Titlebook: An Introduction to Multivariate Techniques for Social and Behavioural Sciences; Spencer Bennett,David Bowers Book 1976 Spencer Bennett and

刪減

An Introduction to Multivariate Techniques for Social and Behavioural Sciences

單純

An Introduction to Multivariate Techniques for Social and Behavioural Sciences978-1-349-15634-4

熱情贊揚

Introduction, example) have been used by researchers in the social and behavioural sciences. These techniques, known collectively as multivariate analysis, as versatile and wide-ranging in application as they are, deserve to be known to a wider audience than hitherto, and it is the purpose of this book to introd

蟄伏

Factor Analysis: the Centroid Method,it is important that the assumptions underlying their use are met. To re-iterate briefly: ideally, the distributions of the variables should be continuous and reasonably normal (at least they should not be bimodal or markedly skewed); discontinuous variables will be discussed further in Chapter 7. R

Immunization

Melodrama

Principal Factor Analysis,e correlations between the original observed . in terms of their correlations with a smaller set of .. In this chapter we will examine two other methods of analysis, principal factor analysis and principal component analysis. The approach of the two methods is similar and their aim, to aid interpret

圣人

Multiple Groups Analysis,thogonal or oblique rotations to simple structure. This chapter is concerned with a method called . from which an oblique factor matrix is obtained directly and all factors are extracted simultaneously. The number of such groups (and therefore factors) is assumed at the outset either on the basis of

FLING

Confess

Discriminant Analysis,. The variables were in fact the results of several measures taken on a single group of objects or persons. In the following chapter we will examine a rather different problem, that in which several groups of objects or persons are measured on the same set of variables. The principal question to be

FILTH

The Analysis of Qualitatitive Data,riminating between groups and classifying individuals or objects into categories. Throughout, it was assumed that the measurement of the variables under consideration was in . terms. Furthermore, it was also assumed that the variables in question were normally distributed (at least approximately) an