Stat 305 syllabus

Applied Statistics for Health Sciences
Course description: An introduction to statistical reasoning and data analysis for the health sciences. Coverage includes descriptive statistics, methods of data collection, estimation, hypothesis testing, non-parametric statistics, ANOVA, repeated measures, correlation and other measures of association, modeling data with linear and logistic regression. Critique of selected research articles and case studies incorporating research and evidence-based practice will be adopted to connect statistics to daily work in healthcare field. Statistical computer software (e.g. Minitab) will be extensively used for data analysis. Computer Lab fee. Note: This course is offered only as a fully online course and only for health sciences students.

Prerequisite: MA 110 Minimum Grade of C or MA 112 Minimum Grade of C.

Suggested Textbook: Biostatistics for the Biological and Health Sciences by Triola, Triola and Roy, Second Edition, Pearson


Learning outcomes: Upon the successful completion of the course a student will:

know basic concepts of probability, discrete and continuous distributions, descriptive and inferential statistics, ANOVA and regression analysis
know standard methods of data analysis using appropriate software
apply statistical data analysis methods in health science data