600.710.86
Statistical Concepts in Public Health 2
 Location:
 Internet
 Term:
 1st term
 Department:
 Online Programs for Applied Learning
 Credits:
 3 credits
 Academic Year:
 2021  2022
 Instruction Method:
 TBD
 Auditors Allowed:
 No
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructor:
 Contact:
 John McGready
 Resources:
 Prerequisite:
600.709.86 Statistical Concepts in Public Health 1
 Description:

Provides a broad overview of biostatistical methods and concepts used in the public health sciences, emphasizing interpretation and concepts rather than calculations or mathematical details. Develops ability to read the scientific literature to critically evaluate study designs and methods of data analysis. Introduces basic concepts of statistical inference, including hypothesis testing, pvalues, and confidence intervals. Topics include comparisons of means and proportions; the normal distribution; regression and correlation; confounding; concepts of study design, including randomization, sample size, and power considerations; logistic regression; and an overview of some methods in survival analysis. Draws examples of the use and abuse of statistical methods from the current biomedical literature.
 Learning Objectives:

Upon successfully completing this course, students will be able to:
 Interpret the results from simple linear regression to assess the magnitude and significance of the relationship between a continuous outcome variable and a binary, categorical or continuous predictor variable
 Assess the strength of a linear relationship between two continuous variables via the coefficient of determination (R squared) and/or its counterpart, the correlation coefficient
 Interpret the results from simple logistic regression to assess the magnitude and significance of the relationship between a binary outcome variable and a binary, categorical or continuous predictor variable
 Interpret the results from simple Cox regression to assess the magnitude and significance of the relationship between a time to event variable and a binary, categorical or continuous predictor variable
 Explain the assumption of proportional hazards, and what this means regarding the interpretation of hazard (incidence rate) ratios from Cox regression models
 Explain how most of the hypotheses tests covered in Statistical Reasoning 1 can be expressed as simple regression models
 Methods of Assessment:
Homework assignments: 50%, Quizzes: 30%, Final exam: 20%
 Enrollment Restriction:
Restricted to MAS in Patient Safety and Healthcare Quality students
 Instructor Consent:
No consent required