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Thompson Rivers University
Thompson Rivers University

BIOL 4001: Biostatistics

This course explores the nature of data and the challenges involved in collecting and handling it, this includes planning the collection of data necessary to examine a particular problem, manipulation of data, summarizing and describing a data set. It also covers the statistical approach for testing hypotheses, and performing data analysis using current statistical tools as a tool for description and hypotheses testing. Students will also interpret and evaluate statistical analyses used by others, design experiments, and analyze and interpret the results of experiments or observational studies.

Learning outcomes

  • Identify statistical analyses necessary for successful research in biology
  • Interpret descriptive statistics in the context of biological data.
  • Use methods of inferential statistics to draw conclusions about biological phenomena.
  • Describe the purpose of statistical analysis and the scientific method to study biology.
  • Carry out data collection, construct hypotheses, analyze data, and apply statistical methods.
  • Explain principles of good study design in the collection of data.
  • Construct testable hypotheses to answer questions of interest.
  • Analyze data to provide numerical and graphical data summaries.
  • Apply statistical methods to make inferences about questions of interest.
  • Use the R software environment for statistical analysis of data.
  • Critically evaluate scientific studies based on their study design and statistical analyses.
  • Communicate the purpose and methods of inferential statistics to audiences familiar with basic science.

Course topics

  • Course Introduction
  • Displaying and Describing Data
  • Statistical Inference
  • Proportions, Frequencies, and Contingency Analysis
  • Inference for One or Two Groups
  • Data Transformations and Nonparametric Methods
  • Designing Effective Experiments
  • Inference for More than Two Groups
  • Correlation and Regression
  • Multiple Factors and Meta-Analysis
  • Computer-Intensive Methods and Survival Analysis
  • Multivariate Methods

Required text and materials

The following textbook is required for this course:

  1. Whitlock MC, Schluter D. 2020. The analysis of biological data, 3rd edition. W. H. Freeman.
    Type: Textbook ISBN: 978-1-319-22623-7

Additional requirements

  • R Statistical Software and RStudio. Details on how to install and download can be found within the course after registration.


To complete this course successfully, students must achieve a passing grade of 50% or higher on the course overall and 50% or higher on the mandatory Final Project.

Assignment 1: Lessons 1-3 8%
Quiz 1: R Tutorials 1-3 8%
Assignment 2: Lessons 4-6 8%
Quiz 2: R Tutorials 4-6 8%
Assignment 3: Lessons 7-9 8%
Quiz 3: R Tutorials 7-9 8%
Assignment 4: Lessons 10-12 8%
Quiz 4: R Tutorials 10-12 8%
Final Project (mandatory) 36%

Open Learning Faculty Member Information

An Open Learning Faculty Member is available to assist students. Students will receive the necessary contact information at the start of the course.

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