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Confirmatory factor analysis (CFA) seeks to determine whether the number of factors and the loadings of measured (indicator) variables on them conform to what is expected on the basis of pre-established theory. Indicator variables are selected on the basis of prior theory and factor analysis is used to see if they load as predicted on the expected number of factors. The researcher first generates one (or a few) model(s) of an underlying explanatory structure (i.e., a construct) which is often expressed as a graph. The researcher's ri priori assumption is that each factor (the number and labels of which may be specified hpriori) is associated with a specified subset of indicator variibles. A minimum requirement of confirmatory factor analysis is that one IiypotheSize beforehand the number of faCtors in the model, but usually also the researcher will posit expectations about which variables will load on which factors (Kim and Mueller, 1978b: 55). The researcher seeks to determine, for instance, if measures created to represent a latent variable really belong together. The correlations between the dependent variables are fitted to this structure. Models are evaluated by comparing how well they fit the data. Variations over CFA are called structural equation modelling (SEM), LISREL, or EQS.
fixed capacitor and variable capacitor
If the test is two-tailed, H1: μ ≠ μ 0 then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr
The total number of overtime hours (in 1000s) worked in a large steel mill was recorded for 16 quarters, as shown below. Year Quarter Overtime hour
#question what is the statistical process to reduce hardness of water
DISCUSS THE METHODS OF MEASURING TREND
Quota sampling Under this method enumerators shall select the respondents in place of those not available, as per the quota fixed according to guide lines provided to them.
Using the raw measurement data presented below, calculate the t value for independent groups to determine whether or not there exists a statistically significant difference between
Coefficient of Determination The coefficient of determination is given by r 2 i.e., the square of the correlation coefficient. It explains to what extent the variation
HOW WOULD YOU INTERPRET THIS PROBABILITY:P(a)=1.05
PCA is a linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinat
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