Question

tests of equality of group means.

1. which one of the above variables are significantly important in assigning group memebership within discriminant anaylisis ?

2.

3.

4.

5.

Wilks' Lambda 1.09 0.997 0.999 0.999 0.649 0.553 0.595 0.026 You adapt to new situations easily You make friends easily You do not like to be tied to someone else's timetable You often like to take chances 0.352 0.283 5.006 0,984 0.997 0.000 0.667 0.634 0.048 0.017 You are more knowledgeable about beer than others 0.186 0.228 3,934 5.722 0.999 0.999 0.9 Gender Part II Output Based Questions Tests of Equality of Group Means 1. Which one of the above variables are significantly important in assigning group membership within discriminant analysis? di2 83738.784 0.007 2. What Null hypothesis is being tested above? 3. Does this dataset meet the statistical assumption of equal variances in test the assumption? Eigenvalues Function Eigenvalue %of Variance Cumulative % Canonical Correla 100 ion 1 0.140 100 0.35 4. What is the statistical interpretation for Eigenvalue of 0.140? Wilks' Lambda Test of Function Wilks' Lambda Chi-square df S 0.877 40.502 11 0.000 5. Does dataset explain more than 50% of variation in assigning group membership?

Answer 1

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AS FOR GIVEN DATA.

1. The variables that are important in assigning group membership are those which have a significant p-value. These variables are:

You like to travel abroad

You are more knowledgable about beer than others

Gender

Education

2. Null Hypothesis: There is homogeneity of variances in groups

3. We will use the box M statistic to test the assumption. As the p-value is significant, we will reject the null hypothesis. Hence, the assumption is not met.

4. Eigenvalue tells us the variance explained by the particular factor out of the total variance by all the factors. It tells us that 14% of variance is explained by this factor.

5.  Wilk Lambda is the measure of the variation not explained by the independent variable. As lamba = 0.877, we can say that 87.7% variation is not explained. Hence, the dataset does not explain more than 50% of the variation.

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