This repository contains exercises for practicing hypothesis testing, specifically focusing on comparing the means of two groups to determine if there is a significant difference. The exercise provided is designed for nutritionists looking to understand if one diet has a higher impact on weight loss compared to another.
Background: A nutritionist has conducted a one-month weight loss study comparing two different diets. Participants were randomly assigned to one of the two diets and their weight loss over the month was recorded. The goal is to determine if there is a significant difference in the average weight loss between the two diets.
Data:
| Diet 1 | Diet 2 |
|---|---|
| 2.0 | 3.0 |
| 2.5 | 3.2 |
| 3.0 | 3.1 |
| 2.8 | 2.9 |
| 2.3 | 2.8 |
| 2.7 | 3.0 |
| 2.5 | 3.2 |
Problem Statement: Using the data above, perform the following steps to answer the question: Is there a significant difference in average weight loss between people who followed the first diet and those who followed the second diet?
- State the null hypothesis (H₀): The second diet does not result in more weight loss than the first diet.
- State the alternative hypothesis (H₁): The second diet results in more weight loss than the first diet.
- Perform a Student's t-test to test the hypothesis.
- Analyze the results and draw conclusions.
- Clone this repository to your local machine.
- Open the Jupyter Notebook
exercise_1.ipynb. - Follow the instructions within the notebook to complete the exercise.
- Save your work and push the changes to GitHub to share your results.
- Python 3.x
- Jupyter Notebook
- NumPy
- SciPy
Feel free to fork the repository and submit pull requests if you'd like to contribute to improving the content or adding new exercises.
This project is licensed under the terms of the MIT license.