Important Preliminary Review

Statistics background

This text assumes the reader has completed an introductory statistics course. For those needing a refresher, two links are provided below.

https://bookdown.org/chesterismay/rbasics/

http://moderndive.com/index.html

Software

The text utilizes the R computing system. The course, STA 363 - Introduction to Statistical Modeling, utilizes RStudio and Rmarkdown.

R is a free statistical software platform that can be easily downloaded from the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/

You can download RStudio from here: https://rstudio.com/products/rstudio/download/#download

Detailed instructions for installing R and RStudio can be found in this video: https://www.youtube.com/watch?v=d-u_7vdag-0

An overview of using R and RStudio can be found here: https://www.youtube.com/watch?v=lVKMsaWju8w&t=458s

Add-on packages

We will be using the following add-on packages in this textbook (note: additional packages may be used in the course).

• tidyverse (Wickham, 2017)
• knitr (Xie, 2019)
• kableExtra (Zhu, 2019)
• GGally (Schloerke et al., 2018)
• ggfortify (Horikoshi et al., 2019)
• gridExtra (Auguie, 2017)
• emmeans (Lenth, 2019)
• lindia (Lee et al., 2017)
• car (Fox et al., 2019)
• leaps (Lumley, 2017)
• caret (Jed Wing et al., 2019)

You can install all of these packages by following the directions here: https://www.youtube.com/watch?v=u1r5XTqrCTQ

Or by running the following command:

install.packages(c("tidyverse",
                   "knitr",
                   "kableExtra",
                   "GGally",
                   "ggfortify",
                   "gridExtra",
                   "emmeans",
                   "lindia",
                   "car",
                   "leaps",
                   "caret"))

IMPORTANT NOTE: If running on a Mac, when asked, “Do you want to install from source?” In general it is better to select “No.”

Help with RMarkdown

Throughout the STA 363 course, Rmarkdown is utilized. In fact, this textbook was written using RMarkdown. You can find a tutorial of RMarkdown here: https://www.youtube.com/watch?v=tKUufzpoHDE

RStudio provides tutorials as well: https://rmarkdown.rstudio.com/lesson-1.html

Managing your work in R

We recommend using ‘Projects’ in RStudio, which links all code and data to a folder in your computer: https://www.youtube.com/watch?v=pyJMWlDptYw

Better yet, create a Github account, and github repository to manage your code and analysis: https://www.youtube.com/watch?v=kL6L2MNqPHg&ab_channel=IDGTECHtalk

Data in this text

The data used in this text is available on the hosting website (https://github.com/tjfisher19/introStatModeling/tree/master/docs/data) and links are provided throughout the text. Alternatively, all data used in the text can be downloaded as a single zip file: zipFileLinkHere

References

Auguie, B., gridExtra: Miscellaneous Functions for "Grid" Graphics, from https://CRAN.R-project.org/package=gridExtra, 2017.

Fox, J., Weisberg, S. and Price, B., Car: Companion to Applied Regression, from https://CRAN.R-project.org/package=car, 2019.

Horikoshi, M. and Tang, Y., Ggfortify: Data Visualization Tools for Statistical Analysis Results, from https://CRAN.R-project.org/package=ggfortify, 2019.

Jed Wing, M. Kuhn. C. from, Weston, S., Williams, A., Keefer, C., Engelhardt, A., Cooper, T., Mayer, Z., et al., Caret: Classification and Regression Training, from https://CRAN.R-project.org/package=caret, 2019.

Lee, Y. Y. and Ventura, S., Lindia: Automated Linear Regression Diagnostic, from https://CRAN.R-project.org/package=lindia, 2017.

Lenth, R., Emmeans: Estimated Marginal Means, Aka Least-Squares Means, from https://CRAN.R-project.org/package=emmeans, 2019.

Lumley, T., Leaps: Regression Subset Selection, from https://CRAN.R-project.org/package=leaps, 2017.

Schloerke, B., Crowley, J., Cook, D., Briatte, F., Marbach, M., Thoen, E., Elberg, A. and Larmarange, J., GGally: Extension to ’Ggplot2’, from https://CRAN.R-project.org/package=GGally, 2018.

Wickham, H., Tidyverse: Easily Install and Load the ’Tidyverse’, from https://CRAN.R-project.org/package=tidyverse, 2017.

Xie, Y., Knitr: A General-Purpose Package for Dynamic Report Generation in r, from https://CRAN.R-project.org/package=knitr, 2019.

Zhu, H., kableExtra: Construct Complex Table with ’Kable’ and Pipe Syntax, from https://CRAN.R-project.org/package=kableExtra, 2019.