Research Methodology - Dr. Krishan K. Pandey
Research Methodology - Dr. Krishan K. Pandey Research Methodology - Dr. Krishan K. Pandey
Multivariate Analysis Techniques 333 1 2 3 4 5 6 7 8 7 .155 .083 .582 .613 .201 .801 1.000 .152 8 .774 .652 .072 .111 .724 .120 .152 1.000 Column sums Ua1 Normalizing U we a1 obtain Va1 3.662 3.263 3.392 3.385 3.324 3.666 3.587 3.605 i.e., V = a1 U /Nor- a malizing factor .371 .331 .344 .343 .337 .372 .363 .365 * b g b g b g b g b g b g b g b g 2 2 2 2 2 2 2 2 * Normalizing factor = 3662 . + 3. 263 + 3392 . + 3385 . + 3. 324 + 3666 . + 3587 . + 3. 605 = 97. 372 = 9. 868 Then we obtain U a2 by accumulatively multiplying V a1 row by row into R and the result comes as under: U a2 : [1.296, 1.143, 1.201, 1.201, 1.165, 1.308, 1.280, 1.275] Normalizing it we obtain (normalizing factor for U a2 will be worked out as above and will be = 3.493): V a2 : [.371, .327, .344, .344, .334, .374, .366, .365] Comparing V a1 and V a2 , we find the two vectors are almost equal and this shows convergence has occurred. Hence V a1 is taken as the characteristic vector, V a . Finally, we compute the loadings on the first principal component by multiplying V a by the square root of the number that we obtain for normalizing U a2 . The result is as under: Variables (Characteristic × normalizing factor of U a2 = Principal vector V ) a Component I 1 .371 × 1.868 = .69 2 .331 × 1.868 = .62 3 .344 × 1.868 = .64 4 .343 × 1.868 = .64 5 .337 × 1.868 = .63 6 .372 × 1.868 = .70 7 .363 × 1.868 = .68 8 .365 × 1.868 = .68
334 Research Methodology For finding principal component II, we have to proceed on similar lines (as stated in the context of obtaining centroid factor B earlier in this chapter) to obtain the following result * : Variables Principal Component II 1 +.57 2 +.59 3 –.52 4 –.59 5 +.57 6 –.61 7 –.49 8 –.61 The other parts of the question can now be worked out (after first putting the above information in a matrix form) as given below: Variables Principal Components Communality, h2 I II 1 .69 +.57 (.69) 2 + (.57) 2 = .801 2 .62 +.59 (.62) 2 + (.59) 2 = .733 3 .64 –.52 (.64) 2 + (–.52) 2 = .680 4 .64 –.59 (.64) 2 + (–.59) 2 = .758 5 .63 +.57 (.63) 2 + (.57) 2 = .722 6 .70 –.61 (.70) 2 + (–.61) 2 = .862 7 .68 –.49 (.68) 2 + (–.49) 2 = .703 8 .68 –.61 (.68) 2 + (–.61) 2 = .835 Eigen value i.e., common 3.4914 2.6007 6.0921 variance Proportion .436 .325 .761 of total (43.6%) (32.5%) (76%) variance Proportion .573 .427 1.000 of common (57%) (43%) (100%) variance All these values can be interpreted in the same manner as stated earlier. * This can easily be worked out. Actual working has been left as an exercise for the students.
- Page 300 and 301: Testing of Hypotheses-II 283 12 Tes
- Page 302 and 303: Testing of Hypotheses-II 285 Illust
- Page 304 and 305: Testing of Hypotheses-II 287 Table
- Page 306 and 307: Testing of Hypotheses-II 289 fact,
- Page 308 and 309: Testing of Hypotheses-II 291 The te
- Page 310 and 311: Testing of Hypotheses-II 293 Pair B
- Page 312 and 313: Testing of Hypotheses-II 295 Table
- Page 314 and 315: Testing of Hypotheses-II 297 Illust
- Page 316 and 317: Testing of Hypotheses-II 299 Soluti
- Page 318 and 319: Testing of Hypotheses-II 301 r = nu
- Page 320 and 321: Testing of Hypotheses-II 303 where
- Page 322 and 323: Testing of Hypotheses-II 305 Table
- Page 324 and 325: Testing of Hypotheses-II 307 We now
- Page 326 and 327: Testing of Hypotheses-II 309 (ii) I
- Page 328 and 329: Testing of Hypotheses-II 311 all po
- Page 330 and 331: Testing of Hypotheses-II 313 CONCLU
- Page 332 and 333: Multivariate Analysis Techniques 31
- Page 334 and 335: Multivariate Analysis Techniques 31
- Page 336 and 337: Multivariate Analysis Techniques 31
- Page 338 and 339: Multivariate Analysis Techniques 32
- Page 340 and 341: Multivariate Analysis Techniques 32
- Page 342 and 343: Multivariate Analysis Techniques 32
- Page 344 and 345: Multivariate Analysis Techniques 32
- Page 346 and 347: Multivariate Analysis Techniques 32
- Page 348 and 349: Multivariate Analysis Techniques 33
- Page 352 and 353: Multivariate Analysis Techniques 33
- Page 354 and 355: Multivariate Analysis Techniques 33
- Page 356 and 357: Multivariate Analysis Techniques 33
- Page 358 and 359: Multivariate Analysis Techniques 34
- Page 360 and 361: Appendix Summary Chart: Showing the
- Page 362 and 363: Interpretation and Report Writing 3
- Page 364 and 365: Interpretation and Report Writing 3
- Page 366 and 367: Interpretation and Report Writing 3
- Page 368 and 369: Interpretation and Report Writing 3
- Page 370 and 371: Interpretation and Report Writing 3
- Page 372 and 373: Interpretation and Report Writing 3
- Page 374 and 375: Interpretation and Report Writing 3
- Page 376 and 377: Interpretation and Report Writing 3
- Page 378 and 379: The Computer: Its Role in Research
- Page 380 and 381: The Computer: Its Role in Research
- Page 382 and 383: The Computer: Its Role in Research
- Page 384 and 385: The Computer: Its Role in Research
- Page 386 and 387: The Computer: Its Role in Research
- Page 388 and 389: The Computer: Its Role in Research
- Page 390 and 391: The Computer: Its Role in Research
- Page 392 and 393: Appendix 375 Appendix (Selected Sta
- Page 394 and 395: Appendix 377 Table 2: Critical Valu
- Page 396 and 397: Appendix 379 v 2 Table 4(a): Critic
- Page 398 and 399: Appendix 381 Table 5: Values for Sp
334 <strong>Research</strong> <strong>Methodology</strong><br />
For finding principal component II, we have to proceed on similar lines (as stated in the context<br />
of obtaining centroid factor B earlier in this chapter) to obtain the following result * :<br />
Variables Principal Component II<br />
1 +.57<br />
2 +.59<br />
3 –.52<br />
4 –.59<br />
5 +.57<br />
6 –.61<br />
7 –.49<br />
8 –.61<br />
The other parts of the question can now be worked out (after first putting the above information in a<br />
matrix form) as given below:<br />
Variables Principal Components Communality, h2 I II<br />
1 .69 +.57 (.69) 2 + (.57) 2 = .801<br />
2 .62 +.59 (.62) 2 + (.59) 2 = .733<br />
3 .64 –.52 (.64) 2 + (–.52) 2 = .680<br />
4 .64 –.59 (.64) 2 + (–.59) 2 = .758<br />
5 .63 +.57 (.63) 2 + (.57) 2 = .722<br />
6 .70 –.61 (.70) 2 + (–.61) 2 = .862<br />
7 .68 –.49 (.68) 2 + (–.49) 2 = .703<br />
8 .68 –.61 (.68) 2 + (–.61) 2 = .835<br />
Eigen value<br />
i.e., common 3.4914 2.6007 6.0921<br />
variance<br />
Proportion .436 .325 .761<br />
of total (43.6%) (32.5%) (76%)<br />
variance<br />
Proportion .573 .427 1.000<br />
of common (57%) (43%) (100%)<br />
variance<br />
All these values can be interpreted in the same manner as stated earlier.<br />
* This can easily be worked out. Actual working has been left as an exercise for the students.