The aim of this course is to provide undergraduate students in the life sciences with an introduction to modern statistical practice. Topics include: exploratory data analysis, probability and random variables; one-sample testing and confidence intervals, role of assumptions, sample size determination, two-sample inference; basic ideas in experimental design, analysis of variance, linear regression, goodness-of fit. See the syllabus for more information.

Note that  students  may receive credit for no more than one of the following courses: Stat 201, 224, 301, 324, & 371.

Math 112 & 113 or Math 114 or equivalent.

Statistics for the Life Sciences, by Samuels and Witmer (3rd edition). A substantial portion of the text will be covered. There may be some  material  presented in the lectures that is not included in the text. You will be responsible for everything covered in the lectures.

For some homework assignments, we will make use of the freely available software  R. R runs under Windows, Macs, and Linux, and R is also available in several public computer labs on campus. I encourage all of you to
get access to R as quickly as possible. If you have your own computer, download the appropriate version of R from  CRAN  otherwise check it out on one of the public computer labs on campus.