Public Health, Biostatistics (PHST)

Subject-area course lists indicate courses currently active for offering at the University of Louisville. Not all courses are scheduled in any given academic term. For class offerings in a specific semester, refer to the Schedule of Classes.

500-level courses generally are included in both the undergraduate- and graduate-level course listings; however, specific course/section offerings may vary between semesters. Students are responsible for ensuring that they enroll in courses that are applicable to their particular academic programs.

Course Fees

Some courses may carry fees beyond the standard tuition costs to cover additional support or materials. Program-, subject- and course-specific fee information can be found on the Office of the Bursar website.


PHST 301. Quantitative Methods in Public Health3 Units

Term Typically Offered: Fall, Spring

Prerequisite(s): MATH 111 or Global Health minor.

Description: The course is an introduction to the concepts and theory behind quantitative analysis methods used in public health. The content focuses on how and why different statistical methods are used with minimal emphasis on statistical calculations. The skills of critical thinking, communication, and teamwork are promoted and cultivated throughout this course.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 302. Intermediate Statistical Analysis3 Units

Term Typically Offered: Spring Only

Prerequisite(s): PHST 301, or equivalent introductory statistics course including MATH 109, SOC 301, PSYC 301, PAS 408 etc.

Description: This course is an intermediate level applied statistics course covering key aspects of data exploration, visualization, and traditional topics in statistical inference, this course will utilize the statisical package SPSS, with a focus on understanding how to use and interpret SPSS output. This course is intended to give students familiarity with statistical tools used to analyze data in a variety of disciples - including economics, marketing, management, education, sociology, psychology, neuroscience, biology, mathematics, physics, environmental science, engineering, computer science, finance, health services administration, and public health - to be better prepared to pose relevant statistical questions, apply appropriate statistical techniques, and effectively interpret and communicate results.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 310. Applied Statistical Regression Models3 Units

Term Typically Offered: Fall Only

Prerequisite(s): PHST 302.

Description: This is the first course of statistical regression models in public health practice. The covered topics are: normal distribution, t-distribution, hypothesis testing, inference for two or more population means, one-way and two-way analysis of variance (ANOVA), linear regression with one or more independent variables, inferential and diagnostic methods in regression and correlation, multiple regression analysis; model building in regression; factorial experiments, and design of experiments. When relevant, examples related to population health issues are utilized.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 315. Sports Statistics3 Units

Term Typically Offered: Summer Only

Prerequisite(s): PHST 301 or equivalent (MATH 109, SOC 301, PYSC 301, and PAS 408) and MATH 111.

Description: Sabermetrics and "moneyball" have highlighted the use of statistics and mathematics in making sports decisions. In this course, we will consider how to use statistical tools to approach a variety of questions in traditional sports including baseball, football, and basketball. We will use methods from statistics such as probability, correlation, regression, and expected values to make predictions and compare game strategies. We will discuss the mathematics of several common approaches for evaluating players and teams.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 421. Statistical Computing in R3 Units

Term Typically Offered: Spring Only

Prerequisite(s): PHST 302.

Description: This course introduces students to the software R for statistical analysis. The R language provides a rich environment for statistical modeling and computing. The course emphasis is on practical issues in statistical computing which includes the basic syntax of R, programming in R, inputting and outputting (I/O) data in R, writing R functions, debugging, profiling R code, generating R packages, and running basic statistical analysis with R.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 431. The Principles of Statistical Learning3 Units

Term Typically Offered: Spring Only

Prerequisite(s): PHST 301, or equivalent (MATH 109, SOC 301, PSYC 301, and PAS 408).

Description: This introductory course gives an overview of many concepts, techniques, and algorithms in Statistical learning, including the topics related to regression, classification, dimension reduction. The course will give the student the basic ideas and intuition behind modern statistical learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 440. Statisitical Study Design and Research Methods3 Units

Term Typically Offered: Fall Only

Prerequisite(s): PHST 302.

Description: This course introduces multiple designs of studies that are commonly used in various disciplines, such as the clinical trails in pharmaceutical studies, the case-control study and cohort study in observational research methods. The research methods associated with those designs will also he discussed. In addition, this course will review some of the fundamental concepts and basic methods in survival analysis.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 500. Introduction to Biostatistics for Health Sciences I3 Units

Term Typically Offered: Fall Only

Prerequisite(s): Enrolled as a student in the PH MPH, MSc or Certificate in Clinical Investigation Sciences program.

Description: An introduction to descriptive and inferential statistical methods, including descriptive and graphical methods, estimation, calculation of confidence intervals, and 1- and 2-sample hypothesis testing, one-way analysis of variance (ANOVA), and simple linear regression. The R statistical software environment will be used to introduce data management and descriptive and inferential statistical methods.

Note: Students interested in this course that do not meet the stated prerequisites should contact the department of Bioinformatics and Biostatistics.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 501. Introduction to Biostatistics for Health Sciences II3 Units

Prerequisite(s): PHST 500.

Description: This course is a continued graduate level introduction to inferential statistical methods, covering multi-way analysis of variance, multiple regression, the chi-square analysis of frequencies and logistic regression, survival analysis, and nonparametric statistical methods. A statistical software package will be used to execute the descriptive, graphical, and inferential statistical techniques on real data sets.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 520. Statistical Computing and Data Management with SAS3 Units

Term Typically Offered: Spring Only

Prerequisite(s): PHST 301, or equivalent (MATH 109, SOC 301, PSYC 301, PAS 408).

Description: This course will introduce students to the fundamental of data management and analysis using SAS. It will give an overview of the SAS system under MS Windows and provide a fundamental grounding in the data step and Base SAS procedure. We will cover elementary statistical analyses such as measures of location and spread, correlation, detection of outliers, graphical displays, comparison of groups, as well as additional specialized studies.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 561. Mathematical Tools I1 Unit

Term Typically Offered: Summer Only

Prerequisite(s): Conditional or full admission to the MS in Biostatistics degree program.

Description: This course covers mathematical tools required for sound comprehension of mathematical probability and statistics concepts included in methodological portions of coursework in the MS in Biostatistics degree. Course topics include: (1) functions and graphs with particular focus on polynomials and roots, rational functions, and exponential and logarithmic functions, and (2) limits and continuity of functions.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 562. Mathematical Tools II1 Unit

Term Typically Offered: Summer Only

Prerequisite(s): Conditional or full admission to the MS in Biostatistics degree program.

Description: This course covers mathematical tools required for sound comprehension of mathematical probability and statistics concepts included in methodological portions of coursework in the MS in Biostatistics degree. Course topics include: (1) first and higher order differentiation of single variable functions and techniques for differentiation, (2) applications of differentiation including identification of minima, maxima, and inflection points, (3) antiderivatives, the definite integral, and the Fundamental Theorem of Calculus, (4) techniques of integration including substitution, integration by parts, etc.; using integrals to compute areas, and (5) sequences and series, convergence of each, partial and infinite sums, geometric series, Taylor series.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 563. Mathematical Tools III1 Unit

Term Typically Offered: Summer Only

Prerequisite(s): Conditional or full admission to the MS in Biostatistics degree program in the School of Public Health and Information Sciences.

Description: This course covers mathematical tools required for sound comprehension of mathematical probability and statistics concepts included in methodological portions of coursework in the MS in Biostatistics degree. Course topics include: (1) multivariable functions, limits, and continuity, (2) partial differentiation and its applications, and (3) multiple integration and its applications.

For class offerings for a specific term, refer to the Schedule of Classes

PHST 564. Mathematical Tools IV1 Unit

Term Typically Offered: Summer Only

Prerequisite(s): Admission to the MS in Biostatistics degree program in the School of Public Health and Information Sciences and MATH 205 (or equivalent).

Description: This course covers mathematical tools required for sound comprehension of mathematical probability and statistics concepts included in methodological portions of coursework in the MS Biostatistics degree. Course topics include (1) vector/matrix algebra and operations, (2) solving systems of linear equations, (3) vector spaces, linear independence, rank, and basis, (4) eigenvalues and eigenvectors, (5) orthogonal vectors and projections, (6) quadratic forms.

For class offerings for a specific term, refer to the Schedule of Classes