Lecture: 3 hours
Laboratory: 1 hour
Descriptive statistics, probability, sampling distributions, estimation, hypothesis testing, contingency tables, ANOVA, regression; implementation of statistical methods using computer package.
Prerequisite: Mathematics 16B or 17B or 21B.
To introduce students to probability and applied statistics, featuring specific examples of importance in various biological science subfields, and using some of the tools, as well as the mathematical maturity, that are drawn from a two or three quarter course in calculus for life science majors. An auxiliary goal of the course is to train students in using a computer package in statistical applications.
Summary of course contents:
The following topics will be covered: Descriptive Statistics, Introduction to a Computer package, Probability Concepts and Laws, Independence, Discrete Distributions, Normal Distributions, Sampling Distributions, Central Limit Theorem, Interval Estimation, Tests for Means and Proportions, X2 tests, One-way Analysis of Variance, Multiple Comparisons, Correlation, and Regression.
Only two units credit allowed to students who have taken course courses 13, 32 or 103; not open for credit to students who have taken course 102.
- Statistics for the Life Sciences, R.L. Samuels, J.A. Witmer, Prentice Hall
- Fundamentals of Biostatistics, B. Rosner, Duxbury
- Principles of Biostatistics (second edition), M. Pagano, K. Grauvreau
Science & Engineering
This course overlaps with Statistics 13, 32, 102 and 103. Among these, only STA 32 has a calculus prerequisite. None of these four courses feature the biological science applications that the present course was constructed around. Examples of the latter include discussion of the ELISA test for the presence of the HIV virus, association between smoking and lung cancer, estimation of carcinogen levels in food, Mendel's breeding experiments, Fisher's analysis of agricultural field trials at Rothamsted, and the relationship between obesity and blood pressure.