# 140.621.01Statistical Methods in Public Health I

Location:
East Baltimore
Term:
1st term
Department:
Biostatistics
Credits:
4 credits
2017 - 2018
Instruction Method:
TBD
Class Times:
• Tu Th,  10:30 - 11:50am
Lab Times:
• Monday,  1:30 - 3:00pm (01)
• Tuesday,  1:30 - 3:00pm (02)
• Wednesday,  1:30 - 3:00pm (03)
• Thursday,  1:30 - 3:00pm (04)
• Friday,  1:30 - 3:00pm (05)
• Monday,  3:30 - 5:00pm (06)
• Tuesday,  3:30 - 5:00pm (07)
• Wednesday,  3:30 - 5:00pm (08)
• Thursday,  3:30 - 5:00pm (09)
Auditors Allowed:
Yes, with instructor consent
Course Instructors:
Contact:
Marie Diener-West
Resources:
Description:

Introduces the basic concepts and methods of statistics as applied to diverse problems in public health and medicine. Demonstrates methods of exploring, organizing, and presenting data, and introduces fundamentals of probability, including probability distributions and conditional probability, with applications to 2x2 tables. Presents the foundations of statistical inference, including concepts of population, sample parameter, and estimate; and approaches to inferences using the likelihood function, confidence intervals, and hypothesis tests. Introduces and employs the statistical computing package, STATA, to manipulate data and prepare students for remaining course work in this sequence.

Learning Objectives:

Upon successfully completing this course, students will be able to:

1. Use statistical reasoning to formulate public health questions in quantitative terms within the scientific method.
2. Design and interpret graphical and tabular displays of statistical information, including stem and leaf plots, box plots, Q-Q plots and frequency tables.
3. Distinguish probability models (binomial, Poisson, and Gaussian) for describing trends and random variation in public health data.
4. Use stratification to eliminate the influence of a possible confounding variable in a study of the association between a risk factor and outcome.
5. Use bootstrapping to construct confidence intervals and interpret them in a scientific context.
6. Explain the implications of the Central Limit Theorem in determining the sampling distributions of sample statistics.
7. Use sampling distribution theory for a single sample mean, difference between two sample means, paired mean difference, single sample proportion, and difference between two sample proportions for statistical inference.
8. Employ statistical methods for inference, including tests and confidence intervals, to draw public health inferences from data.
9. Use the Stata statistical analysis package to construct tables and graphs and perform statistical methods for inference.
Methods of Assessment:

Student evaluation based on problem sets and exams.

Enrollment Restriction:

For MPH, DrPH, "special students" and MSPH degree candidates

Instructor Consent:

Consent required for some students

Consent Note:

Consent Required for non-PH students

For consent, contact: