Research Methodology - Dr. Krishan K. Pandey
Research Methodology - Dr. Krishan K. Pandey Research Methodology - Dr. Krishan K. Pandey
Multivariate Analysis Techniques 341 in hypothesis testing and interval estimation studies. Multivariate analysis (consequently the use of multivariate techniques) is specially important in behavioural sciences and applied researches for most of such studies involve problems in which several response variables are observed simultaneously. The common source of each individual observation generally results into dependence or correlation among the dimensions and it is this feature that distinguishes multivariate data and techniques from their univariate prototypes. In spite of all this, multivariate techniques are expensive and involve laborious computations. As such their applications in the context of research studies have been accelerated only with the advent of high speed electronic computers since 1950’s. Questions 1. What do you mean by multivariate techniques? Explain their significance in context of research studies. 2. Write a brief essay on “Factor analysis” particularly pointing out its merits and limitations. 3. Name the important multivariate techniques and explain the important characteristic of each one of such techniques. 4. Enumerate the steps involved in Thurstone’s centroid method of factor analysis. 5. Write a short note on ‘rotation’ in context of factor analysis. 6. Work out the first two centroid factors as well as first two principal components from the following correlation matrix, R, relating to six variables: Variables 1 2 3 4 5 6 1 1.00 .55 .43 .32 .28 .36 2 1.00 .50 .25 .31 .32 Variables 3 1.00 .39 .25 .33 4 1.00 .43 .49 5 1.00 .44 6 1.00 Answers: Variables Centroid factors Principal Components I II I II 1 .71 .40 .71 .39 2 .70 .46 .71 .48 3 .70 .37 .70 .32 4 .69 –.41 .69 –.42 5 .65 –.43 .64 –.45 6 .71 –.39 .71 –.38 7. Compute communality for each of the variable based on first two centroid factors in question six above and state what does it indicate.
342 Research Methodology 8. Compute the proportion of total variance explained by the two factors worked out in question six above by the principal components method. Also point out the proportion of common variance explained by each of the two factors. ‘ 9. What is the significance of using multiple discriminant analysis? Explain in brief the technical details involved in such a technique. 10. Write short notes on: (i) Cluster analysis; (ii) Multidimensional scaling; (iii) Reflections in context of factor analysis; (iv) Maximum likelihood method of factor analysis; (v) Path analysis.
- Page 308 and 309: Testing of Hypotheses-II 291 The te
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- Page 362 and 363: Interpretation and Report Writing 3
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342 <strong>Research</strong> <strong>Methodology</strong><br />
8. Compute the proportion of total variance explained by the two factors worked out in question six above<br />
by the principal components method. Also point out the proportion of common variance explained by<br />
each of the two factors. ‘<br />
9. What is the significance of using multiple discriminant analysis? Explain in brief the technical details<br />
involved in such a technique.<br />
10. Write short notes on:<br />
(i) Cluster analysis; (ii) Multidimensional scaling;<br />
(iii) Reflections in context of factor analysis;<br />
(iv) Maximum likelihood method of factor analysis; (v) Path analysis.
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