This repository contains the assignment for the first week of the Brainhack School.
The code was tested on Python 3.7.6 using miniconda, with the following package versions:
- pandas 1.0.3
- seaborn 0.10.0
- scipy 1.4.1
To install the packages you can use conda (run these commands in the shell or in an anaconda prompt if on Windows):
conda install pandas=1.0.3
conda install seaborn=0.10.0
conda install scipy=1.4.1
Alternatively, you can install them using pip:
pip install pandas==1.0.3
pip install seaborn==0.10.0
pip install scipy==1.4.1
You will also need jupyter, which can be installed with either conda install -c conda-forge jupyterlab or pip install jupyterlab. For further instructions see here.
The analysis is run in the jupyter notebook myanalysis.ipynb. It will generate a scatterplot of partY and VIQ and fit a linear regression for the male participants in the brainsize data set. For more information, see the comments in the notebook.
You should get the following outputs for the linear regression:
partY ~ VIQ:
- Slope: -0.3231687799523172
- P-value: 0.006498162757245594
- R-squared: 0.3793545687503652
partY2 ~ VIQ:
- Slope: -0.1337686512128251
- P-value: 0.3361285973253568
- R-squared: 0.057902062587242106
...and for the scatterplots:
