This course is a broad overview of the principles and methods of statistical analysis used in life sciences research, including biological, veterinary, and translational research, and provides the background a new researcher needs to understand and apply commonly used statistical methods and the preparation needed for more advanced coursework.
Classes will include general instruction and background information, detailed examples of how to perform the analyses, with actual data sets, and discussion on how the topic has been applied in biological research, including reading and assessing papers in the field. Computing will be performed using the R software environment, though students may use alternate software with permission.
Topics will include:
Descriptive statistics and exploratory graphics
Understanding statistical inference and interpreting P-values and confidence intervals.
One and two sample inference, including t-tests, proportion tests, and non-parametric alternatives
Linear regression, including the effects of confounders
ANOVA methods, including pairwise comparisons and multiple comparisons
Gopher Grades is maintained by Social Coding with data from Summer 2017 to Summer 2025 provided by the University in response to a public records request