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# 140.611.01 STATISTICAL REASONING IN PUBLIC HEALTH I

Department:
Term: 1st term
Credits: 3 credits
Contact: John McGready
Academic Year: 2014 - 2015
Course Instructor:
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, p-values, 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 Objective(s):
Upon successfully completing this course, students will be able to:
Provide examples of different types of data arising in public health studies
Explain the basic differences between different study designs for comparing populations and recognize the issue of confounding when interpreting results from non-randomized studies
Interpret differences in data distributions via visual displays
Explain the difference between a sample and a population
Calculate standard normal scores and resulting probabilities
Calculate and interpret confidence intervals for population means and proportions and incident rates using data from single samples
Compute the mean difference and explain why a mean difference can be used to quantify differences in a continuous measure between two samples (and ultimately two populations)
Compute risk differences, relative risks and odds ratio, and interpret the quantities
Compute incidence rates and incidence rate ratios
Construct, and interpret, Kaplan-Meier estimates of the survival function that describes the "survival experience" of a cohort of subjects
Explain and unify the concept of a confidence interval whether it be for a single population quantity, or a comparison of populations
Compute confidence intervals for population mean differences, difference in proportions, relative risks, odds ratios and incidence rate ratios
Explain why computations for ratios are performed on the (natural) log scale
Perform hypothesis tests for populations comparisons: - Interpret p-values from t-tests and analysis of variance (ANOVA) for mean differences between populations - Interpret p-values from z-tests, chi-square tests and Fisherâ€™s Exact test for comparing proportions between populations - Interpret p-values from z-tests, and log-rank tests for comparing time-to-event outcomes between populations
Explain the role of sample size in determining margin of error (confidence interval width) and compute the necessary sample size(s) to obtain a desired margin of error

Methods of Assessment: Homework Assignments and Quizzes
Location: East Baltimore
Class Times:
• Tuesday 10:30 - 11:50
• Thursday 10:30 - 11:50
Enrollment Minimum: 9
Enrollment Restriction: Limited to degree candidates in SPH and students in the joint MSN/MPH program
Instructor Consent: No consent required
Auditors Allowed: Yes, with instructor consent
Grading Restriction: Letter Grade or Pass/Fail
Special Comments: Course materials fee is \$30.00.