Correlation

BEFORE YOU BEGIN:

The videos below will walk you through the following .Rmd file: https://drive.google.com/file/d/1bd5Ewr2q4e56oJHLbxVuG3yDKNQBO-x5/view?usp=sharing

Be sure you already have the datafile from Ch. 9 saved.

11–A: Correlation Review

If you need a refresher on the basic principles of correlation, please read over this statistics chapter from the PSYC200 Open Science textbook:

https://sites.google.com/umd.edu/statisticsinsocialsciences/07-correlation?authuser=0

11–B: Introduction and Learning Outcomes

In this module, we will be learning how to:

    1. Determine the appropriate correlation to run based upon our data.

    2. Conduct a Pearson's r correlation.

    3. Conduct a Spearman's rho correlation.

    4. Calculate R squared.

    5. Interpret the results of a correlation test.

    6. Depict the results of a correlation test visually.

Video (0:36)

11–C: Loading Packages and Dataset Information

Note that when working through the .Rmd files, R packages will often need to be installed, and libraries loaded. Do NOT quit R while installing or loading packages and libraries. This can corrupt crucial files. Instead, you can STOP the process (by clicking the red stop sign in the upper right corner of the console) and then quit the program, or wait until the process has been completed.

Video (6:10)

11–D: Pearson's r Correlation

Video (6:07)

11–E: Spearman's rho Correlation

Video (6:47)

11–F: Calculating R Squared

Video (4:00)

11–G: Depicting Correlation Visually

Video (7:27)

Rmd Analyses Template

If you would like to run Pearson's r correlational analyses in R you can use this Rmd template

https://drive.google.com/file/d/1BPkiJh8Fk6AeTJvmWF534h5WeVROyDJW/view?usp=sharing

If you would like to run Spearman's rho correlational analyses in R you can use this Rmd template

https://drive.google.com/file/d/1VR0gPxTDKNTRwue1BK2vg67L0AzI9UO7/view?usp=sharing

References

  1. Horst, A. Presenting Monster https://github.com/allisonhorst CC-BY-4.0

  2. R version 4.1.0 (2021-05-18) -- "Camp Pontanezen". Copyright (C) 2021 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit)

  3. RStudio Team (2020). RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.

  4. Tomlinson, T. Jones, B. and Chicoli, A.Statistics in Social Sciences https://sites.google.com/umd.edu/statisticsinsocialsciences

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