.
3) snowball sampling- this method is approbriate when the population you are interested in is hidden or hard to reach. For example: we are doing research with drug addicts. Such population can be hidden because of their illegal behaviour.
4) quota sampling- in this method participants are chosen by researcher non-randomly according to certain qualities. For example: we want to conduct a survey with juvenile offenders. We need to talk to people who have committed crimes under age of 18.

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a) Probability sampling methods
1. In a Simple Random sampling every member of the population has an equal chance of being selected. This sampling frame should include the whole population. For example: A researcher wants to know if people are satisfied with films shot in country , he/she can ask anybody.
2. In cluster sampling, members of a sample are divided into groups according to some criteria such as age, gender, location etc. For example : If we ask the same query only to women or men , we should use a cluster sampling.
3. In a Systematic sampling, every member of the population is listed with a number and individuals are chosen at regular intervals. For example: If you wanted a sample size of 300 from a population of 3000, select every 3000/300 = 10th member of the sampling frame.
4. In Stratified Random sampling, population is divided into smaller groups. These small groups represent the entire population. For example: suppose we conduct a national survey. We might divide the population into groups, based on geography - north, east, south, and west. Then, within each group, we might randomly select survey respondents.

b) Non-probability sampling methods
1. A convenience sample simply includes the individuals who happen to be most accessible to the researcher. This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results. For example: We want to know what students think about humanism and we only ask our class, because there is not enough time, but this is not the general result.
2. In Judgmental or porposive, researchers carefully  choose each individual to be a part of the sample. The researcher’s knowledge is primary in this sampling process as the members of the sample are not randomly chosen. For example: If we want to know the advantages and disadvantages of online lessons on the coronavirus, we need to ask only teachers who teache online.
3. If the population is hard to access, snowball can be used to recruit participants via other participants. The number of people you have access to "snowball" as you get in contact with more people. For example: A researcher is studying environmental engineers but can only find five. She asks these engineers if they know any more. They give her several further referrals, who in turn provide additional contacts. In this way, she manages to contact sufficient engineers.
4. This type of sampling depends of some pre-set standard. It selects the representative sample from the population. Proportion of characteristics/trait in sample should be the same as population. For example: If researcher wants to survey teenage boys' attitudes toward parental pressure, he/she should interview boys between the ages of 12 and 18.

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Sampling is the process of selecting a representative group from the population under study.
Samples are parts of a population. For example, you might have a list of information on 100 (sample) out of 10000 (the population). You can use that list to make some assumptions about the entire population's behavior.
Question 1 :
a) Probability sampling methods- In probability sampling, the goal is for the entire population to have a chance to be elected. This is similar to the lottery.
If the population is everyone who has bought a lottery ticket, then each person has an equal chance of winning the lottery.
The merits are that your sample should represent  the target population and eliminate sampling bias, but the demerit is that it is very difficult achieve (i.e. time, effort, money and etc).
1) Simple Random Sampling- Select items completely randomly, so that each element  has the some probability of being chosen as any other elements. For example, lottery method. One big advantage of this technique is that it is the most direct method of probability sampling.
2) Cluster Sampling- In cluster sampling, the population is divided into groups according to various characteristics and randomly selected from each group. For example, let's examine the thought of women about wearing hijab. We can learn this by conducting surveys in different regions of Azerbaijan.
Merits-1. very helplful in large scale surveys
2. saves time and money.
Demerit- Division of population into clusters is quite and difficult task.
3) Systematic Sampling- In this type of sampling, the first individual is selected randomly and others are selected using a fixed "sampling interval". For example, to present a gift to every 100th customer in the store.
The advantage to this method is that it is very simple method and generally results are satisfactory and re-checking can be done quickly.
4) Stratified Random Sampling- In this sampling, we divide the population into groups based on different traits like gender, category etc. And then we select the sample from these groups. For example, we are asking for the adoption of any law. In this case, our country can be divided into northern, southern, eastern and western regions, and people can make random choices.
This method is time consuming and difficult and this method cannot be used without information on split groups.
Question 2:
b) Non-probability sampling is one in which all the items of the population do not have equal chances of being selected. Researcher selects samples on the basis of  convenience or his judgment ratjer than on the basis of probability.
1) Convenience Sampling- In this method, data is chosen on convenience. For example, we observe the observance of hygiene rules in the markets. To make these observations, we turn to the nearest markets.
Merit- The economy of time, money and efforts.
Demerit- Sample items may not truly represent the population results  obtained are often less reliable.
2) Judgmental Sampljng- Under this method, the choice of sample items depends exclusively on the judgment of the researcher. On the basis of his own choice, he tries to select the best representative of the whole population. For example, if a teacher has to select students for a competition, he or she will not do so at random.
Advantage- Where some characteristics are to be observed in detail.
Disadvantages- 1. Not based on probability, it doesn't guarantee accuracy.
2. Selection of items may be affected by personal bias or prejudice.
3) Snowball Sampling- In this type of sampling, existing people are asked to nominate further people known to them so that sample increases in size like a snowball. For example, the researcher wants to learn more about the Karabakh war, and there is one person he knows. Through this person, the researcher finds several other witnesses.
The disadvantage of this method is that the applicants recommend others with whom they have common features.
4) Quota Sampling- In this sampling, we choose items based on predetermined characteristics of the population. For example, if we want to learn about the treatment of a disease, we must get information from doctors about it.
Merit- Each part of the population gets representation.
Demerits- 1. This method is subject to personal bias.
2. Proves useful only if interviewers are properly trained.

There are, of course, errors in these studies. The most effective way to eliminate these errors is to increase the number of samples. However, sometimes an excessive number of samples can be time consuming and costly. Therefore, first of all, it is necessary to use a well-organized design and tools to minimize errors.

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Sampling methods

Question 1:

a) Probability sampling methods- Probability sampling is a sampling that population are chosen using a method based on theory of probability. These sampling methods are methods that we select participants randomly. This selection gives every member of population equal opportunities to participate in sampling. These methods reduce bias. Conducting this sampling takes a longer time. When starting this sampling, we have a hypothesis and after sampling, we prove the hypothesis.

1. Simple Random Sampling- In this sampling we can choose every single member of a population randomly. And each person has the same probability to be a part of a sample. For example, If I want to know “People are satisfied with their living conditions or not” and for this, I can ask this question everybody.

2. Cluster Sampling- İn this sampling population is divided into sections on the basis of defining demographic parameters such as location, age, gender etc. For example, If I want to know people’s opinions about domestic violence and for this query, If I choose women, this will be cluster sampling.

3. Systematic Sampling- In this sampling members are chosen at regular intervals. For example, If I want to know people’s opinions about “Nagorno- Karabakh conflict” and there is a list of 1000 people. If I choose every fifth people, this will be a systematic sampling.

4. Stratified Sampling- In this the population can be divided into smaller groups, but these groups represent the entire population. For example, If I want to know students’ opinions about the faculty of law and If I choose our group( English-9), this will be stratified sampling.

Question 2:

b) Non-probability sampling methods- Non-probability sampling is a sampling method in which researcher selects samples based on the subjective judgement of the researcher. Unlike probability sampling methods, the non-probability sampling method is used to create a hypothesis and the hypothesis is derived after conducting research. In this method the research is exploratory and the participants are selected arbitrarily. This type of sampling is biased and conducting this sampling is quick.

1. Convenience Sampling- This sampling is depend on the ease of access to subjects. For example, If I want to know the young’s opinions about horror movies and If I choose my friends, this will be convenience sampling. Because it is convenient for me conducting this survey among my friends.

2. Judgemental or Purposive Sampling- In this sampling, the participants are selected on the basis of research requirements. For example, If I want to know students’ opinions of Baku State University about their scholarships, I will conduct this survey among students of BSU.

3. Snowball Sampling- This method is used when the topic is highly sensitive and it is difficult to find out samples. For example, If I want to get information about someone’s murder, but it is difficult to conduct a investigation. I can find a man who has information about victim, he know his relatives and so on. I can find others by the help of a man.

4. Quota Sampling- This sampling is conducted on basis of a pre-set standart. For example, If I want to know about the elderly’s health conditions, and If I conduct this survey among females, above 65, this will be quota sampling.