Schedule

Week 1: Foundations

Jan 22

No class! (Semester begins Tuesday.)

Jan 24

Probability & Estimation Review

• Statistical Thinking 6.1-6.10
• Experimentology 5.1-5.3
• Cummings (2014)

Jan 26

Lab

Week 2: Models

Jan 29

Modeling & Inference Review

• McElreath 1.1-1.4
• Experimentology 6.1-6.5

Jan 31

Regression Review

• Gelman & Hill 3.1-3.5
• Experimentology 7.1-7.2

Feb 2

Lab

Week 3: Statistical Power

Feb 5

Repeated Measurements

• Experimentology 7.3
• Gelman & Hill 11.1-11.5
• Judd et al (2012)

Feb 7 HW 1 DUE

Power Analysis (John Curtin)

• Experimentology 10.4
• Button et al (2003)

Feb 9

Lab

Week 4: Linear mixed-effects models 1

Feb 12

Partial Pooling

• Gelman & Hill 12.1-12.9
• Mahr blog post

Feb 14

Generalizability

• Yarkoni (2022)

Feb 16

Lab

Week 5: Linear mixed-effects models 2

Feb 19

Pitfalls

• Meteyard & Davies (2020)
• Barr et al (2013)

Feb 21 HW 2 DUE

Model Inspection

• Luke (2017)

Feb 23

Lab

Week 6: Generalized linear model

Feb 26

Contrasts

• Nicenboim et al 8.1 - 8.5
• David (2013)

Feb 28 HW 3 DUE

Logistic regression

• Gelman & Hill 5.1 - 5.5
• MacKay 39.1-39.3

Mar 1

Lab

Week 7: Model comparison

Mar 4

Model comparison 1

• Etz (2018)

Mar 6

Model comparison 2

• Roberts & Pashler (2000)

Mar 8

Lab

Week 8: False alarms

Mar 11

Multiple comparisons

• Gelman et al., 2009

Mar 13 CA 1 DUE

Signal detection theory

• Lynn & Barrett (2014)

Mar 15

Lab

Week 9: Exam & Review

Mar 18

Review session

Mar 20

In-class exam

Mar 22

Lab TBD

Week 10: Spring recess

Mar 25

No class!

Mar 27

No class!

Mar 29

No class!

Week 11: Data generating processes

Apr 1

Priors

• McElreath 2.1-2.3

Apr 3

Posteriors

• McElreath 2.4.1
• Bayes Theorem
• Rouder et al. (2009)

Apr 5

Lab

Week 12: Bayesian data analysis 1

Apr 8

Bayesian regression

• McElreath 4.4
• Intro to brms
• brms tutorial

Apr 10

Group work

Apr 12

Lab TBD

• Project Proposal DUE

Week 13: Group work

Apr 15

Group work

Apr 17

Group work

Apr 19

Lab

Week 14: Best practices

Apr 22

Reproducible research

• Project analyses DUE

Apr 24

Computational models

• Oberauer & Lewandowsky (2019)

Apr 26

Lab TBD

• Peer review DUE
• HW 4 DUE

Week 15: Review and exam

Apr 29

Review

May 1

Project presentations

May 3

No lab

• Final report DUE

Week 16: Finals week

May 6

No class

May 8 CA 2 DUE

No class

May 10

No lab