Unless otherwise specified, readings are chapters from:
Field, A., Miles, J., and Field, Z. (2012). Discovering statistics using R. Sage publications.
Week 1: Introduction to R
Reading: Chapter 3. Main concepts: Install R & RStudio, open dataset, recode variables.
Week 2: Introduction to Research Methods
Reading: Chapter 1. Main concepts: Theory, hypotheses, variables, measurement.
Week 3: Introduction to Statistics & Univariate Analysis
Reading: Chapter 2. Main concepts (statistics): Descriptive & inferential statistics, sampling, p-value. Main concepts (univariate analysis): central tendency, variation, histogram.
Week 4: Bivariate analysis
4.1 Comparison of means
Reading: Chapter 9. Main concepts: comparison of mean, paired/independent samples.
4.2 Correlation
Reading: Chapter 6. Main concepts: pearsons r, covariance, scatterplot.
4.3 Chi-square
Reading: Chapter 18. Main concepts: cross-tabulation, chi-square, degrees of freedom.
Weeks 5: Dimension reduction
5.1 Index creation and testing
Reading: Chapter 17, section 17.8. Main concepts: Cronbach alpha, reliability with item deleted.
5.2 Factor analysis
Reading: Chapter 17. Main concepts: factors, factor scores, rotation.
Week 6: Linear Regression
Reading: Chapter 7
Week 7: Student Presentations + Report Due (0%)
Week 8: Midterm (30 mins - 0%) + Regression diagnostics
Reading: Chapter 7, section 7.7 onwards
Week 9: Logistic regression & other types of regression
Reading: Chapter 8. Optional Reading (other types of regression): Chapters 18 and 19.
Week 10: Mediation, moderation, and path analysis
Reading: Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173.
Week 11: Presenting results & writing a report
Reading: methods101.com
Week 12: Graphs with ggplot
Reading: methods101.com
Week 13: Student Presentations + Report Due (50%)
Week 14: Final exam (2 hours - 25%)