# Department of Statistics

## Stat 205

205—Elementary Statistics for the Biological and Life Sciences. (3) (Prereq: MATH 111 or higher, or consent of department) An introduction to fundamental statistical methods with applications in the biological and life sciences. Topics include descriptive statistics, probability, inference, and an overview of contingency tables, linear regression, and ANOVA.

Usually Offered: Fall and Spring Semesters

Purpose: To give students in biology, ecology, public health, pharmacy, nursing and other life sciences a non-calculus based introduction to the application of modern statistical methods including descriptive and inferential statistics. To show students that statistics is an important research tool within the biological and life sciences.

Current Textbook: Statistics for the Life Sciences, 4/E, by Samuels, M. L., Witmer, J. A., and Schaffner, A. (2011). Pearson.

 Topics Covered Chapters Time Describing/summarizing data: Summary statistics, Graphical display of data, Random sampling, introduction to R 1.1, 1.3, 2.1-2.6, 2.8 2.0 weeks Basic probability and statistical distributions: Discrete distributions, Continuous distributions, Binomial and normal distributions 3.1-3.6, 4.1-4.4 2.0 weeks Statistical estimation, Central limit theorem 5.1-5.2 0.5 weeks Confidence Intervals in one and two-sample problems 6.1-6.3, 6.5-6.6 1.0 weeks Hypothesis testing, Power and sample size, P-values, Error rates, Experiments vs. observational studies, Association vs. causation, One and two-sided tests, Wilcoxon-Mann-Whitney test 7.1-7.5, 7.7, 7.9-7.10 1.5 weeks Paired observations, Sign test, Confidence interval and hypothesis test for binomial proportion 8.2-8.3, 9.2, 9.4 1 week Contingency tables: Difference in proportions, Relative risk, Odds ratios, Testing independence, Case-control studies, Simpson's paradox, Cochran-Mantel-Haenszel test 10.1-10.2, 10.4-10.5, 10.7, 10.9 and notes 1.5 weeks Analysis of Variance: Introduction to one-factor ANOVA 11.1-11.2, 11.4 0.5 week Correlation and Regression: Linear correlation analysis, Simple linear regression, multiple regression 12.1-12.5 and notes 1 week Advanced topics: Logistic regression, Diagnostic screening, Survival analysis notes 1 week

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.

Contact Faculty: TBD