Skip to content

Latest commit

 

History

History
31 lines (20 loc) · 2.37 KB

File metadata and controls

31 lines (20 loc) · 2.37 KB

DS 1.1 Cardio Hypothesis Challenge

Applying DS 1.1 Concepts to a Real World Problem

This project empowers you to use a new and possibly never-before-seen dataset to go step-by-step through performing data exploration, cleaning, visualizations, and hypothesis testing for a real-world use case.

Instructions:

  1. Copy the link to the raw dataset here
  2. Create a copy of this notebook, and follow the comments and instructions in it
  3. Submit your copy of the notebook on Gradescope

References

All of the materials you need to complete the steps are in your lessons. Some good references:

  • Class 4: Applied Descriptive Statistics
  • Class 6: PDFs, CDFs, and Normal Distributions
  • Classes 7 & 8: Hypothesis Testing & Acceptable Error

Evaluation

This project will be evaluated as follows. You must get an average score of 3 to pass this project:

Score Rating Correctness Code Quality
1 Needs Improvement Required sections of submission are largely missing or not functional Code is messy and hard to follow. Code includes TODOs or does not include comments explaining which exploratory or visualization steps were taken and why. Some follow up questions may not be answered completely.
2 Basic Most sections are complete, some may be missing, or not fully complete. Some sections have code that is messy and hard to follow, or is not properly commented to demonstrate understanding. Follow up questions may not be clearly answered.
3 Proficient All sections are attempted, and 80% of sections are complete, and, if using the provided null hypothesis, arrive at the correct conclusion. Code is clear and easy to follow, all code is commented, and comments explain which exploratory or visualization steps were taken and why. Follow up questions are clearly answered.
4 Advanced All sections are complete, additional data explorations or visualizations have been provided, or a unique null hypothesis was created and evaluated. All code is clear, commented, and explained. Additional visualization or statistical resources have been utilized.