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Courses in SPH Biostatistics Department
Biostatistics offers training in the development and application of statistical and mathematical methods to the design and analysis of public health problems and biomedical research. Biostatistics is a core competency of public health, and a key to unlocking better outcomes.

Biostatistics (BIOSTAT)

Courses in the School of Public Health are listed in the Schedule of Classes under the School of Public Health.

The following courses count as LSA courses for LSA degree credit.
BIOSTAT 617 / SOC 717 / STATS 580 / SURVMETH 617. Methods and Theory of Sample Design
Three or more courses in statistics and preferably a course in methods of survey sampling. (3). (BS). May not be repeated for credit.

This course is concerned with the theory underlying the methods of survey sampling widely used in practice. It covers the basic techniques of simple random sampling, stratification, systematic sampling, cluster and multi-stage sampling, and probability proportional to size sampling. It also examines methods of variance estimation for complex sample designs, including the Taylor series expansion method, balanced repeated replications, and jackknife methods.

BIOSTAT 646 / BIOINF 545 / STATS 545. High Throughput Molecular Genomic and Epigenomic Data Analysis
STATS 400 (or equivalent) and graduate standing: or permission of instructor. Students should have completed at least programming class with a passing grade. Preparation in biiology or quantitative analysis also recommended. (3). (BS). May not be repeated for credit.

This course will cover basic analysis of microarrays, RNA-Seq, and ChIP-Seq data including hands-on lab sessions. The class also covers an introduction to the underlying biology and the technologies used for measuring RNA levels, transcription factor binding an epigenetic modifications, and quality control of microarray and deep sequencing data. Topics: technologies, experimental design, data preprocessing, normalization, quality control, statistical inference (group comparisons, peak detection), multiple comparison adjustments, power calculations, clustering, functional enrichment testing.

BIOSTAT 680 / MATH 627. Applications of Stochastic Processes I
Graduate standing; BIOSTAT 601, 650, 602 and MATH 450. (3). (BS). May not be repeated for credit.

BIOSTAT 685 / STATS 560. Introduction to Nonparametric Statistics
STATS 426 or permission of instructor. (3). (BS). May not be repeated for credit.

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