# 140.622.02 STATISTICAL METHODS IN PUBLIC HEALTH II

Department:
Term: 2nd term
Credits: 4 credits
Course Instructors:
Description:

Presents use of likelihood functions, confidence intervals, and hypothesis tests to draw scientific inferences from public health data. Discusses null and alternative hypotheses, Type I and II errors, and power. Develops parametric and non-parametric statistical methods for comparing multiple groups (ANOVA). Also introduces measures of association and simple linear regression. Addresses methods for planning a study, including stratification, balance, sampling strategies, and sample size.

Old Learning Objective:

Students who successfully master this course will be able to: 1) Use statistical reasoning to formulate public health questions in quantitative terms [1.1 Distinguish the summary measures of association applicable to retrospective and prospective study designs; 1.2 Distinguish between the appropriate regression models for handling continuous outcomes, binary outcomes and time-to-events; 1.3 Conduct an intent-to-treat statistical analysis of data from a randomized community trial and correctly interpret the findings about the treatment efficacy; 1.4 Conduct a basic analysis of data from a cohort study and correctly interpret the findings about the association between exposure and outcome; 1.5 Conduct a basic analysis of data from a case-control study and correctly interpret the findings about exposure and outcome; 1.6 Use stratification in design and analysis to minimize confounding and identify effect modification]; 2)Design and interpret graphical and tabular displays of statistical information [2.1 Use the statistical analysis package Stata to construct statistical tables and graphs of journal quality]; 3) Use probability models to describe trends and random variation in public health data [3.1 Distinguish among the underlying probability distributions for modeling continuous, categorical, binary and time-to-event data; 3.2 Calculate the sample size necessary for estimating either a continuous or binary outcome in a single group; 3.3 Estimate the sample size necessary for determining a statistically significant difference in either a continuous or binary outcome between two groups; 3.4 Recognize the assumptions required in performing statistical tests assessing relationships between an outcome and a risk factor]; 4) Use statistical methods for inference, including confidence intervals and tests, to draw valid public health inferences from study data [4.1 Estimate two proportions and their difference, and confidence intervals for each. Interpret the interval estimates within a scientific context. Recognize the importance of other sources of uncertainty beyond those captured by the confidence interval; 4.2 Estimate an odds ratio or relative and its associated confidence interval. Explain the difference between the two and when each is appropriate; 4.3 Perform and interpret one-way analysis of variance to test for differences in means among three or more populations. Evaluate whether underlying probability model assumptions are appropriate; 4.4 Contrast mean outcomes among pairwise groups using multiple comparisons procedures; 4.5 Interpret the correlation coefficient as a measure of the strength of a linear association between a continuous response variable and a continuous predictor variable; 4.6 Perform and correctly interpret the results from a simple linear regression analysis to describe the dependence of a continuous response variable on a single predictor variable; 4.7 Use data transformations such as logs and square roots so that regression model assumptions are more nearly satisfied].

New Learning Objective(s):
Upon successfully completing this course, students will be able to:
Use statistical reasoning to formulate public health questions in quantitative terms [1.1 Distinguish the summary measures of association applicable to retrospective and prospective study designs; 1.2 Distinguish between the appropriate regression models
Design and interpret graphical and tabular displays of statistical information [2.1 Use the statistical analysis package Stata to construct statistical tables and graphs of journal quality];
Distinguish among the underlying probability distributions for modeling continuous, categorical, binary and time-to-event data; 3.2 Calculate the sample size necessary for estimating either a continuous or binary outcome in a single group; 3.3 Estimate the sample size necessary for determining a statistically significant difference in either a continuous or binary outcome between two groups; 3.4 Recognize the assumptions required in performing statistical tests assessing relationships between an outcome and a risk factor
Use statistical methods for inference, including confidence intervals and tests, to draw valid public health inferences from study data 4.1 Estimate two proportions and their difference, and confidence intervals for each. Interpret the interval estimates within a scientific context. Recognize the importance of other sources of uncertainty beyond those captured by the confidence interval; 4.2 Estimate an odds ratio or relative and its associated confidence interval. Explain the difference between the two and when each is appropriate; 4.3 Perform and interpret one-way analysis of variance to test for differences in means among three or more populations. Evaluate whether underlying probability model assumptions are appropriate; 4.4 Contrast mean outcomes among pairwise groups using multiple comparisons procedures; 4.5 Interpret the correlation coefficient as a measure of the strength of a linear association between a continuous response variable and a continuous predictor variable

Methods of Assessment: Student evaluation based on problem sets and exams.
Location: East Baltimore
Class Times:
• Tuesday 10:30 - 11:50
• Thursday 10:30 - 11:50
Lab Times:
• Monday 1:30 - 3:00
• Tuesday 1:30 - 3:00
• Wednesday 1:30 - 3:00
• Thursday 1:30 - 3:00
• Friday 1:30 - 3:00
• Monday 3:00 - 5:00
• Tuesday 3:00 - 5:00
• Wednesday 3:00 - 5:00
• Thursday 3:00 - 5:00
Enrollment Minimum: 10
Enrollment Restriction: For PhD, ScM and MHS degree candidates in departments to be determined
Instructor Consent: Consent required for some students

Consent required for non-PH students

For consent, contact: kbandeen@jhsph.edu
Prerequisite:

140.621

Auditors Allowed: Yes, with instructor consent