STATISTICS SPSS

THERE ARE ONLY 1 QUESTION TO ANSWER BASED ON THE OUTPUTS PROVIDED BELOW.

Are all variables significant in the model?

4) Verify the sales agent's claim using canonical discriminant analysis (use the stepwise method, in case there is correlation between any two independent variables) in SPSS (or any other software) and report your findings by answering the followingquestions:

(i)Are all variables significant in the model?

Make use of the following outputs in order to answer the question above:

Wilks' Lambda Number of Exact F Step Variables Lambda df1 df2 df3 Statistic df1 df2 Sig 1 .656 1 1 115 60.434 115.000 <.001 .516 .351 .326 .313 co .302 .307 group comparisons d step vehicle type car lorry f sig. sig a. degrees of freedom for b. c. d. e. f. g. h. i. canonical discriminant functions eigenvalues function eigenvalue variance cumulative correlation first were used in the analysis. wilks lambda test chi-square df standardized coefficients log-transformed sales zscore: price thousands .803 wheelbase length curb weight fuel capacity efficiency .632 unstandardized at centroids evaluated meansclassification processing summary processed excluded missing or out-of-range codes least one discriminating variable output prior probabilities groups cases analysis unweighted weighted total classification fisher linear results predicted membership original count .9 cross-validated grouped correctly classified. cross validation is done only those each case classified by derived from all other than that case. classified.stepwise statistics variables entered exact removed statistic df1 df2 df3 horsepower log- transformed minimizes overall entered. maximum number steps minimum partial to enter remove level tolerance vin insufficient further computation.variables .345 .372 .437 .343 .334 .173 .177 .339 .196 .138 .176 .328 .395 .372variables not min. resale value engine size .242 width .779 .566 .688 .665 .359 .402 .214 .649 .511 .432 .616 .292 .504 .864 .400 .250 .436 .270 .191 .706 .188 .506 .341 .695 .223 .388 .184 .197 .150 .350 .310 .055 .342 .142 .296>