Undergraduate Courses

PUBHLTH 223: Introduction to Biostatistics

[3 credits, Fall and Spring]

Prerequisites: None

Description: This introductory course is designed to give students the basic skills to organize and summarize data, along with an introduction to the fundamental principles of statistical inference. The course emphasizes an understanding of statistical concepts and interpretation of numeric data summaries along with basic analysis methods, using examples and exercises from medical and public health studies. The course does not require a high-level mathematics background, and will highlight the use and integration of statistical software, spreadsheets and word processing software in conducting and presenting data summaries and analyses.

Textbook: OpenIntro Statistics

Software: R/Stata

PUBHLTH 490ST: Telling stories with data: statistics, modeling, and visualization

[3 credits, Fall]

Prerequisites: One of any of the following introductory stats courses taught at UMass: PUBHLTH 223, STAT 240, STAT 501, ResEcon 212, PSYCH 240. If you have not taken an intro stats course at UMass but still want to enroll in this course, you are encouraged to petition the instructor for permission, especially if any of the following apply: (a) you have taken AP Stats in high school, (b) you have taken a college-level intro stats course just one of the ones listed above, or (c) you are confident in your quantitative skills and your ability to succeed in a fast-paced, advanced introductory course.

Description: The aim of this course is to provide students with the skills necessary to tell interesting and useful stories in real-world encounters with data. Students will learn fundamental concepts and tools relevant to the practice of summarizing, visualizing, modeling, and analyzing data. Students will learn how to build statistical models that can be used to describe multidimensional relationships that exist in the real world. Specific methods covered will include linear, logistic, and Poisson regression. This course will introduce students to the R statistical computing language and by the end of the course will require substantial independent programming. To the extent possible, the course will draw on real datasets from biological and biomedical applications. This course is designed for students who are looking for a second course in applied statistics/biostatistics (e.g. beyond PUBHLTH 223 or STAT 240), or an accelerated introduction to statistics and modern statistical computing.

Textbook: Daniel Kaplan, Statistical Modeling: A Fresh Approach.

Software: R

PUBHLTH 497P: Tossing dice and spinning news : Making sense of public health media reports

[3 credits, Spring]

Prerequisites: PUBHLTH 223 (Intro to Biostatistics) and PUBHLTH 324 (Intro to Epidemiology).

Description: Students will learn to apply the fundamental concepts learned in PUBHLTH 223 or other Introductory biostatistics courses and PUBHLTH 324 or other introductory epidemiology course to critique articles, identify key issues with results that are  (in)accurately presented by the media to the general public. This course will primarily focus on understanding and interpreting published study results and will not involve conducting extensive statistical analyses.

Textbook: none

Software: none