M301- Introductory Biostatistics

Introductory Biostatistics will begin by defining populations, samples and parameters. Students will then learn to use the information in the sample to make inferences about population parameters. Data types will be introduced (continuous, categorical, censored) and common methods of visualization and exploratory data analyses will be described. Three methods of inference will be discussed: point estimation, interval estimation and hypothesis testing. Interpretation of estimates will be discussed thoroughly. Hypothesis testing will receive special attention, with definitions of Type I and II errors. Students will learn what p-values are, how they are interpreted, and their appropriate and inappropriate uses. Thresholding variables to create categories will be discussed with correct and commonly-used incorrect methods as well as a critical review of the advantages and disadvantages of using thresholds. Two lectures will focus on censored data, a common occurrence in cancer studies, highlighting why it happens, how one can tell and what can be done with such data. Students will also learn non-parametric statistical methods and exact methods. The last lecture will cover statistical concepts for diagnostic studies, which are widely useful and will re-appear in Advanced Biostatistics (M305).