Bartlett's test


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Bartlett's test

[′bärt·ləts ‚test]
(statistics)
A method to test for the equalities of variances from a number of independent normal samples by testing the hypothesis.
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Based on the findings the adequacy of the model is confirmed for each of the dimensions and for Bartlett's test P< 0/05.
Exploratory factor analysis was done on the employer attractiveness variables and the results of communalities table, KMO Value, Bartlett's Test of Sphericity, factor loading were checked.
The suitability for factor analysis is tested using two analysis namely KMO test and Bartlett's test of Sphericity.
3 100 Table 3: KMO & Bartlett's Test of Sphercity Kaiser-Meyer-Olkin .
Bartlett's Test of KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
The KMO and the Bartlett's test of sphericity were found to be significant amongst both the respondent groups (KMO value = 0.
Also check for the factor analysis to identify the structure (factor model) is appropriate, Bartlett's test was used.
50 (See Tables 2 & 3), and Bartlett's Test of Sphericity was statistically significant at p< 0.
60) and Bartlett's Test of Sphericity was significant (Table 2).
Factor analysis was redone according to the indexes presented, with the results of the Kaiser-Meyer-Olkin test and Bartlett's test.
Table 2: KMO and Bartlett's Test and Table 3: Factor loadings after rotation: Component Matrix) to a more manageable number, prior to using them in other analyses such as multiple regression or multivariate analysis of variance (MANOVA) [Fidell (2009)].
A different type of test, the Bartlett's test, which compares the weighted arithmetic average of the sample variances to the weighted geometric average of the sample variances also can be used, but is not robust to violations of normality.