Discriminant Analysis- Spss Essays

619 Words Apr 2nd, 2013 3 Pages
DISCRIMINANT /GROUPS=R(1 2) /VARIABLES=Writtentest GD PI /ANALYSIS ALL /SAVE=CLASS /PRIORS EQUAL /STATISTICS=MEAN STDDEV RAW CORR TABLE CROSSVALID /CLASSIFY=NONMISSING POOLED.

Discriminant
Notes Output Created Comments Input Data C: \Users\Student\Desktop\experiment for disciminant analysis.sav DataSet1 30 User-defined missing values are treated as missing in the analysis phase. In the analysis phase, cases with no user- or system-missing values for any predictor variable are used. Cases with user-, system-missing, or out-of-range values for the grouping variable are always excluded. DISCRIMINANT /GROUPS=R(1 2) /VARIABLES=Writtentest GD PI /ANALYSIS ALL /SAVE=CLASS /PRIORS EQUAL /STATISTICS=MEAN STDDEV RAW CORR TABLE CROSSVALID
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Standardized Canonical Discriminant Function Coefficients Function 1 Writtentest GD PI 1.000 .287 -.048 Structure Matrix Function 1 Writtentest PI GD .960 .334 .196 Pooled within-groups correlations between discriminating variables and standardized canonical discriminant functions Variables ordered by absolute size of correlation within function. Canonical Discriminant Function Coefficients Function 1 Writtentest GD PI (Constant) .136 .250 -.039 -13.230 Unstandardized coefficients Functions at Group Centroids Function R Pass Fail 1 .335 -1.101

Unstandardized canonical discriminant functions evaluated at group means

Classification Statistics
Classification Processing Summary Processed Excluded Missing or out-of-range group codes At least one missing discriminating variable Used in Output 30 0 0 30

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Prior Probabilities for Groups Cases Used in Analysis R Pass Fail Total Prior .500 .500 1.000 Unweighted 23 7 30 Weighted 23.000 7.000 30.000 Classification Results Predicted Group Membership Pass Fail Total R Original Count Pass 18 5 23 Fail 1 6 7 % Pass 78.3 21.7 100.0 Fail 14.3 85.7 100.0 a Cross-validated Count Pass 17 6 23 Fail 1 6 7 % Pass 73.9 26.1 100.0 Fail 14.3 85.7 100.0 a. Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case. b. 80.0% of

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