- Achievement 1: Using exploratory data analysis before developing a logistic regression model
- Achievement 2: Understanding the binary logistic regression statistical model
- Achievement 3: Estimating a simple logistic regression model and interpreting predictor significance and interpretation
- Achievement 4: Computing and interpreting two measures of model fit
- Achievement 5: Estimating a larger logistic regression model with categorical and continuous predictors
- Achievement 6: Interpreting the results of a larger logistic regression model
- Achievement 7: Checking logistic regression assumptions and using diagnostics to identify outliers and influential values
- Achievement 8: Using the model to predict probabilities for observations that are outside the data set
- Achievement 9: Adding and interpreting interaction terms in logistic regression
- Achievement 10: Using the likelihood ratio test to compare two nested logistic regression models
