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Essay / Research Paper Abstract
This 5 page paper answers a set of questions on statistics, including describing the differences between multivariate, bivariate and univariate methods, dependence and non dependence methods, defining multiple linear regression, discriminant analysis of variance, canonical correlation and multivariate analysis of variance and how they may be used. The bibliography cites 5 sources.
Page Count:
5 pages (~225 words per page)
File: TS14_TEstatypes.doc
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Unformatted sample text from the term paper:
situation where there are more than one simultaneous statistical variable being examined and will be concerned with the multivariate probability distributions. Bivariate statistical analysis may be categorised as a special
case of multivariate statistical analysis as it is an assessment looking at two variables, such as with correlation statistical analysis and the use in linear regressions where the association between
two variables is assessed (Curwin and Slater, 2003). By comparison univariate analysis is relativity simple, this is an approach where for a any chosen sample there is only an
assessment of a single variable, it is possible to use this approach several times, each time to test a single variable. When undertaking a univariate analysis a second variable may
be implied in the way that the sample is grouped or sorted (Curwin and Slater, 2003). 2. What is the distinction between dependence methods and interdependence methods? In
any situation where there is more than a single variable being assessed the relationship or potential relationship between the variables being tests may need to be considered (Curwin and Slater,
2003). In some cases some of the variables may be dependant on other variables, in this case dependence methods will need to be used depending on hoe many of
the variables are dependent and the type of dependence, for example, where only one or more variables are dependant and they are metric then the use of multiple regression
analysis may be used, but where it is non metric multiple discriminate analysis may be used for one dependant variable and conjoint analysis for several dependant variables. 3.
What is the aim of multiple linear regression? Discriminant analysis of variance? Canonical correlation? Multivariate analysis of variance? Multiple linear regression is used
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