Methods in Experimental Ecology II

Why? Pseudo-replication Unnecessary complicated analysis Weak inference Confounding variables

Methods in Experimental Ecology I Experimental Design and Pseud-replication Probability Distributions Data with normal errors Summary statistics Confidence Intervals Regression Model Selection approaches Statistics Dept. Methods in Experimental Ecology II Bayesian and Frequentist approaches Complex data General Linear Models Mix-models Non-linear Models Data modeling Mathematics Dept. Computer Science Dept.

Approach Understanding the attributes of the data using generated data Implementation of analysis Identification of model limitations Understanding differences between approaches Application to case studies

Bayesian Analysis of averages

Analysis of count data Gregory Territo (Parkinson’s Lab)

Wildebeest carcasses from the Serengeti (Sinclair and Arcese 1995) Analysis of categorical data Females Marrow Death OG SWF TG Total PRED 32 26 8 66 NPRED 6 16 48 58 24 114 Wildebeest carcasses from the Serengeti (Sinclair and Arcese 1995) Males Marrow Death OG SWF TG Total PRED 43 14 10 67 NPRED 12 7 26 45 55 21 36 112

R However, I will teach using R because Students can use any platform they feel comfortable However, I will teach using R because It is free It has reasonable documentation in the web It is flexible It has many applications for biological purposes