Academic Calendar 2024-2025

Search Results

Search Results for "HSCI 190"

HSCI 190  Introduction to Statistics for the Health Sciences  Units: 3.00  
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. To be successful in the course assessments, students will need to progressively build their skills and apply the course knowledge to 1) select appropriate statistical tests based on the research question and data, 2) interpret findings from descriptive and statistical analyses, and 3) communicate the results effectively.
NOTE Also offered online; consult the Bachelor of Health Sciences program office (Learning Hours may vary).
Requirements: Prerequisite Registration in a BHSc Program. Exclusion BIOL 243/3.0; CHEE 209/3.5; COMM 162/3.0; ECON 250/3.0; GPHY 247/3.0; KNPE 251/3.0; NURS 323/3.0; POLS 285/3.0; POLS 385/3.0*; PSYC 202/3.0; SOCY 211/3.0; STAM 200/3.0; STAT 263/3.0. One-Way Exclusion May not be taken with or after STAT 269/3.0.  
Offering Faculty: Faculty of Health Sciences  

Course Learning Outcomes:

  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.