This course is designed to introduce you to graduatelevel behavioral research with a focus on data analysis. We will examine the core concepts in inferential statistics, as well as issues of replication and reproducibility. The course also provides a survey of methods that serves as a foundation for other quantitative courses, both within and outside the department.
Prerequisites: This course assumes that students have taken a previous undergraduatelevel research methods course (e.g. PSYC 2100WQ) and have a strong understanding of descriptive statistics, ttests, and correlations. If you are concerned about your readiness for the course you may want to discuss how to approach the course with Professor Stevenson or your advisor.
Problem sets can use your choice of programming language (e.g. R or SPSS). R is available here (or Rstudio). SPSS is available here (or AnyWare).Topic  Assignments  
08.29 08.31  Course Intro Data Analysis 
Problem Set 1 due 9/2 
09.05 09.07  Labor Day (no class) Visualization 

09.12 09.14  Null Hypothesis Significance Testing ...and its interpretation 
Problem Set 2 due 9/13 
09.19 09.21  Validity and Reliability Validity and Reliability 
Problem Set 3 due 9/23 
09.26 09.28  Experimental Design Effect size and power 

10.03 10.05  Oneway ANOVA General Linear Model 
Problem Set 4 due 10/04 
10.10 10.12  Contrasts and trend analysis ANOVA in practice 
Problem Set 5 due 10/14 
10.17 10.19  Factorial ANOVA Factorial ANOVA con't 

10.24 10.26  ANCOVA Multiple comparisons 
Problem Set 6 due 10/25 
10.31 11.02  Repeatedmeasures ANOVA Repeatedmeasures ANOVA con't 
Problem Set 7 due 11/04 
11.07 11.09  Intro to Mixed effects models Outliers and Transformations 

11.14 11.16  Tests for distributions Nonparametric tests 
Problem Set 8 due 11/15 
11.21 11.23  Fall Break (no class) Fall Break (no class) 

11.28 11.30  Intro to Bayesian methods Intro to Factor Analysis 

12.05 12.07  Project Presentations Project Presentations 
Project Reports due 12/16 