Statistics for Life Sciences

Course Notes for ST231, Updated for Winter 2024

Author

Dr. Devan Becker

Published

2023-06-20

Introduction

These course notes are self-contained and provided as an Open Educational Resources. In doing so, I will also borrow from OpenIntro Statistics for the Biomedical and Life Sciences, with attribution. As such, these resources have the same license (see the end of this page), except for those elements that are still present from Baldi & Moore (mainly exercises, which are being removed as I go).

Alternate Textbooks for Extra Instruction

  • These course notes structured to coincide with Baldi and Moore’s The Basic Practice of Statistics in the Life Sciences, 4th edition. However, I have made them self-contained in order to provide these notes as an Open Educational Resources.

Learning Outcomes

  • Critically appraise published articles in health sciences research.
  • Use industry standard tools to apply basic statistical concepts to real-world problems.
  • Understand the use and application of statistical techniques such as descriptive and inferential statistics.

Accessing Materials

  • Lectures posted on MyLS
  • rdrr.io allows running single R commands to caclulate probabilities
  • RStudio
    • Free, open-source interface to the R programming language.
    • A free online cloud version is available - no need to install R on your own computer!
  • Syzygy Jupyter Notebooks
    • Free, web-based service for WLU students
    • No need to install R on your own computer!

You can use either RStudio or Syzygy for this course, RStudio has many fantastic bells and whistles that help you produce results and reports, whereas Syzygy has an online interface and makes it easy to use without installing R on your own computer. Note that Syzygy uses “notebooks” rather than the RMarkdown notebooks that RStudio prefers. L1abs will use RStudio.

For lectures, I will be using VSCode, which I use because it works well with python and R as well as other languages that I need. I will switch to RStudio for many demonstrations just to show you how it works because this is the program that most people who do statistics will use. I will occasionally demonstrate some concepts using Jupyter notebooks because this is another common way that people do statistics and data science. You will not be tested on the features of Rtudio, VSCode or Jupyter notebooks, but mastery of RStudio will be extremely helpful for all future data analysis tasks beyond this course.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 Unported License.