Introductory Applied
Statistics for the Life Sciences 
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Description 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; onesample
testing and confidence intervals, role of assumptions, sample size
determination, twosample inference; basic ideas in experimental
design, analysis of variance, linear regression, goodnessof 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. Prerequisites Math 112 & 113 or Math 114 or
equivalent.
Required text 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.
Computing 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. Grading

