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Statistics for Experimental Research
Graduate Program (& Advanced Certificate) Status
Course Description

This course will cover the basic topics of Experimental Statistics and Research Methods for Behavioral Sciences. It will consist of two parts, frequentist and Bayesian statistics. The frequentist part comprises the subjects of scales, descriptive statistics, frequentist inferential statistics including independent and repeated measure t-tests, one- and twoway ANOVAs, effect sizes, correlational and regression analysis, and selected nonparametric methods. In the second part, the basics of Bayesian statistics will be introduced and contrasted with frequentist statistics. The course will also survey the good practices of designing, conducting, analyzing, interpreting, and communicating scientific psychological research. Students will use SPSS, R, Python or other programs in their assignments for statistical analysis.

Learning Outcomes
  • Being able to plan and design an experimental study 
  • Understanding why and when you need frequentist or Bayesian statistics 
  • Knowing enough to evaluate appropriateness of use of statistics in Results sections of research papers 
  • Being able to select and perform correct statistics for your own data
Assessment

The final grade will be determined roughly by the following weighting: 

  • Exam (to be conducted on the week following the end semester): 75% 
  • Assigned study reports, class activity: 25%

Required Materials:

  • Gravetter, F. J., & Wallnau, L. B. (2009). Statistics for the Behavioral Sciences (8th ed.). Belmont: Wadsworth. (G&W) 
  • Provided pdfs
Course Level
Doctoral
Academic Year
2023-2024
Term
Winter
US Credits
2
ECTS Credits
4
Course Code
CDCR6053