- Recording High-Speed Video of Animal Behavior
- Collecting Locomotor Data from High-Speed Video
- Digitizing Points on a High-Speed Video
- Obtaining Instantaneous Velocity and Acceleration Data from a High-Speed Video
- Syncing a High-Speed Video Camera with Other Equipment
- Using a Kistler Force Plate
- Using a Kistler Force Transducer
- Fixing and Preserving Specimens

Description | Reference | |

## Calculates a reduced major axis regression and its residuals in two ways, and calculates Kolmogorov-Smirnov and Shapiro-Wilks tests for normality on the residuals. |
## Bergman, P.J., Berk, C.P. 2012. The evolution of positive allometry of weaponry in horned lizards ( | |

## Does a Mantel test to compare two matrices in different ways: You can compare just the lower triangle, the lower triangle and diagonal, or the whole matrix. |
## Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560. | |

## Uses multiple regression to construct an F-matrix and associated statistics and metrics, including the FF |
## Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560. | |

## Creates an F-array and associated statistics for multiple phenotypic traits, multiple performance measures, and multiple species related by a phylogeny. Uses the Mantel and F-matrix functions. |
## Bergmann, P.J., McElroy, E.J. 2014. Many-to-many mapping of phenotype to performance: An extension of the F-matrix for studying functional complexity. Evolutionary Biology 41: 546-560. | |

## Does a randomization ANOVA of any design that can be handled by the aov function in R with a user-specified number of data randomizations. |
## Mitchell, A., Bergmann, P.J. 2016. Thermal and moisture habitat preferences do not maximize jumping performance in frogs. Functional Ecology 30: 733-742. |

- Lab 1 - Introduction to R
- Lab 2 - Experimental Design
- Lab 3 - ANOVA
- Lab 4 - OLS versus RMA Regression
- Lab 5 - Multiple Regression and ANCOVA
- Lab 6 - MANOVA
- Lab 7 - PCA
- Lab 8 - Randomization Tests
- Lab 9 - Model Selection Using AIC
- Lab 10 - Phylogenetic Correlation and Regression
- Lab 11 - Models of Trait Evolution
- Lab 12 - Introduction to Bayesian Inference