# Statistical Methods II AEMA-610

Course description and overview

Course outline

This introductory page refers to various documents that are a complement
to the class notes for this course.

There are examples from the course notes, plus other examples illustrating
various topics. Most examples have 3 sections :

- Description of topic and data
- SAS Code
- Interpretation, further references, pointers, etc

You can browse through topics as well as retrieve files with the data from
examples, together with the SAS code used. The course notes are available as
as a PDF file that can be read and printed using
Adobe Acrobat reader.

### Topics

#### Introduction

- Introduction, SAS, viewing
- Prerequisites/Review
- Introduction to the SAS language
- The Model, what and why

#### Multiple Regression and Correlations

- Multiple Regression I
- Are We Normal?
- Type I and Type III (Sequential and Marginal)
Sums of Squares
- Quadratic Regressions
- Independent variables, To Be (In), or Not To
Be (In)?
- Computing our own F-values
- Correlations

#### Classification Models

- Completely Randomized Design, One-way
classification
- Partial R
^{2}
- Multiple Comparisons
- Fixed or Random Effects
- Regression vs. Classification
- Variance, Normality and Homogeneity of Variance
(The Sequel)
- Two-way classification, Fixed effects
- Gains in efficiency
- Ignoring an effect from a model (Ignorance is
bliss!)
- Nested designs
- Nested designs (the sequel)
- Factorial designs, fixed effects
- Classification and covariates
- Factorial models, Classification vs. Regression

#### Mixed Models

- What are they and why are they important?
- Two-way classification, mixed model (RCBD)
- Pseudo R
^{2} in a mixed model
- Repeated measures
- Latin square Designs
- Simple Cross-Over Design

#### Other Aspects

- Expectations of Mean Squares (CRD)
- Sample size and number of sub-samples
- Combining Probabilities
- Categorical Data

#### Examples

- Log of examples
- Output from example 1
- Output from example 2
- Output from example 3

#### R stuff

- Link to various examples using R

- Normal distribution table (PDF)

- t table (PDF)

- Chi-squared table, part 1 (PDF)

- Chi-squared table, part 2 (PDF)

- F table, part 1 (PDF)

- F table, part 2 (PDF)

- F table, part 3 (PDF)

- F table, part 4 (PDF)

- F table, part 5 (PDF)

- F table, part 6 (PDF)

- IML reference manual (1000 pages)

- STAT reference manual (8000 pages!)

- Selected references
- Course notes (PDF, Acrobat format)

Department of Animal Science homepage

Faculty of Agricultural and
Environmental Sciences homepage

McGill University homepage

Statistical Methods II, AEMA-610A, McGill University

Roger Cue, Dept. Animal Science ©

Roger.Cue@mcgill.ca

last update : 2018 July 21^{st}