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This repository contains the content for an undergraduate-level lab on computational statistics using the R programming language.

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PSYC278-Lab: Computational Statistics with R

Preamble

PSYC278, or The Analysis of Behavioral and Neuroscientific Data, is an undergraduate statistics course offered at the University of British Columbia. It is intended for students enrolled in the neuroscience program who are interested in specializing in cognitive and behavioural neuroscience. I have worked as a lab instructor for the course each year since 2020. The laboratory component of the course formerly involved a group research project requiring students to re-analyze the data from an existing study. Owing to considerable overlap with the lab component of PSYC277, in 2021 I spearheaded the lab's transformation into a tutorial focusing on computational statistics using R. Ke Zhang (PhD, UBC) and I developed the content using RMarkdown and TeX. This content frequently references material presented in the course textbook:

Pagano, R. R. (2013). Understanding Statistics in the Behavioral Sciences (10th ed.). Belmont, CA: Cengage Learning.

Cotents

Altogether there are eight modules. For each module, both the source material (RMarkdown + Figures) and rendered PDFs have been made available.

  • Lab 01, Foundations of R
  • Lab 02, Frequency Distributions
  • Lab 03, The Normal Distribution & Z-Scores
  • Lab 04, Correlation & Regression (Univariate)
  • Lab 05, Hypothesis Testing & Power
  • Lab 06, Sampling Distributions & Z-Tests
  • Lab 07, T-tests
  • Lab 08, Analysis of Variance

The 'take-home' exams from the '22 and '23 spring semesters are available in the 'Final-Assignment' folder.

Detailed Note on Contributions

I developed the modules for Lab 01 (R Foundations), Lab 02 (Frequency Distributions), Lab 04 (Correlation and Regression), Lab 06 (Sampling Distributions), and Lab 08 (Analysis of Variance). Ke Zhang provided invaluable comments and feedback.

Ke Zhang developed the modules for Lab 03 (Z-Scores and the Normal Distribution), Lab 05 (Hypothesis Testing and Power) and Lab 07 (T-Tests). Since their initial inception, I have refined and added to this content. Nevertheless, Ke remains rightfully credited as their principle author.

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This repository contains the content for an undergraduate-level lab on computational statistics using the R programming language.

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