Capstone Project: MuscleHub. Request for feedback

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1

Would you be willing to provide feedback on the coding and presenting I did as part of this capstone project for the path Analyze Data with Python?
Is there a more efficient way to perform the different assignment?
Do you agree with the findings I discuss in my presentation?

Link to my code:

Link to the presentation:

Thank you in advance and please let me know if there is something you would like me to provide feedback on.

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Welcome to the Forums. Congratulations on completing the project. :partying_face:

It’s so great that you did a video presentation of the project too. There was another learner who did that and she had a lot of fun with it.

There is one thing I’d tweak.

  • At point 7:06 in the presentation it gets a little confusing. There are 3 questions this A/B testing is trying to answer between the two groups A&B (A, who took the fitness test, B did not take the test). For each question there is a null and alternative hypothesis. 2 out of the 3 tests had a statistically significant difference between the two groups. So, doesn’t it seem like getting rid of the fitness test is the recommendation? Your Jupyter notebook has it laid out well, so, perhaps try to follow that.

Something else to keep in mind with presentations of data & testing…know your audience. Are they tech savvy or not? If they are savvy, then you can go into more details about the specifics of the hypothesis tests. If they are not you could stick to graphics and bottom line numbers (like you did). You can always include an appendix with all your data tests and notebook in detail and refer people to that if they’re interested or have more questions.

Oh, and bonus points for The Simpsons figures in the background on the desk! :slight_smile:

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3

Thanks for the reply. The slide about the A/B test does seem confusing in retrospect; there is a lot of text on that slide. Based on the quantitative data it seems like getting rid of the fitness test is the right call. However, the qualitative data shows that there are people who are new to the gym who appreciate it. Hence, doing further research into identifying that specific group and offering them the fitness test could be useful. That’s why my conclusion is based on whether the audience is willing to do further investments: either pursue further research or get rid of the fitness test.

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