This course covers a suite of parametric and non-parametric statistical techniques used for analyzing ecological data.  The class builds on fundamental principles learned in FIS4200.  Procedures include one-way and two-way analysis of variance (ANOVA's), mean separation techniques, contrasts, repeated measures, Kruskal-Wallis test, correlation, simple and multiple linear regression, stepwise variable selection, residual analysis, trend analysis, and categorical data analysis (contingency table analysis and logistic regression for resource selection). Emphasis is placed on statistical models, appropriate application of testing procedures, understanding test assumptions, and interpretation.  Other topics include fundamental experimental design concepts (e.g., simple designs, experimental vs. measurement units, confounding, randomization, factors), per comparison error rate vs. experiment-wise error rate, non-centrality parameters, and interactions.  Instruction uses a combination of presentations and computer exercises.  In addition, participants will design an experiment, collect and analyze data, and derive conclusions in accordance with principles taught in Data Analysis I and II.

College Credit:  2 semester hours

Who Should Attend:  Any biologist that reviews or conducts scientific investigations. 

Pre-requisite:  Data Analysis I (FIS4200)

Length:  5 days/36 hours

Objectives:  By the end of this session, the participant will be able to:

• Use data description techniques;
• Calculate statistical power and sample size;
• Select proper methods to analyze various types of ecological data as animal or plant resource selection, impact analysis (status), and trend monitoring;
• Identify assumptions of inferential statistical methods and use proper alternatives if required;
• Interpret results of statistical procedures; and
• Provide participants additional background to be successful in Data Analysis III: Status Assessment and Monitoring.