IMSE 440

Week	Topics
1	Course introduction, Introduction to Python
2	Introduction to data analysis in Python
3	Introduction to data analysis and visualization in Python
4	Simple linear regression, parameter estimation
5	Assessing the accuracy of the parameter estimates
6	Assessing the accuracy of the model
7	Confidence and prediction intervals
8	Multiple linear regression, categorical predictors
9	Model diagnostics & evaluation
10	Overfitting, cross-validation, more on linear regression
11	Logistic regression
12	Classifier evaluation, Introduction to design of experiments
13	Comparing experiments, experiments with a single factor
14	Randomized design, blocking factors and common designs, Latin Squares design

IMSE 440: Applied Statistical Models in Engineering