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.
References in periodicals archive ?
The suitability of the data for structure detection, respectively the appropriateness of the factor analysis is tested by Kaiser-Meyer-Olkin (KMO) index, and Bartlett's Test of Sphericity.
Secondly, Bartlett's test of sphericity is employed to test whether correlation matrix is an identity matrix.
Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's Test of Sphericity were performed which confirms the appropriateness of the sample data, where sample adequacy (.919) is above the cut off and the p-value is less than .001 for sphericity.
In this study, Kaiser-Meyer-Olkin (KMO) value was found to be 0.660 and Bartlett's test was determined as [X.sup.2]=5888.904 and p=0.000.
Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (KMO) and Bartlett's test of sphericity were used to investigate the adequacy of the sample size.
Bartlett's test and KMO value used to check the factor analysis appropriateness.
When the correlations were verified with Bartlett's test of Sphericity for the biometric traits, the results were significant (P<0.01, Chi-square value 182.865) which was supportive for the rationality of the factor analysis of the data as indicated in Table-4.
* Correlation Matrix, Kaiser-Meyer-Olkin (KMO) Measure and Bartlett's Test
Descriptive statistics, Reliability, KMO and Bartlett's test, factor loading, correlation regression performed on the data for inferences.
Two tests, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) and Bartlett's Test of Sphericity, were run to determine the appropriateness of including factor analysis in this research.