STA 207
Preface
1
Causal Inference
1.1
Association and Causality
1.2
Potential Outcomes
1.3
Experiments v.s. Observational Studies
1.4
Learning Objectives
2
One-way ANOVA
2.1
Simple randomized experiments
2.2
One-way ANOVA
2.2.1
A motivating example: the Spock trial
2.2.2
ANOVA model
2.2.3
Statistical inference
2.2.4
Alternative forms of the ANOVA model
2.3
Model diagnostics
2.4
Learning Objectives
3
Two-way ANOVA
3.1
Experiments with two (or more) factors
3.2
Two-way ANOVA
3.2.1
A motivating example: Hey fever relief data set
3.2.2
A two-way ANOVA model
3.2.3
Statistical inference
3.2.4
Model diagnostics
3.2.5
Strategy for data analysis
3.2.6
Special case: one observation per cell
3.2.7
Unbalanced two-way ANOVA
3.3
Learning Objectives
4
Random and Mixed Effect Models
4.1
Nested design
4.2
Random effects model
4.3
Learning Objectives
5
Repeated Measures Design
5.1
Repeated measures design
5.2
Analysis of repeated measures designs
5.2.1
Two-way ANOVA model
5.2.2
More complicated repeated measures design
5.2.3
Longitudinal data analysis
5.3
Learning Objectives
6
Case-control Study
6.1
Case-control study
6.2
Logistic regression
6.3
Generalized linear model
7
Observational Study
7.1
Causality in observational studies
7.2
Analysis with no latent confouding
7.3
Instrumental variable
7.4
Missing data
8
Complex data
8.1
Data in the big data era
8.2
Useful methods
8.2.1
Penalized regression
8.2.2
Model selection
8.2.3
Other
9
Project description
9.1
Project 1: Project STAR I
9.1.1
Background
9.1.2
Tasks
9.2
Project 2: Project STAR II
9.2.1
Background
9.2.2
Tasks
9.3
Project 3: US Traffic Fatalities
9.3.1
Background
9.3.2
Tasks
9.3.3
Hints
9.4
Project 4: Bank Marketing
9.4.1
Background
9.4.2
Tasks
9.4.3
Hints
References
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Statistical Methods for Research II
References