IMSE 440: Applied Statistical Models in Engineering

Syllabus Canvas Project


Week Topics
0 Course introduction, Introduction to Python
1 Introduction to data analysis in Python
2 Introduction to data analysis and visualization in Python
3 Simple linear regression, parameter estimation
4 Assessing the accuracy of the coefficient estimates
5 Assessing the accuracy of the model, correlation
6 Confidence/prediction intervals
7 Multiple linear regression, model utility test, interactions
8 Categorical predictors, model diagnostics & evaluation
9 Overfitting, Cross validation, model selection
10 Logistic regression, classifier evaluation
11 Introduction to design of experiments, comparing experiments
12 Experiments with a single factor, completely randomized design
13 Blocking factors and common designs, randomized complete block design, Latin Squares design