STSCI 2200

Biological Statistics I

Course Description

Course information provided by the 2015-2016 Catalog.

In this course, students develop statistical methods and apply them to problems encountered in the biological and environmental sciences. Methods include data visualization, population parameter estimation, sampling, bootstrap resampling, hypothesis testing, the Normal and other probability distributions, and an introduction to linear modeling. Applied analysis is carried out in the R statistical computing environment.

Prerequisites/Corequisites Prerequisite: one semester of calculus.

Forbidden Overlaps Forbidden Overlap: Students may receive credit for only one course in the following group: AEM 2100, BTRY 3010, BTRY 6010, ENGRD 2700, HADM 2010, ILRST 2100, ILRST 6100, MATH 1710, NTRES 3130, PAM 2100, PAM 2101, PSYCH 3500, SOC 3010, STSCI 2100, STSCI 2150, STSCI 2200.

Outcomes

• Students will be able to discuss and explain hypothesis testing and the basic principles of probability and statistics.
• Students will be able visualize trends in complex data sets and develop simple models for analysis.
• Students will be able to estimate population means, variances, standard deviations, and standard errors through a variety of methods.
• Students will be able to critically evaluate the assumptions upon which statistical estimation is based.
• Students will be able to conduct a single-sample, two-sample, and paired t-tests.
• Students will be able to conduct goodness-of-fit tests, contingency tables, simple linear regression and one-way analysis of variance.

Distribution Category (MQR)

When Offered Fall.

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