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Introduction to Statistics for the Health Sciences

HSCI 190 Introduction to Statistics for the Health Sciences

 Fall 2023 (Blended), Winter 2024 (Online)
 Year 1 Core Course
 10-11 hours/week
 3 units
On-Campus Course
Online Course

This course is designed to introduce students to basic statistical concepts and techniques and provide them with practical skills for applying statistics to health sciences research. This includes data visualization, probability distributions, descriptive statistics, hypothesis testing, and parameter estimation. Specific techniques such as t-tests, correlations, analysis of variance, and regression analyses will also be covered. Throughout the course, real data will be used to guide learning. Students will also discuss and practice how to effectively interpret and report statistical findings within the health sciences.


Not open to students in the Faculty of Arts and Science.

STAM 200/3.0, BIOL 243/3.0, GPHY 247/3.0, KNPE 251/3.0, NURS 323/3.0, POLS 385/3.0, PSYC 202/3.0, STAT 263/3.0.

This course will be delivered online and in a blended format.

After completing HSCI 190, students will be able to:

  1. Describe data using appropriate descriptive statistics and data visualization techniques to effectively communicate results of a study.
  2. Explain how study design can inform or limit statistical testing and data interpretation.
  3. Explain the assumptions of the statistical tests covered in this course and use that information to select the most appropriate statistical test for a given research question and data set.
  4. Interpret findings from the statistical analyses covered in this course and communicate the implications of the results effectively.
  1. Advocate (Assessment 3)
  2. Leader (Assessment 3)
  3. Collaborator (Assessment 3)
  4. Professional (Assessment 3)
  5. Communicator (Assessments 1-5)
  6. Scholar (Assessments 1-5)
  7. Content Expert (Assessments 1-5)

Assessment 1 – Module Quizzes (12%)

There will be 6 quizzes throughout the semester– one quiz at the end of each module. Each quiz is worth 2% to represent a total of 12% of the final grade.

Assessment 2 – Module Homework (18%)

In each module, students will be presented with a series of homework questions. Students must submit their responses prior to their module tutorial. The homework questions will be reviewed as a group during tutorials; students will then have the chance to update their homework and resubmit. The homework for each module will be worth 3%.

Assessment 3 - Observing & Summarizing Data from the World Around Us (15%)

In this assignment, students will be asked to create a data set based on their observations of a real-life phenomenon. Some examples include minutes played by each athlete during a sports game, age of Canadian astronauts, weights of food in your house, daily temperatures over a certain period, etc. Students will conduct descriptive statistics and visualize their data set using a contemporary statistical software. Students will write a 1-2 page summary of their data collection, statistical methods, and findings. Students should include all statistical output as an appendix. 

Assessment 5 – Interpreting Data Written Assignment (25%)

In this assignment, students will be provided with four data sets from health sciences research. For each data set, students will conduct descriptive statistics, visualize the data, select, and run the appropriate statistical test using a contemporary statistical software. Students will provide a 4-6 page summary of their rationale for selecting that statistical test, their statistical methods, findings, and their interpretation of the results for each data set. Students should include all statistical output as an appendix to the written report. 

Assessment 6 - Final Exam (30%)

The final examination will consist of multiple-choice and short-answer questions, addressing all topics covered in this course. 

Students can expect to spend on average 10 hours a week in the modules, weekly homework questions, assignments, and studying.

HSCI 190 course material includes assignment descriptions, select journal articles, data files, and modules that will be posted to or linked within the indicated LMS. In addition to the course material, students will be required to access a contemporary statistical software (e.g. SPSS, PRISM, etc.) to complete their homework and assignments. The instructor will inform students of the selected statistical software.