Principles of data analysis based on real examples will be discussed in this course. Topics include measures of central tendency, dispersion, confidence intervals, sampling issues, probability distributions, hypothesis testing, comparing means, and basic experimental design procedures.

In this course, students will learn about the following:

  • Interpreting sampling and effective display of data
  • Applying the concepts of probability distributions
  • Utilizing the data analysis techniques for discrete data
  • Constructing the analysis techniques for continuous data
  • Formulating experimental design and analysis

Each student will be required to complete a series of assignments, several exams, and a final examination. Graduate students will also read, discuss and summarize papers from the primary literature.

Taught in spring semesters.  3 credits

MATH 1130 or STAT 2510

Michael C. Whitlock and Dolph Schluter. 2009. The Analysis of Biological Data. Roberts and Company, Greenwood Village, CO. ISBN 978-0-9815194-0-1; Library of Congress ID QH323.5.W48 2009.