CATALOG DESCRIPTION:

STAT 02.280 - 4 s.h.

Prerequisites: Calculus I (MATH 01.130) and one of the following: either a) prerequisites Biology 1: Diversity, Evolution and Adaptation (BIOL 01.104) and Biology 2: Concepts in Genetics (BIOL 01.106), b) the co-requisite Biology 3T (BIOL 01.202), or c) prerequisites Biology I (BIOL 01.100) and Biology II (BIOL 01.101)

This laboratory course begins with elementary data analysis (descriptive statistics) for one and two variables, probability and sampling distributions. It uses the normal and t-distributions to introduce the concepts of estimation and hypotheses testing. It includes inference for simple linear regression and correlation, basic analyses of variance, nonparametric tests and chi-square tests. Emphasis is placed on experimentation and the application of statistical methods to the biological sciences. Computer software is used regularly in data manipulation, statistical analyses, and formal presentation of results.

OBJECTIVES:

The objectives of the course in relation to student outcomes: This course will serve as an introduction to statistical methods. We anticipate that most Biology majors will take this course, so while the subject matter is statistics, we will draw from biologically relevant examples and data sets. Students will be exposed to more topics than in a traditional Statistics I course, which at 3 credit hours does not have the time to cover many important statistical techniques for the biology student. Upon completion of this course, the students will have learned, in addition to statistics, how to use a powerful statistical software package for their data analyses in future courses.

CONTENT:

1. Descriptive Statistics

Types of data and graphing techniques (bar graphs, pie charts, etc.)
Distributions and histograms
Measures of center and variability
The normal distribution
Scatterplots
Correlation
Least squares line and descriptive simple linear regression

2. Basic Probability & Sampling Distributions

Basic probability (complementary events and the additive rule)
Conditional probability and independence
Random sampling
Sampling distributions
The central limit theorem

3. Basic Statistical Inference

Confidence intervals for means (for known and unknown s.d.)
Hypothesis tests for means (for known and unknown s.d.)
Type I and II errors
Tests for normality
Confidence intervals and hypothesis tests for population proportions
1-sample, 2-sample, and paired t-tests

4. More Advanced Inference

Chi-square tests (including goodness of fit, independence and homogeneity)
Inference in simple linear regression
One-way ANOVA
Nonparametric tests

POSSIBLE TEXTS:

Finney, D.J., 1980. Statistics for Biologists, Chapman & Hall

Quinn, G.P. & Keough, M.J., 2002. Experimental Design and Data Analysis for Biologists, Cambridge University Press

Samuels, ML and Witmer, JA. 2003. Statistics for the Life Sciences, Third Edition. Pearson Education. Inc.

Watts, T.A. 1997. Introductory Statistics for Biology Students, 2nd edition, Chapman & Hall/CRC.

DCW/CJL 08/07