Biomedical Statistics with R
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.