Simon Fraser University
Engaging the World

Course Outlines

Fall 2026 - STAT 201 D100

Statistics for the Life Sciences (3)

Class Number: 6067

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 9 – Dec 6, 2026: Tue, 1:30–2:20 p.m.
    Burnaby

    Sep 9 – Dec 6, 2026: Thu, 12:30–2:20 p.m.
    Burnaby

  • Prerequisites:

    Recommended: 30 units.

Description

CALENDAR DESCRIPTION:

Research methodology and associated statistical analysis techniques for students with training in the life sciences. Intended to be particularly accessible to students who are not specializing in Statistics. Students cannot obtain credit for STAT 201 if they already have credit for - or are taking concurrently - STAT 101, 203, 205, 285, or any upper division STAT course. Quantitative.

COURSE DETAILS:

This course may be applied to the Certificate in Liberal Arts

STAT Workshop Coordinator: Sonja Isberg

Outline:

Aimed at a non-mathematical audience, this course discusses procedures that are commonly used in the summary of data and in the interpretation of statistical studies. The course follows Chapters 0–27 of The Basic Practice of Statistics (9th Edition) by Moore, Notz, and Fligner, excluding Chapter 13. Chapters 7, 11, 19, and 24 are review chapters and may be used as supplementary material. The major topics are as follows:

  1. Descriptive Statistics for One Variable (Chapters 1–3)
    Graphical and numerical summaries of a single variable are introduced, including bar charts, pie charts, histograms, stem-and-leaf plots, measures of center and spread (mean, median, quartiles, standard deviation), and the Normal distribution.
  2. Descriptive Statistics for Two Variables (Chapters 4–6)
    Relationships between variables are explored using scatterplots, correlation, simple linear regression, two-way tables, and measures of association for categorical variables.
  3. Producing Data (Chapters 8–10)
    Methods for collecting data are discussed, including survey sampling, experimental design, and observational studies. Topics include simple random sampling, stratified and cluster sampling, randomization, treatments, controls, blocking, matching, and ethical issues in statistical investigations.
  4. Probability and Statistical Inference (Chapters 12, 14–18)
    Fundamental concepts of probability are introduced, including probability rules, probability distributions, the Binomial distribution, and sampling distributions. These concepts provide the foundation for statistical inference, including confidence intervals, hypothesis tests, p-values, statistical significance, and practical considerations in conducting and interpreting statistical analyses.
  5. Estimation and Testing for One-Sample Problems (Chapters 20 and 22)
    Confidence intervals and hypothesis tests for a single population mean and a single population proportion are presented, with emphasis on the use of statistical software and interpretation of results.
  6. Estimation and Testing for Two-Sample Problems (Chapters 21 and 23)
    Confidence intervals and hypothesis tests for comparing two population means and two population proportions are presented, with emphasis on the use of statistical software and interpretation of results.
  7. Chi-Square Procedures for Categorical Data (Chapter 25)
    Chi-square tests for goodness-of-fit, homogeneity, and independence are introduced. Contingency tables and measures of association for categorical variables are discussed, with emphasis on interpretation and software implementation.
  8. Regression and Analysis of Variance (Chapters 26 and 27)
    Statistical inference for simple linear regression is introduced, including confidence intervals and hypothesis tests for regression parameters. One-way analysis of variance is presented as a method for comparing several population means, with emphasis on software implementation and interpretation.

Grading

  • Midterm 1 20%
  • Midterm 2 20%
  • Midterm 3 20%
  • Final Comprehensive Exam 40%

NOTES:

Above grading is subject to change.

There will be no make-up midterms.

There will be no class Tuesday Oct 20.

Materials

MATERIALS + SUPPLIES:

R can be accessed via Jupyter, an online platform, at https://sfu.syzygy.ca/. Alternatively, R Studio and R statistical
software can be downloaded free of charge from https://posit.co/download/rstudio-desktop/ and https://cran.r-
project.org/, respectively

REQUIRED READING:

The Basic Practice of Statistics (9th ed.) by D. S. Moore, W. I. Notz, and M. A. Fligner. Publisher: W.H. Freeman Publishers

E-book available at SFU Bookstore.

Department Undergraduate Notes:

Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or caladmin@sfu.ca.  


Tutor Requests:
Students looking for a tutor should visit https://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

At SFU, you are expected to act honestly and responsibly in all your academic work. Cheating, plagiarism, or any other form of academic dishonesty harms your own learning, undermines the efforts of your classmates who pursue their studies honestly, and goes against the core values of the university.

To learn more about the academic disciplinary process and relevant academic supports, visit: 


RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.