In this part of my practise the following hypothesis were performed.
- Independent T-test to test the difference between two groups
- Welch's T-test for sampples with unequal variances
- Paired difference T-test for assess the significance of an intervention
- Applying one-way and two-way ANOVA for multiple categorical values
The test were performed on different datasets for the following purpose:
- Bike sharing data set: To test whether weather situation, temperature affected the numbe of bikes rented.
- Blood pressure dataset: To test the blood pressure results before and after the intervention are statistically significant or not
- Women's clothing e-commerce reviews data set: To test whether the frequency distribution of a dataset matches the expected distribution
Following tasks related to hypothesis testing and data visualization were done:
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Hypothesis testing
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Data visualization
You can find all the datasets used in this project inside the datasets
directory. The datasets include
- Bike_sharing_dataset_preprocessed.csv
- Blood_pressure.csv
- Womens Clothin E-Commerce Reviews.csv
You can clone the repository and practise for yourself.
This is a part of Pluralsight's - Interpreting Data Using Statistical Models with Python
Thank you for your support ❤️