Math 5 Final Project <br />
Peter Howell <br />
Section 40431, Prof. Raylene Potter<br />

# Relationship Between Course Modality, Teacher/Student Prep, and Final Grades

## Data Collection

- Overview

### Procedures

- Python script for extracting grades
- Anonymization of teachers and students
- Excluded Courses

### Critique of Procedures

- Shortcomings of data source
- Possible sources of bias

## Statistical Analysis

- Descriptive Statistics
    - mean, median, mode, percentials, variances, etc
    - interpretations of central tendency and dispersion

- Graphical Representations
    - bar, histogram, etc
    - determine approximate shapes
    - distributional assumptions met?

- Hypothesis Tests
    1. one-sample proportion
    2. two-sample proportion
    3. one-sample t test
    4. two-sample t test

- Correlation / Regression Models
    1.
    2.

## Shapes of Distributions

- are distributional assumptions met (normal? uniform?)

## Critique Analysis

- sample size
- bias
- assumptions 
- nonsampling errors

## Summary / Conclusions

## Appendix

- dataset
- code