Introduction to probability theory and statistical inference with a focus on applications in life sciences. Includes probability laws, probability distributions, sampling methods, experimental design, descriptive statistics, confidence intervals, hypothesis testing, types of error, correlation and regression, and analysis of variance. Computer software for statistical computing is used to apply the concepts covered to realistic data sets from the biological and/or social sciences. Offered spring semester only. Prerequisite: complete university's directed self-placement process. Liberal Arts CoreDesignation: Mathematics (MT) Depth in Sciences (DSCI). (3)