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Applied Statistics Using SPSS, STATISTICA, MATLAB and R

Applied Statistics Using SPSS, STATISTICA, MATLAB and R

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{CON, ADI, FAD, GLA}; {ADI, FAD, GLA, MAS}; {CAR}<br />

153<br />

These results show that variable PA500 can be helpful in the discrimination of<br />

carcinoma type tissues from other types.<br />

Table 4.16. Scheffé test results obtained with <strong>SPSS</strong>, for the breast tissue problem<br />

(variable PA500). Values under columns “1”, “2” <strong>and</strong> “3” are group means.<br />

Subset for alpha = 0.05<br />

CLASS N 1 2 3<br />

CON 14 7.029E-02<br />

ADI 22 7.355E-02 7.355E-02<br />

FAD 15 9.533E-02 9.533E-02<br />

GLA 16 0.1170 0.1170<br />

MAS 18 0.1231<br />

CAR 21 0.2199<br />

Sig. 0.094 0.062 1.000<br />

Example 4.16<br />

Q: Taking into account the results of the previous Example 4.15, it may be asked<br />

whether or not class {CON} can be distinguished from the three-class group {ADI,<br />

FAD, GLA}, using variable PA500. Perform a contrast test in order to elucidate<br />

this issue.<br />

A: We perform the contrast corresponding to the null hypothesis:<br />

H0: µCON = (µFAD + µGLA + µADI)/3,<br />

4.5 Inference on More than Two Populations<br />

i.e., we test whether or not the mean of class {CON} can be accepted equal to the<br />

mean of the joint class {FAD, GLA, ADI}. We therefore use the contrast<br />

coefficients shown in Table 4.17. Table 4.18 shows the t-test results for this<br />

contrast. The possibility of using variable PA500 for discrimination of class<br />

{CON} from the other three classes seems reasonable.<br />

Table 4.17. Coefficients for the contrast {CON} vs. {FAD, GLA, ADI}.<br />

CAR FAD MAS GLA CON ADI<br />

0 −1 0 −1 3 −1

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