Biostatistics has many applications, from the environmental and medical to forensic science, public health and genomics. It is used in various industries and is a course that is taken in several different majors and graduate programs, but most notably graduate degree programs in public health. Courses in biostatistics are part of some undergraduate curricula; degrees in biostatistics are possible at the master's degree and doctorate levels. Courses are also appropriate to individuals who wish to become statisticians or biostatisticians.
Biostatistics are gathered from a range of data including:
- Sonar images
- Paper/seismographic charts
- Graphs (often created by the statistician)
- Scientific experiments
- Mathematical equations with multiple variables
Students learn to use these independently and in combination to create accurate and useful statistics.
List of Common Courses
Principles of Biostatistics Course
This introductory course covers the fundamental concepts of biostatistics and their applications to the interpretation of medical research. Students may review such topics as probability distributions, linear and logistic regression, descriptive statistics and survival analysis.
Applied Statistics Lecture
This lecture may be offered as part of a series intended to familiarize undergraduate students to Biostatistics careers. Topics may include research methods, statistical concepts and the diverse nature of the biostatistics field. Lectures are generally led by faculty and may be offered as a 1-credit or non-credit program.
Statistics for Human Genetics Course
This second-year graduate course is designed for biostatistics and biology students interested in the statistical methodology used in the research of genetic and genomic issues. Topics include DNA or protein sequence alignment, analyses of gene expression data and statistical applications in genetic mapping. An advanced course in statistics may be a prerequisite.
Biostatistical Methodology Course
This course introduces the theories and methods utilized in biostatistical research and reporting. Topics may include the Central Limit Theorem, probability distributions, random sampling, correlation and simple linear regression. Previous courses in advanced algebra and a working knowledge of Microsoft Excel may be required.
Statistical Analysis System (SAS) Course
This course is designed to acquaint students with the use of SAS and to build the skills necessary for successful data manipulation and analysis. Topics may include the graphical techniques for data display, replication and documentation.
Multiple Comparisons Lecture
This lecture examines the effects of multiple testing and the proper methods for data adjustment. Topics may include the issues of large multiplicity and multiple hypotheses, along with a review of specific analytic procedures utilized in multiple testing settings. The lecture is typically available as a 1-credit or non-credit program.