Anth 410 / 510 BIOANTH STATISTICS

Professor: Dr. Frances White

Telephone: 346-5278

E-mail: fwhite@uoregon.edu

Course content

This course is designed for graduate students and upper-level undergraduates with some statistical knowledge and background. My goal is to provide you with a firm grounding in the statistical analysis of data from the field of biological anthropology. I intend to teach you a sophisticated knowledge of important methods in biometry (biological statistics) and their inherent values, assumptions, limitations, and common uses (and misuses). My approach will be to teach you to use the Sokal and Rohlf textbook Biometry (third edition) as a future resource as well as to aid your current understanding. Successful completion of this course will enable you to logically design research projects, to analyze your data in a correct, appropriate, and powerful fashion, and to understand and critically evaluate statistical analyses in the literature.

The course is divided into three major sections. The first short section will briefly cover probability statistics, descriptive statistics, hypothesis testing and experimental design. This first section should be a review of your background coming into this class together with a unification of different terminology you may have encountered in other textbooks. The second section will form the bulk of the class and will cover the different parametric and non-parametric methods of statistical analysis of analysis of variance (anova), correlation, linear regression, frequency analysis, and special topics such as time series data and randomization tests. Analyses will be introduced using univariate data, and bivariate and multivariate applications will be covered where appropriate. The third section of the class runs concurrently with the first two and will involve the use of computer programs for the data organization, statistical analysis, graphical presentation (SAS^© for Windows, BIOMStat, SigmaPlot).

Grading: All exams will be open book. A copy of the Statistical Tables and a simple, non-programmable calculator will be required in all classes, labs, and exams.

The final grade will be based on:

Midterm exam 1 10%

Midterm exam 2 30%

Computer labs 20%

Final exam 40%

Copies of previous exams will be posted on the class Blackboard site

Textbooks:

Sokal and Rohlf, Biometry (3rd edition), Freeman

Rohlf and Sokal, Statistical Tables, Freeman

Topics covered: (Note that dates will shift if we need more time on a topic)

Week	Topic	Chapters (Sokal & Rohlf)
Week 1	Descriptive statistics, parametric and non-parametric	1, 2, 3, 4
	Probability distributions, normality	5, 6
Week 2	Introduction to labs, moving data around and descriptive statistics in Excel
	Hypothesis testing, transformations	7
Week 3	Analysis of variance	8
	Single classification anova	9
Week 4	Lab: testing for normality, assumptions and transformations, single class anova (Model I)	13
	Midterm 1: descriptive statistics, definition of terms, single class anova, normality and transformations
Week 5	Model II and mixed model single class anova, multiple comparisons (planned and unplanned)	9
	Model II two-level nested anova, correspondence across classes	10
Week 6	Mixed model and multi-level nested anova. Model I, II and mixed model two-way anova, with and without replication	11
	Non-parametric anova. Multiway anova with and without replication, Model I, II and mixed.	13, 12
Week 7	Lab: non-parametric anova, nested and two-way anova, multiple comparisons.	13 section 13.11
	Midterm 2: Multiple comparisons. Nested, 2-way multiway, and non-parametric anova.
Week 8	Linear regression: Model I, with and without replication	14
	Analysis of covariance, multiple regression, non-linear regression. Correlation	15, 16
Week 9	Lab: regression and correlation, parametric and non-parametric.
	Frequency analysis.	17
Week 10	Special topics (distribution free methods, time series, randomization tests)	18
	Lab: frequency analysis, special topics
FINAL	Final Exam June 9 at 10:15am