Section 3 Analysis Overview

The following sections on Multivariate Analysis are drawn from Johnson, Wichern, and others (2014). The Key Elements Section below draws heavily from Chapters 2 and 3. The Linear Predictors Section draws from Chapters 2, 6 and 7.

The aim of these two sections is to establish the key theoretical concepts required to understand the Multivariate Models discussed later. The Key Elements Section defines a Random Sample and presents (without proof) the asymptotic properties of the (multivariate) sample mean and sample covariance matrix.The Linear Predictors Section section defines a Linear Predictor Function and the Mean Squared Error criterion for measuring the accuracy of linear prediction functions. This section finishes with an explanation of the link between best linear predictors and the Multiple Correlation Coefficient.

References

Johnson, Richard Arnold, Dean W Wichern, and others. 2014. Applied Multivariate Statistical Analysis. Vol. 4. Prentice-Hall New Jersey.