BME59500 - Biostatistics

Fall 2017

Days/Time: TTh / TBA
Credit Hours: 3

Learning Objective:
The course is designed for graduate students to build a foundation of multivariate statistical analysis, to analyze large data with multiple variables, to formulate appropriate models from different perspectives, and to correctly interpret statistical estimates. By the completion of this course, students will be able:1) to understand fundamental concepts in multivariate regression analyses, 2) to apply data analyses using an advanced statistical software package, 3) to formulate research questions into suitable multivariate frameworks, and 4) to analyze appropriate statistical estimates from multivariate analyses.

Course focuses on fundamental principles of multivariate statistical analyses in biostatistics, including multiple linear regression, multiple logistic regression, analysis of variance, & basic epidemiology concepts. Fundamental theories are applied to analyze various biomedical applications ranging from lab data to large-scale epidemiological data. Focus on multivariate statistical analyses, which involve observation & analysis of more than 1 variable & take into account effects of all variables on responses of interest. This course is an intermediate biostatics course, based on mathematical formations, explanations of key concepts, & hands-on analyses (neither a cookbook approach nor a sophisticated mathematical approach).

Topics Covered:
Introduction to basic epidemiological concepts; Simple linear regression; Correlation analysis; Multiple linear regression; Screening and diagnostic tests; Simple logistic regression; Multiple logistic regression; Analysis of variance; Multiple comparisons; Survival analysis.

IE 330 Probability and Statistics in Engineering II or equivalent basic statistics course.

Applied/Theory: 70/30

Web Address:

Web Content:
Link to my current website, syllabus, grades, lecture notes, homework assignments, solutions, quizzes, chat room and message board.

Students will be evaluated in terms of their performance on series of homework that will be distributed during semester. Assignment will be evaluated critically. Assignment will include hands-on analyses of basic principles of concepts covered during lectures using small sample examples.


One midterm & one final take-home exam. Each exam will cover different content; hence, final exam not cumulative. Format of exams subject to change.

Dupont WD. Statistical Modeling for Biomedical Researchers. Cambridge University Press, 2nd edition, 2009. Disclaimer: final textbook listings are available in April for fall and summer semesters. Please visit the Listing of Textbooks by College or School for the most up-to-date information.

Computer Requirements:
ProEd Minimum Computer Requirements. This course will also conduct basic operations in large-scale statistical analyses with statistical software packages (e.g. STATA). Students will have access to the packages in BME computer lab. Six-month ($32) or one-year ($49) STATA licenses are also available to purchase his/her own student version ( STATA is chosen for the breath and depth of its statistical methods, its ease of use, and its good documentation. However, students can use other software packages such as SAS, SPSS, and R (free statistical software). Overall, minimal help on STATA will be provided, given that this course is intended to teach biostatistics not a package.

ProEd Minimum Requirements:

Tuition & Fees: view

Other Requirements:


Young L. Kim
Purdue University
Weldon School of Biomedical Engineering
206 S. Martin Jischke Drive
West Lafayette, IN 47907-2032
Instructor HomePage

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