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The rcmdr guide A Guide to Data Analysis in R Commander Viann Nguyen-Feng M A Mark A Stellmack Ph D University of Minnesota Copyright ? by Viann Nguyen-Feng and Mark A Stellmack CAbout the authors Viann Nguyen-Feng received her M P H from Eastern Virginia

A Guide to Data Analysis in R Commander Viann Nguyen-Feng M A Mark A Stellmack Ph D University of Minnesota Copyright ? by Viann Nguyen-Feng and Mark A Stellmack CAbout the authors Viann Nguyen-Feng received her M P H from Eastern Virginia Medical School after which she completed a post-graduate epidemiology fellowship and then a M A at the University of Minnesota She is currently pursuing a Ph D at the University of Minnesota Mark A Stellmack received his Ph D in Experimental Psychology from Loyola University of Chicago specializing in the study of auditory perception He teaches undergraduate statistics and research methods courses at the University of Minnesota Please contact the authors with questions comments and suggestions Viann Nguyen-Feng nguy umn edu Mark Stellmack stell umn edu CA Guide to Data Analysis in R Commander Table of Contents The Purpose of this Guide Installing R RStudio and Rcmdr Running R Commander Initial data entry Saving a Comma Separated Variable CSV spreadsheet in Excel Opening a Comma Separated Variable CSV spreadsheet in Rcmdr Viewing a data set Editing a data set Switching between multiple data sets Saving and loading a data set BASIC ANALYSES Descriptive statistics Mean standard deviation standard error of mean interquartile range coe ?cient of variation skewness kurtosis quantiles Correlations Correlation matrix Two-sample t-tests Between-groups Independent-groups t-test Within-groups Repeated-measures Correlated-groups Paired t-test One-Way Analysis of Variance ANOVA and Post-Hoc Tests Two-Way Analysis of Variance ANOVA Testing main e ?ects and interactions with multi-way ANOVAs Graphing interactions with multi-way ANOVAs Linear regression Chi-square Chi-square using raw data Chi-square using frequency counts ADVANCED ANALYSES Descriptive statistics for sub-groups Correlation test Testing the signi ?cance of correlations Graphs Scatterplot Scatterplot by groups CLine graph Bar graph Miscellaneous Opening and Entering data Opening an Excel spreadsheet Entering data directly into Rcmdr Recoding variables Combining items Converting variables from numeric to factor items Coding in R Deleting data sets Labeling points in a scatterplot Repeated-measures ANOVA Mixed-method ANOVA Updates Updating packages RStudio updates CThe Purpose of this Guide Our background is in Psychology We teach introductory statistics and research methods courses which are typically required for most Psychology majors Our statistics course teaches the basics of descriptive and inferential statistics and our students perform computations by hand In our research methods course students learn to perform the same statistical analyses on a computer In the past we used a popular software package for which our university purchased a sitelicense and which ran on university-owned computers However the software is prohibitively expensive to students As a result students were able to use the software only on university computers during times when the computers were available We sought an alternative software package that worked like the more expensive option but that was more a ?ordable and that students could use anytime on their own computers That led us to the R programming language R is a free powerful data-analysis program that performs many complex statistical analyses but using R requires one to learn the