Discriminant analysis can predict group membership based on independent variables and identify characteristics that classify individuals. It works when the dependent variable is dichotomous or multicategorical and independents are metric. For example, it could classify athletes as basketballers or volleyballers based on anthropometric measures, or students as high or low performers based on skills. For accurate results, group sizes should not differ greatly, there should be at least five times as many cases as independents, variables must be normally distributed, and have linear and homoscedastic relationships. SPSS can be used to conduct a discriminant analysis to identify players' categories in a sports selection process.

3. Objectiv
e
• To understand group differences and to predict the likelihood that a
particular entity will belong to a particular class or group based on
independent variables.

4. A second purpose of the discriminant
analysis is to study the relationship
between group membership and the
variables used to predict the group
membership.

5. When the dependent variable is dichotomous or
multichotomies.
Independent variable are metric;
i.e.; interval or ratio.

6. o To identify the characteristics on the basis of which one can classify an individual as :
 Basketballer or volleyballer on the basis of anthropometric variables.
 High or low performer on the basis of skill.
 Junior or senior category on the basis of the maturity parameters.

7. Sample size
 Group sizes of the dependent should not be grossly
different i.e. 80;20, here logistic regression may be
prefer.
 Should be at least five times the number of independent
variables.
Normal distribution
 Each of the independent variable is normally distributed.
Homogeneity of variance/Covariances
 All variables have linear and homoscedastic relationship.

8. Application of SPSS
Eg. To identify the players into different categories during selection
process.
Variable
View

9. Data View

10. Steps:

11. Next

12. Output

13. Z= -124.155 + .974 * X1 + .411 * X2 - .702 * X3 -2.621 * X4
X1 Height
X2 Back explosive
strength
X3 Judgement
X4 Palm length
Where,

15. THANK YOU…