Importance Of Factor Analysis

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Factor analysis is used to find latent variables or factors among observed variables. In other words, if the data contains many variables, the researcher can use factor analysis to reduce the number of variables. Factor analysis groups variables with similar characteristics together. With factor analysis one can produce a small number of factors from a large number of variables which is capable of explaining the observed variance in the larger number of variables. The reduced factors can also be used for further analysis. There are three stages in factor analysis: 1. First, a correlation matrix is generated for all the variables. A correlation matrix is a rectangular array of the correla¬tion coefficients of the variables with each other.…show more content…
The calculated value of chi-square is compared with the table value of chi-square for given levels of significance usually at 5 percent levels. If at the stated levels, the Calculated Value (CV) is less than the Table Value (TV), the null hypothesis is accepted and otherwise it is rejected. 1.11.7 Garrent’s Ranking Method To find out the most significant factor which influences the respondent, Garrett’s ranking technique was used. As per this method, respondents have been asked to assign the rank for all factors and the outcomes of such ranking have been converted into score value with the help of the following formula: 100 (Rij – 0.5) Present Position = ____________ Nj Where Rij = Rank given for the ith variable by jth respondents Nj = Number of variable ranked by jth…show more content…
For this reason they are often referred to as Likert-type scale. In a Likert scale, the respondent is asked to respond to each of the statements in terms of several degrees, usually five degrees (but at times 3 or 7 may also be used) of agreement or disagreement. Likert scales are developed by utilizing the item analysis approach wherein a particular item is evaluated on the basis of how well it discriminates between those respondents whose total score is high and those whose score is low. Those items or statements that best meet this sort of discrimination test are included in the final instrument. Thus, summated scales consist of a number of statements which express either a favourable or unfavourable attitude towards the given object to which the respondent is asked to react. The respondent indicates his agreement or disagreement with each statement in the instrument. Each response is given a numerical score, indicating its favourableness or unfavourableness, and the scores are totaled to measure the respondent’s attitude. In other words, the overall score represents the respondent’s position on the continuum of favourable-unfavourableness towards an

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