BIOST 2141 - BIOSTATISTICAL METHODS

Minimum Credits: 3
Maximum Credits: 3
BIOST 2141 is an introductory applied biostatistics course for biostatistics graduate students, other quantitative public health students, and health career professionals who will make use of statistical methods in research projects, interpreting literature and possibly develop new biostatistical methods in the future. This class is intended for students needing a more research-oriented approach than that provided in BIOST 2011 (Principles of Statistical Reasoning) and an approach with a greater emphasis on mathematical foundation than provided in BIOST 2041 (Introduction to Statistical Methods I). Students in BIOST 2141 are expected to have a working knowledge calculus including multivariable differentiation and integration. Topics covered in this course include exploratory and descriptive analyses, both quantitative and graphical. Probability is discussed, including sample spaces, probability measures, probability calculus, and popular continuous and discrete distributions. Estimation and hypothesis testing are discussed in detail for one- and two-sample problems for both continuous and discrete data. One-way ANOVA, ANCOVA, simple linear regression, and correlation methods are explored. Nonparametric and computationally intensive resampling and simulation-based methods are discussed in addition to classical parametric approaches. Broad goals include: the use of R to analyze data sets and answer research questions; recognition of situations when procedures are and are not appropriate; and intuitive understanding of the rationale used in creating the statistical procedures presented.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Course Requirements: PLAN: BIOST-MS or BIOST-PHD

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