Discriminant analysis
Discriminant
Analysis is used primarily to predict membership in two or
more mutually exclusive groups. It can be used to assess the adequacy of
classification, given the group memberships of the objects under study; or when
we wish to assign objects to one of a number of (known) groups of objects.
DA
is used when:
·
the dependent is categorical with the
predictor IV’s at interval level such as age, income, attitudes, perceptions,
and years of education, although dummy variables can be used as predictors as
in multiple regression. Logistic regression IV’s can be of any level of measurement.
·
there are more than two DV categories,
unlike logistic regression, which is limited to a dichotomous dependent
variable.
The
major underlying assumptions of DA are:
·
The observations are a random sample;
·
Each predictor variable is normally distributed;
·
Each of the allocations for the
dependent categories in the initial classification are correctly classified;
·
There must be at least two groups or
categories, with each case belonging to only one group so that the groups are
mutually exclusive and collectively exhaustive (all cases can be placed in a
group);
Purposes
of DA:
·
To investigate differences between
groups on the basis of the attributes of the cases, indicating which attributes
contribute most to group separation. The descriptive technique successively identifies
the linear combination of attributes known as canonical discriminant functions
(equations) which contribute maximally to group separation.
·
Predictive DA addresses the question of
how to assign new cases to groups. The DA function uses a person’s scores on
the predictor variables to predict the category to which the individual
belongs.
·
To determine the most parsimonious way
to distinguish between groups.
·
To classify cases into groups.
Statistical significance tests using chi square enable you to see how well the
function separates the groups.
·
To test theory whether cases are classified
as predicted.
Submitted By:-
Sumedha Singla
14114
Group - G
HR - Batch
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