HSCI 190 Introduction to Statistics for the Health Sciences
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.
BHSc On-Campus & BISC Students: This course is taken as a core course towards you Bachelor of Health Sciences degree and is offered in the blended on-campus format.
BHSc Online Students: You will be able to enroll in HSCI 190 during the Spring/Summer 2021 term when it will be offered in the fully online format for the first time. The online offering of Introduction to Statistics for Winter 2021 can be found with the course code STAM 200.
May not be taken with or after 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:
- Describe data using appropriate descriptive statistics and data visualization techniques.
- Understand and explain how study design can inform or limit statistical testing and data interpretation.
- Explain the assumptions of the statistical tests covered in this course and select the most appropriate statistical test for a given research question and data set.
- Interpret findings from the statistical analyses covered in this course and communicate the implications of the results effectively.
- Advocate (Assessment 3)
- Leader (Assessment 3)
- Collaborator (Assessment 3)
- Professional (Assessment 3)
- Communicator (Assessments 1-5)
- Scholar (Assessments 1-5)
- Content Expert (Assessments 1-5)
Assessment 1 – Module Quizzes (3% each for a total of 18%)
Students will complete a quiz at the end of each module.
Assessment 2 –Assignment #1 (12%)
In this assignment, students will be asked to create a data set based on their observations of a real-life phenomenon. Students will conduct descriptive statistics and visualize their data set using a contemporary statistical software. Students will write a summary of their data collection, statistical methods, and findings. Students should include all statistical output as an appendix.
Assessment 3 –Assignment #2 (15%)
Working in groups, students will discuss the data they collected in the first assignment. Students will brainstorm research questions based off their observations and select one to work on as a group. Each group will design a study to address their research question. Groups will be asked to consider how their study design may influence, or be influenced by, concepts covered in Modules 1 & 2 (e.g. variance, sample size, power, etc.). Each student will submit a 250-word description of their research question and design considerations. Students will be assessed on their group participation and written submission.
Assessment 4 – Assignment #3 (25%)
In this assignment, students will be provided with 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 summary of their rationale for selecting that statistical test, their statistical findings, and their interpretation of the results for each data set. Students should include all statistical output as an appendix.
Assessment 5 - 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.