# Week 9: Regression I - Testing relation between two variables

# Key concepts

- Correlation:
- Pearson correlation
- Spearman’s rank correlation
- Interpretation of correlation coefficient

- Linear regression:
- Dependent and independent variable
- Slope (regression coefficient) and intercept
- Goodness of fit
- Residual variation and standard error of the estimate

- Assumptions of linear regression
- Errors Normally distributed
- Homoskedasticity
- Errors are independent of each other
- Independent and dependent variables must be interval variables
- Linear relationship between variables

# Before class

## Required readings

- Meier, K. J., Brudney, J. L., & Bohte, J. (2014). Introduction to Regression Analysis. In
*Applied Statistics for Public and Nonprofit Administration*. - Meier, K. J., Brudney, J. L., & Bohte, J. (2014). The Assumptions of Linear Regression. In
*Applied Statistics for Public and Nonprofit Administration*. - Video Intro to Linear Regression

# In class

- Lecture on key concepts
- In class practice
- Paper practice
- In-class practice

- Assignment catch-up: Qualitative group project feedback.

# After class

Qualitative group project proposal final due next week.