# data[].attributes.body
Initially looking at this module looked like a pain to complete, and I did have trouble interpreting the different projects to their respective data selections. However, your examples provided on canvas, based on real depictions of data from the world proved to be incredibly useful for me. All of your hard work continues to excel students in the proper direction and I appreaciate you for that! Cheers!

# data[].attributes.body
My muddiest points were undestanding the excell worksheets. Mainly because my brain just gets overhwelmed by a lot of numbers and how long they can be in stats. But I liked that the class was very realistic and used real world and personal scenerios and data.

# data[].attributes.body
My muddiest points were truly understanding the formulas and the Google charts and apply it to excel. If it were not for Professor Halsey’s video and breaking down the step by steps, I would have been lost.

# data[].attributes.body
My muddiest point is just recognizing and connecting the terminology to the exact referred material. Along with familiarizing myself with some of the practice towards the measurement and the application of the data.

# data[].attributes.body
My muddiest points were the projects, it was helpful that we had the excel spreadsheets set up for us already to find the statistics easier but I would not know how to find some of the answers on my own without it being preset.

# data[].attributes.body
While I learned a lot throughout this class there are some parts that seemed unclear. One of the most confusing and muddiest parts of this class was trying to understand confidence intervals and the significance of them.

# data[].attributes.body
The muddiest part for me was the module projects

at the end of each module.. Those were the ones that had tables

and data and more numbers and things. I struggled with those.

# data[].attributes.body
My muddiest points were probably finding good resources for the data I needed for my projects. Thinking of ideas for projects was also challenging. I also had trouble completing projects without falling behind in class, as although we could turn in things late, we would have already moved onto a new topic in class- which led to even more confusion for me. At times, working with google sheets was also tough and took a lot more effort than I think it needed to. But, the way your explained the math always made sense, as well as what you expected from us for our projects.

- Mara

# data[].attributes.body
I think one of my muddiest points would be trying to understand the difference between the GOF test and the Chi-Square test. Another one of my muddiest points would be trying to catch up from the previous classes because I got sick.

# data[].attributes.body
So Math and I are like oil and water; we do not mix. This class has been a pleasant re-introduction to Math as I no longer feel like running the other way when I hear that M word. At first I was overwhelmed by the symbols and material but I feel like I have gotten a good grasp on hypothesis testing as well as confidence levels. I feel good to have made it to the end and want to thank you all for embarking on this journey together

# data[].attributes.body
I believe that my muddiest point of doing the GOF and Chi-square Test for Independence was which subject they should on. I already figured out for the Gof test, but for the Chi-Square test, I started to struggle on which two subjects of data I could use for the test. But, I decided to use the group data collection we all did on December 5th and compare two of the different categorical and numeric data.

# data[].attributes.body
I think my muddiest point is being able to interpret my data. I usually takes me some time to understand what I am trying to show and interpret from my results into a table. And from the table into words explaining what I found. But I am doing better than the beginning of the semester with the resources that were shown to us.

-Fernanda Pineda

# data[].attributes.body
I think the muddiest point for me is the knowing the difference between goodness of fit and two proportions. To me it feels like they look at the statistics the same way, so I feel like I still don't understand.

Mario Madrigal

# data[].attributes.body
I feel that I understand hypothesis tests pretty well now that we've had lots of practice with them. What I find to be muddy is knowing what separates the different hypothesis tests that we perform, for example whether the test is for comparing two proportions, a GOF test, or a test for independence. I notice that we follow the same process each time. Comparing two proportions and testing for independence have been tricky because of the additional variable you have to deal with.

# data[].attributes.body
I think my muddiest point is being able to convert the data to Excel and be able to interpret the results. I am getting most of the math, just need a little bit of help in the interpretation. I am also a little bit behind because of college apps, but I am catching up this week.

# data[].attributes.body
2nd times the charm right? Since my first one disappeared I decided to try again.

Oddly enough, that should be the theme of my time here, try again. I keep trying over and over because my muddiest parts seem to be having grands ideas and class passing by so fast that I don’t get to implement them. Between that, other classes work and family we are feeling the strain….

To my Classmates still with us, YOU GOT THIS! These last few weeks can beat us and the new year isn’t ready for the party we are ready to have!!!!!

# data[].attributes.body
My muddiest point is probably interpreting some of the tables I get from GoogleSheets. I understand what's happening in the big picture and can speculate a little with the initial data but I don't think I could reliably explain how the formulas work.

# data[].attributes.body
I believe my muddiest point was understanding some of the various parts of statistics, especially towards the end of the last few modules. I also had a hard time with finding good resources for some of the stats I needed to look up, and also had a hard time using the Google Sheets on my own. Hypothesis testing is something I kind of understand. It is something I can't fully do on my own just yet, but with examples and repetitiveness I understand it fairly well for a little bit. I don't fully understand confidence intervals.

# data[].attributes.body
My muddies points were probably staying on track and getting things done promptly. With personal things going on and a stressful job/semester, it was a little hard to keep up, but that's life! The mathematics of it all was fairly simple to understand!

# data[].attributes.headline
My muddiest point was motivating myself to finish my work for the class. I often procrastinate and I've thought about giving up.

# data[].attributes.subject
My muddiest point was motivating myself to finish my work for the class. I often procrastinate and I've thought about giving up.

# data[].attributes.body
My muddiest point was most likely to probability concepts. Probability problems can be unclearest to me. Things I could use more guidance on would also be finding a relevant sources for probability concepts and looking resources based on probability. I'm already starting to get the essence of confidence intervals. I'm wasn't starting to grasp hypothesis testing. Generally, I'm managing by using the modules on Canvas, review through my notes on my iPad that I took, etc. All the probability concepts wasn't working for me while everything else for data collection was working for me.

-Devin Nghiem

# data[].attributes.body
I think my muddiest point was truly understanding the math behind statistics. I understand how to get the data to put it up in charts, and organize it, but without the formulas provided, I would be so lost.

# data[].attributes.body
I've been playing catch-up with assignments, and upon reflection my muddiest points have been coming up with my own ideas. I'm very hands on and need many examples, so I sometimes get confused or slightly miss the mark with my ideas. I also struggled a bit with using google sheets. I think I would've watched more tutorial video and gotten more familiar with it had I not fallen so behind.

# data[].attributes.body
Muddiest point for me was playing catch up as well as coming up with ideas. I am still trying to manage my time properly with all the life changes I have experiences in last several months. I am forever greatful for professors like Halsey, that make it possible for students to succeed even if we fall behind.
I did come up with some ideas for research and then half way through project I would realize it is not working out and would have to start all over. I believe it also made me fall behind even more. But I am all caught up now, Thank you Professor Halsey :)

# data[].attributes.body
The muddiest parts for me was that I was playing catch up due to life situations. Doing all this work in a short. period of time has my brain strained, ha. Other than that, the muddiest part if thinking of topics to collect data on (something that interests me)

# data[].attributes.body
I think the muddiest part is getting the data because it takes time. But the videos help so much and we get the google excel with everything that we need. Sometimes its hard to find what numbers to put in the table but that is about it

# data[].attributes.body
I think my muddiest points are making the charts accurately to my data in google sheets. Sometimes I struggle with how to list the formulas and where to place them. I think being able to view other people's work has helped me/

# data[].attributes.headline
I'd like to say my muddiest point so far is making the time to get real life samples for data and using that data for calculation. I think the course is taught really well with great details and feedback, but I might just be slow and need more time to finish assignments.

# data[].attributes.subject
I'd like to say my muddiest point so far is making the time to get real life samples for data and using that data for calculation. I think the course is taught really well with great details and feedback, but I might just be slow and need more time to finish assignments.

# data[].attributes.body
I overall struggled with coming up with unique project ideas on my own. I would have ideas but not know how to group them in order to gather the necessary data.I really liked how we went over examples in class similar to our projects. One thing that was not working is how overwhelming each module is on canvas, I would get lost trying to navigate through all the information.

# data[].attributes.body
I would have to say is coming up with the appropriate sample to meet each of the different Project requirements. And the amount of work required to be completed on Monday so that it was not late. Overall, I learned a lot in this class.
- Pablo

# data[].attributes.body
My muddiest points have been figuring out what kind of data/groups are needed for each type of test. Once I was able to figure out a study and the data points I needed to input into formulas it became more manageable. I believe I am starting to get a grasp of confidence intervals and hypothesis testing. I got a little behind about half way through the course but was able to gradually catch back up. Not having hard weekly deadlines was helpful.

-Cat

# data[].attributes.body
My most difficulty in the class is the Chi-Square testing. More specifically, calculating the expected frequencies, with it being challenging to understand their meaning as well. Maybe I haven't contributed enough time to studying the concept, but I feel like I'm guessing towards the end the problem and the numbers become extremely confusing so I definitely need more guidance there.

# data[].attributes.body
hello everyone my mudiest point is probably applying real life examples to the data that we are shown throughout the modules. Sometimes my brain feels a bit foggy when it comes to this aspect. I believe I could be managing better but due to personal situations in life it has caused me to get a little behind, and I am currently working to catch up.

# data[].attributes.body
I'd say muddiest moment in this class was Google sheets. I would have to rewatch the tutorials several times for my data to come out correct. Overall I love the structure of this course.

# data[].attributes.body
During the class, I just found this out by a very help peer in the class. That I have been working harder than needing too. Wondering why the assignments were difficult to do and get the proper math. That I have been doing every assignment from scratching and plugging in every number myself to get the inference or value of the static equation projects! I mean better late than never. I am a little confused on how it all works but then I do know. I think its been really wonderful to have pro be very organized and self explaining how to do the projects its been fun and hard and easy. A great time and happy to know so much now

# data[].attributes.body
I think my muddiest point are just figuring out how to put real life data into calculations with google sheets for example. Sometimes things just don't look about right when I try to conclude, but usually it does make sense. The modules give good examples, but I sometimes have a hard time thinking up my own unique example. However, it feels like a big lift off the shoulder after all the data is collected and inputted.

# data[].attributes.body
Hi everyone! For me, this class had some ups and downs. I would say the most difficult part of the class for me would be parts of the hypothesis test. The math made sense to me, but I always had a hard time figuring out the different hypotheses and how to differentiate between the alternative and null hypothesis. However, something that really helped me was the examples that were included in the modules. I would often go back to them to help me whenever I was stuck on an assignment. Additionally, I really appreciated the videos that professor put out because they would oftentimes clear up any confusion I had. Overall, I would say that I learned a lot from this class and all the resources provided by professor were essential in allowing me to be successful.
-Harsimran Kaur

# data[].attributes.body
The hardest part and confusing for me was trying to relate and find real life examples to conduct my projects. The average inference point seemed kind of confusing in the beginning, but as I read more into it, it got more easy to understand.

# data[].attributes.body
I've enjoyed the class. I'm not a math guy, and that is what it is. I've enjoyed learning and applying some of the things we have gone over. Definitely a rough class to do on an expedited semester. There were a handful of times when I tried to join the Hangout, and no one was there. This is my 1st online class, and I suffered from the lack of interaction and face to face with my peers. I was able to meet with the professor face to face to discuss things, and walked away from those meetings feeling better. Did I learn things? Yes, am i satiation now? no. :-)

# data[].attributes.body
hello,
The points I am most confused on are the module projects and well everything. The way everything is set up it does not offer enough chances to fully grasp and check knowledge before the projects. I also think that the projects make things far more confusing that actually showing if we know the information or not.

# data[].attributes.body
I found my muddiest points to be the module projects. I found myself getting quite confused during them and ended up spending a lot more time on them than I probably needed. Everything else was quite clear and I was able to do it all. I think everything we were taught was taught in a clear and concise manner so I had no trouble understanding the content itself.

# data[].attributes.body
The decision rule and alternative/null hypotheses were both initially confusing to me, however I feel more confidant now in that regard. One area that I found challenging was forming an idea for my module projects. Overall, I found the class to be pretty smooth and enjoyed it. Professor Boyd's videos were IMMENSELY helpful! I wish everyone the best of luck and have a great rest of your Summer!!
-Tristan

# data[].attributes.body
I enjoyed this class very much! I liked getting to think of ideas with everyone and it helped a lot when it came to creative blocks. Also, being able to have so many options for the module projects made it easier for me to be interested in what I am analyzing since I was able to pick whatever I thought was interesting at the time! I also really appreciated the videos Prof. Boyd posted -- when it comes to math, I for some reason cannot follow textbooks or words. So, the videos were so helpful as I can follow along with how to complete the assignments. However, I had a hard time grasping on the concept of creating Null and Alternative hypothesis statements. I know what they are, but I keep confusing the two, so I'd have to repeatedly reference the module pages for help. Another thing I loved was the support of Prof. Boyd! I'd reach out when I had issues, and he'd respond very quickly with thoughts on how I can improve. Thank you everyone for being a great class!

# data[].attributes.body
At first, I had a lot of difficulty understanding the material of this class. However, after many hours of figuring everything out and doing assignments, I am a lot better at grasping these statistic ideas. The projects last week were confusing at some times, but the walk through videos and very organized module helps me succeed in completing the assignments. The main thing I struggled on was getting the hang of the Inference for Single Proportion Chart. Sometimes, I'd input my values and the chart would have red markers and I had no clue why. I did however get around that issue after trial and error!

# data[].attributes.body
I find this class to be enjoyable with the way the Professor is teaching us the material. I have always been not that great in mathematics, but I do appreciate the effort that Professor puts for us to understand the material. With that being said, I feel like the hypothesis test is one of the complicated tests from this class, at least that’s how I feel. Based on the directions I can complete the test however I am not sure if the test is correct or not. If we can have examples of the tests being worked on in a video will be more helpful compared to reading them.

# data[].attributes.body
So my biggest struggle this semester has been myself. I allowed myself to fall completely behind and I had to play catch up. I learned sometimes life hits you all at once but you can't just give up. I am pushing myself daily to be better than I was the day before. I just hope my effort doesn't go unnoticed. Also, I am so grateful for the due date flexibility. I would say reading all of the slides in the modules wasn't very helpful for me at all. But when I watched the videos that Halsey posted, it made so much more sense. As far as content goes, the muddiest is definitely the CI's. I am still a bit confused about them but I hope I did the assignments correctly.

# data[].attributes.body
I agree with everyone’s comments. It’s been a great class, and I’m so appreciative that it has been project focused, and not exam/what do you remember based. I’d be failing for sure. I am so thankful the due dates are not hard and fast. I would have been more stressed if they had been. I struggle with inferences and finding ideas. I also struggle with the ‘why’ aspect. Often, I can see there’s a difference in something, so I question why all the extra steps. I know it’s an introductory course so we’re not going to go deep, but I get caught on the why of it all. I spend a LOT of time figuring out how to create the formulas to put on the sheets to turn in – copy/paste hasn’t been my friend in this regard. I have to do a lot of searching for symbols and how to add them. I feel equally clear and muddy about what we’ve studied. It’s been a quick cram of everything, but Professor Halsey’s videos have helped tremendously. I think if this were my major, I would have opted for the full semester course so there would be time to absorb it all.

# data[].attributes.body
This lesson is incredibly intriguing to me, however I'm still puzzled about critical value, test statistics, and p-value. I'm not sure why we need to compare these figures to see if the data is statistically significant. The project videos and Google Sheets template have been quite beneficial to me; however, I wish there were additional films discussing critical value, test statistics, and p-value. Overall, it not super hard just need some more explaining how it is included to the problem.
-Tyler Duong

# data[].attributes.body
I really enjoy the class, even when it gets a little confusing the videos and the canvas material makes it clearer. I also don't feel the pressure I used to feel in other classes, one of the most enjoyable classes for me.

# data[].attributes.body
Hi class,
I think these past couple of weeks being in this class has been super interesting! I don't think I've ever had a Professor where they were project based instead of quiz/exam based, which helps me learn better. I do often struggle to come up with ways to creatively show the projects. In school I've learned to be analytical and not focus on how it "looks". But I have learned in this class it is real world experience to make your project of ideas to look creative and eye catching. Another thing I struggle with are test hypothesis and p-value. It is definitely confusing to me and wish I could understand it better. Other than that I think this class is great!
-Emily Bennett

# data[].attributes.body
With having to learn so much material in a short amount of time, I can confidently say that I'm mostly confused about everything! I try to use the videos and examples to guide me best but sometimes I still have a hard time understanding the concepts. One of the biggest difficulties I've found for me is the TEMPLATES. I get confused on which exact one I need to be using unless Professor Halsey references it somewhere in the module or in a video that he does for the project guidance. Other times I've found that some of the calculators need to be paid for now and when I try to search for another online it won’t always be the same. Other than that I've definitely given it all I got to try and turn in my best work with a peace of mind that if I got it wrong I'll be able to go back and correct my work.

# data[].attributes.body
I find this class very interesting, but topics I am still confused about are critical value, test statistics, and p-value. I do not understand why we have to compare these numbers to find whether the data is statistically significant. The project videos and google sheets template have been very helpful to me, I wish there more videos explaining about critical value, test statistics, and p-value

# data[].attributes.body
I honestly find this class pretty interesting and fun since we get to come up with our own topics and gather our own data which makes it very engaging and feels real. Although confidence intervals have been kind of confusing and hard at times, I think it is making more sense to me as we work on more and more projects. Everything else is fine though so hopefully I can grasp everything before the class is over.

# data[].attributes.body
I am still unclear on  hypothesis testing and understanding all the information to put into words. Just reading doesn't work well for me but having videos helps a lot.

# data[].attributes.body
The picture above pretty much sums up how I felt at the beginning of the semester. I felt like a deer in headlights, breaking down over the first few module projects. My biggest struggle was navigating Google Sheets- if I clicked one wrong thing or made one mistake, it was hard getting it back to normal. As time went on, I got more practice with it and soon I knew what was expected of me and what each graph/table meant. The only thing that's still muddy or unclear to me is the hypothesis testing- knowing when to conduct a right-tail, left-tail, or two-tail hypothesis. I know what each one means but applying it to the topic is a little tricky. I think more practice with the concept would help solidify it for me. Another difficulty I had was coming up with ideas out of thin air. My mind would just go blank when it came time to come up with examples for the different problems we were doing. I would usually have to resort to Google to help jog my memory and get ideas flowing Statistics was a foreign language to me at the beginning, but the videos and walkthroughs of module projects made the biggest difference! They were so helpful. I enjoyed being able to apply real-world scenarios to statistics, it made it so much more engaging and fun.

# data[].attributes.body
Hello Everyone, the one thing I found a bit of difficulty with is coming up with ideas for my projects since sometimes it's difficult to think of real-world situations but once I do find a situation it is nice to see how this class could really be helpful in the future

# data[].attributes.body
Doing a summer stats class online was/is super challenging, but with all the support and tutorial videos provided from the professor I feel like I learned a lot and was able to navigate difficult areas with ease. Hypothesis testing is still 50/50 for me. Truthfully, one of the muddiest points for me still is utilizing google sheets along with all the formulas. I feel like there are many more shortcuts I am unfamiliar with that could have made this course easier. This last module seems to be the most clear for me so that’s promising!
-Britney Weber

# data[].attributes.body
Hey everyone,
For me it takes a while to take in a single concept. I was able to learn more on how to use google sheets each week since I've never used it before. The video walkthroughs were also super helpful and easy to follow. Although it was challenging it was still a very interesting class and a lot of different concepts that we learned about the past few weeks.

# data[].attributes.body
I think so far the class is going smooth. The hardest part for me was grasping the concept of Confidence Intervals. For the most part, the class is challenging but fun.

# data[].attributes.body
In my opinion, the class has been progressing smoothly thus far. Personally, I found the concept of confidence intervals to be the most challenging aspect.

# data[].attributes.body
I think everything thing has gone okay so far. The most challenging topic for me has been hypothesis testing. I had a hard time understanding what data to input and change for each formula and type. I think I have a grasp on confidence intervals. I am also not tech savvy so I have been trying to figure out which platform would be best.

# data[].attributes.body
Hello all!
For me I am slowly but surely getting to understand the information being provided and what all the numbers mean. What I seem to struggle with most is excel and figuring how to do the formulas in them properly. I am thankful for my resources in helping me with this and I think I'm getting it a bit more now, however it is just going over my head for some reason. Does anyone else feel this way?

# data[].attributes.body
For me the information has been generally easy to understand. Something I do struggle with are the charts on Excel since I'm not savvy when it comes to that. I also have to do the majority of my work on my phone which did make it difficult. Overall it's not bad though.

# data[].attributes.body
Most of the information for me wasn't too bad. I made it harder on myself than it needed to be. The confidence intervals were a little challenging until I began to under stood it. I managed pretty well given my circumstances, but I could have had an easier time if I kept up with it. I definitely will not trust myself with flexible due dates again.

# data[].attributes.body
This GIF sums it up for me. Its a lot of material being covered in a short amount of time, but that's what we signed up for right. I think time management is my nemesis this semester and ultimately its my fault. I am getting this a lot better than I did the last time I attempted this class. I do have to say the equations always get me.. so I am very thankful for the google sheets and the video walk throughs. I also have to say that the program R is difficult for me, but at least I can say I have heard of it now.

# data[].attributes.body
For me this course has been both a struggle and a blessing. It's taught me to approach life in a different way. However, it's been a challenge juggling life with a course as fast as this. What is unclearest to me probably is how to you google sheets and specifically R (tho I hope to get better) I feel pretty good on it but theres moments where I just have no clue what to do. Moreso, what has been a struggle I'm realizing is knowing what exactly to do with data I have, seems like theres so many ways to disect I often stumble along the way. I could use more guidence in getting deeper understandings rather than only touching the service. I'm not to confident on confidence intervals but I feel confident on hypothesis testing. What has worked great for me is the videos, they work so wonderful in the sense they are both visual, auditory, and overall engage multiple senses. Often for me personally seeing so much text on a single page over whelms me, but the videos have made it much simplier to digest.

# data[].attributes.body
We have covered so much material in such a short amount of time and Halsey has been incredible about providing pages of explanation, videos, check ins to make sure as a student we have all the resources needed to succeed and for that I am grateful! Not every online class feels manageable or approachable. It has been so hard to juggle the family, working full time and this course but somehow I am slowly finishing the work. I was impressed with me being able to grasp these concepts of hypothesis testing's and confidence intervals after not being in school for so very long but I feel encouraged at this point because I have some understanding of the topics covered and have most enjoyed playing with the formulas within excel!

# data[].attributes.body
The flexibility of the schedule in this class has been a life-saver. It's a really meaty class to cram into a summer session, and covers a lot of things that I'm just barely grasping (or think I'm grasping, we'll see), but having wiggle room with timing has been really key to giving me a chance of passing.

My wife and I sort of unexpectedly are having to move during the session so it's been a bit hectic and my brain hasn't been super dialed in.

As far as the concepts go, when they are talked about in verbal, conversational terms, I can wrap my head around them decently well. It's when we get into the mathematical terms and start having to apply the concepts in a math way that I start to get a bit flustered and have to rely on the templates a lot (which, thank you so much for those by the way, Halsey! They're an amazing background tool to have). A lot of that is me getting in my own head since I've had a lot of trouble with mathematics in the past and so I subconsciously sort of count myself out of being able to understand it, if that makes sense.

# data[].attributes.body
I think for me the merriest part is just finding the motivation and time to do the work. Since the course is expedited it is a little difficult grasping all the information, overall this course is really good and I've retained most of what we learned. The walk-through videos are super helpful and in general all of the pages have lots of good useful information, I think just managing my time and the work for this class and my other class has been the most difficult thing so far.

# data[].attributes.body
I think the muddiest parts for is time management, just like someone else in this class. I am taking another class, and I didn't expect the workload for that class to be so much that it is interfering with this class. Im so so grateful that Halsey is understanding and accepts late assignments; however, I need to not rely on that.
I also thought trying to understand the tables was quite muddy at first, but I slowly got used to them and can just about interpret them.
Overall, I am like barely managing. I am at least getting my assignments done. Maybe not on time, but they're done.

# data[].attributes.body
I think the muddiest thing for me right now is trying to maintain school work and my kids and trying to pass all my classes especially this one this class has been the most struggling class for me i never struggled so much in a class until now I’m not sure why this has been the most challenging hard class for me but it’s been a roller coaster

# data[].attributes.body
Muddiest parts for me are managing my time amongst this fast pace class.

# data[].attributes.body
I think that the muddiest thing for me right now is my time. I have a job where I work Monday through Friday 8-6 and am trying to find time for homework but it is really hard to. When I get home, I usually want to just go to bed, but I also have to work on some homework, and it is very stressful and very hard to compromise on.

# data[].attributes.body
I think I have been struggling a little bit in identifying what information is needed when. We have learned so many topics and then it feels like we are getting to a point where everything seems hard to understand. I utilize the videos and read the instructions in the modules, but it is hard to keep up. I do appreciate how many resources are available in the module for us to look at. I would appreciate  a bit more detail in assignment instructions, just so I can have a better idea of what I am supposed to be doing on my part.
Jimmi

# data[].attributes.body
Muddiest Parts:
I have been really enjoying learning, and everything is made ten times easier with your walkthrough videos. There has been so many times where I literally just don’t even know where to start on a project and seeing you walkthrough and actually explain somewhat step by step is like perfect. I will say this is probably one of the easiest hardest classes ever, if that makes sense. I am not at all good at math, partnered with the heavy reading load , and module projects; this class has for sure been difficult. But like a lot of students say, the professor really makes or breaks the class and you’d made it a lot easier and enjoyable.

# data[].attributes.body
As we get closer to the end, I am constantly losing motivation to do anything. the module projects just don't make sense to me at all like choosing what example to make my project on is the hardest and how to incorporate the example into data. I tend to turn in assignments late due to me not understanding how to make my example into data the way the module project wants it.

# data[].attributes.body
I have, and continue to, struggle with the null and the alternative hypotheses. I grasp the general idea and what they mean, but applying them to each scenario is a little difficult for me since I am not 100% sure how to phrase them, if that makes sense. Knowing if we're supposed to include the averages and standard deviation for each module project is a little unclear too.

# data[].attributes.body
When first looking at the assignments and the projects for the module I was a little nervous. I am more of a visual and auditory learner compared to just reading so I like the videos that the professor posts and they are very helpful for me.  After watching the videos provided, I am getting the things done and also gaining confidence through the process.

# data[].attributes.body
At first I was really struggling with determining which type of test to use and choosing a hypothesis, but with the last two module projects I now have a better grasp on these. I think that the video walkthroughs are the most helpful part of getting through a module project, sometimes I keep it open to come back to multiple times while working on the project because its an outline and walkthrough in one and easy to work with.

# data[].attributes.body
I think that the hardest part has been getting through the module projects, since I feel like the information gets jumbled in my head once I try to apply it to my own experiments. I manage to try and get through it, it just gets overwhelming at times.

# data[].attributes.body
The muddiest part for me would have to be doing the module projects because they demand a lot more time and work to do. Like many of us have said already, the video walkthroughs are super helpful when I am struggling to understand any of the material. I feel that I could use more guidance on Google Sheets and more about the functions and formulas that we'd use for classwork. Yes, I am starting to get a grasp of confidence intervals and hypothesis tests. I find that the google sheet templates are very helpful producing these. Generally, I think I am managing well.

# data[].attributes.body
One thing I am struggling with is just starting on my assignments. It was getting close to the end and I started to lose motivation as we got closer. Sometimes also when I am using google sheets I mistype something and everything is off like my data. Video walkthroughs help me understand a lot I just don't have the motivation as when I first started this class.

# data[].attributes.body
One thing that I would say that I was struggling with in this class are the module projects. To overcome that struggle I would rewatch the videos again and again. I think that I am starting to get the idea of confidence intervals and hypothesis testing as I rewatch the videos.

# data[].attributes.body
I would say the most unclear thing or something I've been struggling with are the module projects. It's being able to focus and get started is the hard part. The data sometimes can be confusing based on your question. I've been trying to understand it better but sometimes starting off is a struggle for me.

# data[].attributes.body
At first, I was struggling with staying focused and not getting lost in the material. I tend to overwhelm myself with work more than I need to. I think the hardest part has been the module projects. I tend to overcomplicate them which ends up making it impossible. I understand the concepts but have trouble applying them into my own projects. I feel like I have gotten the hang of Google Sheets much more than in the beginning. I am also starting to better understand the hypothesis theory and different test tables.

# data[].attributes.body
At first, I was struggling to understand how the confidence intervals and hypothesis tests actually showed what the data meant and why they were relevant but after doing several examples and problems it became much clearer! I really enjoy the module and project walk-through videos, I always revisit them several times to fully understand the criteria.

# data[].attributes.body
I would say by far the most unclear thing for me was understanding the format of the most recent module projects. even though they were difficult for me in the beginning I soon caught on and was able to finish all the projects

# data[].attributes.body
I think I would say I am getting the hang of it because of all the videos and examples we have been given and think I am grasping hypothesis testing and overall I am managing alright while doing another class, this class, and work and glad I am almost at the home stretch. Having visual examples and stuff is working and alos trying to memorize the symbols is the hardest part too.

# data[].attributes.body
I can say that as this week has progressed I can see how each unit/module correspond to one another and its starting to click for me. I feel what's really helped me and has allowed me to succeed is your video walk throughs that you upload. Alejandro

# data[].attributes.body
I can confidently say I am grasping the hypothesis theory a lot more than I did originally, even more than I expected to. One thing I wonder is, if the data gather equals null, is it still possible for the actual intention of the units to be the alternative? I hope that makes sense! Veronica Martinez

# data[].attributes.body
For me, the only muddy part of the class for me is getting the chart for the module project. If there was a link to the google sheets as a template that would make completing the assignment so easy for me. I struggle with how to implement my numbers which translates into my hypothesis. But once I get a better hang of that part of the module projects I should be good :)

# data[].attributes.body
Hello everyone, in this module so far I see how things are relating to each other and I do not have any problem understanding the information just by reading the informations and watching the walkthrough videos because I think that is the only reason I have not been struggling.

# data[].attributes.body
Hey guys, personally I am so so thankful for the video walk-throughs on most of the assignments. I struggle a lot with the wording of these assignments but the video walk to help me so much. I feel like I have a pretty good understanding of the hypothesis Testing. I’ve had plenty of experience working with hypothesis not only in science classes but sometimes even in English classes. Something that is muddy to me in this class is understanding all the symbols/ new vocabulary.

# data[].attributes.body
I definitely have been struggling to get through how to set up a hypothesis test. I love that Halsey includes module walk throughs, those really help me. I feel like there is a lot to cover in a short amount of time and I find myself behind and stressed out. We are all doing our best and we should be proud!

# data[].attributes.body
First, I’d like to say that if it wasn’t for the tutorial walk through videos and hangouts, I would be sooo lost! I find the most challenging part or unclear is interpreting the data and putting it into words. Even though there are videos step by step, the data we have is different so I don’t know if I’m doing it correctly. But I wing it. Each module I am slowly understanding more and more. The downside is that the summer course is so fast,  but I think for the time frame everything is on point.

Jaeniene

# data[].attributes.body
The module projects are kinda difficult for me to grasp solely because the choosing and creating tables based on my project can get so confusing for me. (I'm not gifted in the math department...) But the videos you provide also help me a lot to follow a guide for what my project needs and what it should look like.

# data[].attributes.body
Hey everyone,
So far I have been feeling pretty good about the overall progress of understanding hypothesis testing. I'm familiar with the idea of hypothesis from some science classes I have taken. However, some of the muddiest points for me is trying to understand the long list of symbols that goes with this unit.

# data[].attributes.body
Overall, I have been having a good progress understanding the nature of hypothesis test and how every factor affects it. I am having some trouble with the symbols but I keep trying to memorize them. I feel like I am more of a visual learner, so definitely the videos from the module are super helpful.

-Roberto Rendon

# data[].attributes.headline
overall I think this class has been great... I do have some trouble with the google assignments and having my links show up properly on canvas. -Deja 

# data[].attributes.subject
overall I think this class has been great... I do have some trouble with the google assignments and having my links show up properly on canvas. -Deja 

# data[].attributes.body
Overall Statistics has always been rough for me.  I can't wrap my head around that all of our formulas, tests, etc are never going to be absolutely 100% certain or correct.  And these results will most likely be skewed with bias or sampling errors.  I think the more I do it, the more used to it I will get and just accept it.
Another example is that for a while, I kept confusing Confidence Intervals with Standard Deviation.  I thought they were the same!
Lastly, I am still struggling with the technology. I am a total old-fashioned textbook girl, but that's not the way the world is, so I'm grateful for this opportunity to get it into my head that this is the new normal! :P