Things that you should know, or review, as a necessary prerequisite for this course.

Quantitative and Qualitative variables, Continuous and Discrete variables. Normal distributions and Binomial distributions. How to test if data are Normally distributed.

Means, Standard Deviations, Coefficients of Variation. What they are and how to calculate them.

Chi-squares.

What a t-test is; comparing 2 or more means.

What an F-test is; comparing 2 Mean Squares.

The relationship between the variation, the standard deviation and the sampling variance of a mean and the standard error of a mean. Confidence Intervals.

Review simple linear regression; what the intercept and regression estimate mean. Also simple correlations between 2 traits.

The above material is covered in the course Statistical Methods I (AEMA-310). This is approximately equivalent to the contents of chapters 1 to 6, and 10 and 11, of the textbook Principles and Procedures of Statistics: A biometrical approach, by Steel, Torrie and Dickey. This post-graduate statistics course (AEMA-610) uses Steel, Torrie and Dickey as a reference textbook, amongst others. It starts where Statistical Methods I (AEMA-310) ends and covers Multiple Regression, Multiple and Partial Correlations, Analysis of Variance with Classification Models (One-way, Two-way and Multi-way/Multi-Factorial ANOVA). Many of the examples have been taken from Steel, Torrie and Dickey to illustrate principles of 'balanced' and 'unbalanced' analyses and to show how statistical analyses using computer programs (in this case using SAS) do indeed give the same answers as the textbook! Thus Steel, Torrie and Dickey as well as the course notes and this on-line material are all designed to complement oneanother.

R.I. Cue, 2010 April 28