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RBIF 111

R for Biomedical Informatics

This course is an advanced mathematics and applied statistics course that will introduce students to data analysis methods and statistical testing. It provides a foundation for Biological Data Mining and Modeling (RBIF 112) and Design and Analysis of Microarray Experiments (RBIF114). The course covers R (a statistical programming language) to introduce students to descriptive and inferential statistics, basics of programming, common data structures and analysis techniques. The course covers methods important to data analysis such as t-tests, chi-squared analysis, Mann-Whitney tests, correlation and regression, ANOVA, LDA, PCA, tests of significance, and Fisher's exact test.

At the end of the course, students will be able to:

Write programs in R for data analysis.

Discern appropriate data models to answer specific questions.

Analyze data with a number of statistical models.

Conduct explorative analysis of large data sets.

Choose appropriate methods of analysis for a given problem.

Perform tests to validate models against data.

Evaluate various statistical methods on the basis of their strengths and weaknesses.

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