STAT 485: Intermediate Topics in R Statistical Language

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course overview

Since its release in 1997, R has emerged as a popular tool for statistical analysis and research. The flexibility and extensibility of R are keys attributes that have driven its adoption. Some of the advantages of R are related to the command line interface (CLI) form in which it is used. However, this does add to the challenge of learning to use R. The goal of this course is to build upon the knowledge and experience gained in STAT 484. Specifically:

  1. Become familiar with using R for common statistical analyses
  2. Learn how to use R graphics to develop sophisticated figures
  3. Explore simple programming in R
  4. Develop good analytical practices including documenting analysis and data manipulation, and collaborating with others in the R user/learner community


Here is a link to the Online Notes for STAT 485.

course topics

Course topics include:

  • Linear models – regression
  • Linear models – ANOVA I
  • Linear models – ANOVA II - multiple way ANOVA
  • Managing Projects and Producing Reports
  • Visualizing Data I - enhancing scatter plots
  • Visualizing Data II - errorbars and polygonsVisualizing Data II - enhancing barplots and and boxplots
  • Mixed effects models - introduce lme(), lmer()
  • Fitting other models. Non-linear least squared models, logistic regession
  • Writing functions


 Familiarity with basic statistics is assumed.


Text: We will make extensive use of Essential R – the course notes for this class. You should download it and will probably find it useful to print it. You may also want to download additional resources in the compressed folder Essential

 Other Books and Resources on R:

Statistics: An introduction using R. 2005. Michael J. Crawley. Wiley and Sons. (This was useful enough to me when I began learning R that I bought a copy.).

Using R for Introductory Statistics. 2004. John Verzani. Chapman & Hall/CRC. (An extension of SimpleR) If I was going to require a text, this would be it.


  • Access to your own copy of R. Please make sure that you visit Statistical Software page for the latest information about R.
  • RStudio is a very nice platform for using R that will run on Windows, Mac, and Linux. R studio adds many useful features to simplify using R. All the functions used in this class can be performed without RStudio, but I will be demonstrating their use within RStudio.

assessment plan

Grades will be based on three components: weekly exercises (36%), participation (20%) and a project of your choosing (44%).

Exercises will be graded with an emphasis on completeness rather than correctness - the point is to do them so you actually use R.  Participation includes both in class and on-line participation, which will be through forums and a wiki on Canvas; I will count posting questions, tips, and helping others out as participation.  The project should consist of an analysis or publication quality graphic based on data of your choosing. Ideally, you have data you want to analyze or present, so this should be useful to you.

academic integrity

All Penn State policies regarding ethics and honorable behavior apply to this course. Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students.

For any material or ideas obtained from other sources, such as the text or things you see on the web, in the library, etc., a source reference must be given. Direct quotes from any source must be identified as such.

All exam answers must be your own, and you must not provide any assistance to other students during exams. Any instances of academic dishonesty WILL be pursued under the University and Eberly College of Science regulations concerning academic integrity. For more information on academic integrity, see Penn State's statement on plagiarism and academic dishonesty.

The Eberly College of Science Code of Mutual Respect and Cooperation embodies the values that we hope our faculty, staff, and students possess and will endorse to make The Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded.


Penn State welcomes students with disabilities into the University's educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact the Office for Disability Services (ODS) at 814-863-1807 (V/TTY). For further information regarding ODS, please visit the Office for Disability Services Web site at

In order to receive consideration for course accommodations, you must contact ODS and provide documentation (see the documentation guidelines at If the documentation supports the need for academic adjustments, ODS will provide a letter identifying appropriate academic adjustments. Please share this letter and discuss the adjustments with your instructor as early in the course as possible. You must contact ODS and request academic adjustment letters at the beginning of each semester.

course author

Dr. Eric Nord is the primary author of the materials for this course.