Week

Topic

Material

1

Introduction and Basic Concepts

Moment statistics, distributions, transformations, t-test, correlation, chi-square, Dean’s roadmap of inferential statistics

2

Resampling Methods

Randomization, Bootstrap, Jackknife, Monte Carlo methods

3

Univariate ANOVA Models

1-way, factorial, nested, etc., type I and type II error, Power

4

Univariate Regression

Regression, multiple regression, ANCOVA

5

Matrix Algebra and GLM

Deriving ANOVA and regression in matrix form, GLM

6

Multivariate GLM

MANOVA, MANCOVA, regression, pairwise comparisons with Mahalanobic distance, etc.

7

Patterns of Change

Interpreting interaction terms in GLM, why significant interaction terms exist, dissecting patterns of change

8

Ordination Methods

Principal Components Analysis (PCA), Principal Coordinates Analysis (PCoA), Multidimensional Scaling (MDS), Canonical Variates/Discriminant Function Analysis (CVA, DFA), Correspondence Analysis (CA)

9

Clustering Methods

SAHN methods (UPGMA, WPGMA,etc), K-means clustering

10

Canonical Ordination Methods and Multivariate Association

Canonical Correspondence Analysis (CCA), Redundancy Analysis (RDA), Canonical correlation, partial least squares

11

Matrix Correlation and Flow Chart

Multivariate flow-chart; 2-way Mantel test, 3-way Mantel test

12

Comparative Method

Accounting for the effects of phylogeny in MANOVA, regression, etc.

13

Spatial Statistics

autocorrelation, connectivity matrices, correlograms, semivariograms, point patterns

14

Meta-Analysis

Basic objective, effect sizes, summary analyses, exploratory and graphical approaches, funnel plots, etc.

15

Model Selection

AIC, BIC, LRTmethods