FROM DATA TO THESIS: Using Python for Non-Technical
Playground, Chapter 8: ANOVA and Regression

How to use this project
1. Open this directory in VS Code, Jupyter, or your favourite Python editor.
2. Open exercises.py. It has four parts:
   A. Practise the chapter       the book's exercises, with blanks (______) to fill
   B. Go further                 new exercises beyond the book
   C. Check your understanding   short questions to answer in your own words
   D. Do it yourself             open tasks: no starter code and no answers
   Run each section with Shift+Enter or in your Python terminal.
3. Check parts A to C in solutions.py, after you have tried each one yourself.
   Part D has no solutions: the tasks are open, as in your own thesis.

The exercises need these packages (install once):
pip install pandas numpy scipy statsmodels matplotlib seaborn patsy

Files
- exercises.py        the four parts, with starter code for parts A and B
- solutions.py        solutions for parts A and B, model answers for part C
- students.csv        one row per student in the wellbeing study (600 students)
- semesters.csv       one row per student per semester
- questionnaire.csv   the 22 questionnaire items
- trees.csv           classic forestry dataset: girth, height, volume
- ucbadmissions.csv   1973 Berkeley admissions aggregate data

Please note: Elaf and her data are fictional. The data was generated by a
computer program to look realistic, and its patterns were built in by the
author. It describes no real people and is not evidence about real students;
do not cite or use it as research findings.

All four parts can also be done in your browser at:
https://polla-fattah.github.io/data2thesis_python/playground/chapter08.html
