Welcome to our class website. We will use this site in conjunction with I-learn 3.0 to supply material for the class. This is my second year of teaching at BYU-I and my first time teaching this specific course at BYU-I. I love applied statistics and the analytical advantages that come from knowing R. I look forward to learning with you this semester.

Applied Statistics

Over the last decade, I have spent much of my time working with very smart people that did not have a statistical analysis background. During that time I learned how vital it was to learn how others used language to convey topics. We all spoke English, but we had learned very specific definitions in our domains that were different than the general language definition. At times, each domain’s specific definition was very different from each other.

I hope that this class will firm up statistical language and introduce you to applied statistical analysis. Hopefully, I can help empower you to understand the implications of variability in all aspects of our lives.

Course Overview

General Course Goal

Help data-driven students to

  • use statistics as a bridge between imprecise measurements of, or knowledge about, a system and the truths of the system (ALT Writing: understand the principles of data analysis and decision making when uncertainty exists),
  • understand how to communicate/interact with statisticians and use statistical software when working in teams.

Course Outcomes

Students will

  1. learn to use R and R Studio as a tool for statistical analysis.
  2. be able to perform z-tests, t-tests, and chi-squared tests as well as their nonparametric equivalents.
  3. be able to use ANOVA with one or more factors.
  4. be able to apply simple and multiple linear regression.
  5. be able to apply simple and multiple logistic regression.

Course Materials

  • Text: R-Markdown notes from your Instructor.
  • Software: R and RStudio
  • Access to (and frequent use of) I-Learn, campus email, and a laptop.
  • A dedicated “Math 325 Notebook” folder on your computer.

Please read the syllabus and review the material on R Analysis Languange. You can also find an example of the beginning textbook that you will build throughout the semester. We will use our textbook download page to get the material for each week.