The results below pertain to a test conducted to investigate how a group of items in a survey are cab be reduced into a lesser number of condensed constructs. You are required to identify the test, interpret the results and report them in an academic

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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The results below pertain to a test conducted to investigate how a group of items in a survey are cab be reduced into a lesser number of condensed constructs. You are required to identify the test, interpret the results and report them in an academic style. You must discuss the assumptions that come with the results of this test. In other words, you are not required to discuss the assumptions that should be checked before the test. 

Component
1
2
3
4
5
6
7
8
9
10
4.247
1.134
.935
.732
.676
.600
.516
481
381
298
Extraction Method: Principal Component Analysis.
Component Matrix
Component
q1a
q2a
q3a
q4a
q5a
q6a
q7a
q8a
q9a
Total
1
451
.547
628
.763
.811
.752
.695
.692
q10a
.692
Extraction Method: Principal
Component Analysis.
a. 2 components
extracted.
1
2
Rotated Component
Matrix
Component
.601
488
846
.822
.625
532
802
q1a
q2a
q3a
q4a
q5a
q6a
q7a
q8a
q9a
q10a
.636
Extraction Method: Principal
Component Analysis.
Rotation Method: Varimax
Initial Eigenvalues
% of Variance Cumulative %
2
749
.705
473
42.465
11.339
9.353
7.320
6.765
5.995
5.164
4.807
3.808
2.984
459
461
42.465
53.804
63.157
70.477
77.242
83.237
88.401
93.208
97.016
100.000
Total Variance Explained
Extraction Sums of Squared Loadings
Total
% of Variance Cumulative %
4.247
1.134
42.465
11.339
42.465
53.804
Rotation Sums of Squared Loadings
Total
% of Variance Cumulative %
33.612
20.192
3.361
2.019
33.612
53.804
Transcribed Image Text:Component 1 2 3 4 5 6 7 8 9 10 4.247 1.134 .935 .732 .676 .600 .516 481 381 298 Extraction Method: Principal Component Analysis. Component Matrix Component q1a q2a q3a q4a q5a q6a q7a q8a q9a Total 1 451 .547 628 .763 .811 .752 .695 .692 q10a .692 Extraction Method: Principal Component Analysis. a. 2 components extracted. 1 2 Rotated Component Matrix Component .601 488 846 .822 .625 532 802 q1a q2a q3a q4a q5a q6a q7a q8a q9a q10a .636 Extraction Method: Principal Component Analysis. Rotation Method: Varimax Initial Eigenvalues % of Variance Cumulative % 2 749 .705 473 42.465 11.339 9.353 7.320 6.765 5.995 5.164 4.807 3.808 2.984 459 461 42.465 53.804 63.157 70.477 77.242 83.237 88.401 93.208 97.016 100.000 Total Variance Explained Extraction Sums of Squared Loadings Total % of Variance Cumulative % 4.247 1.134 42.465 11.339 42.465 53.804 Rotation Sums of Squared Loadings Total % of Variance Cumulative % 33.612 20.192 3.361 2.019 33.612 53.804
Correlation q1a
q2a
q3a
q4a
q1a
q2a
q3a
q4a
q5a
q6a
q5a
q6a
q7a
q8a
q7a
q8a
q9a
q10a
q1a
Communalities
1.000
374
244
188
275
340
264
151
171
195
Initial Extraction
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
q9a
1.000
q10a
1.000
Extraction Method: Principal
Component Analysis.
df
Sig.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett's Test of
Approx. Chi-Square
Sphericity
q2a
565
538
421
.723
723
566
493
220
644
487
374
1.000
.346
272
289
320
379
125
238
347
q3a
.244
.346
1.000
342
412
.411
.421
198
.369
325
Correlation Matrix
q4a
q5a
.188
272
342
1.000
.676
540
.431
,133
.585
471
.885
1592.443
45
<.001
275
289
412
.676
1.000
.548
441
233
591
539
q6a
340
320
411
540
548
1.000
491
219
412
.436
q7a
264
.379
421
431
441
.491
1.000
178
.385
411
q8a
.151
125
.198
.133
.233
219
.178
1.000
.078
220
q9a
171
238
.369
.585
.591
412
385
.078
1.000
.408
q10a
195
347
325
471
539
.436
411
220
408
1.000
Transcribed Image Text:Correlation q1a q2a q3a q4a q1a q2a q3a q4a q5a q6a q5a q6a q7a q8a q7a q8a q9a q10a q1a Communalities 1.000 374 244 188 275 340 264 151 171 195 Initial Extraction 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 q9a 1.000 q10a 1.000 Extraction Method: Principal Component Analysis. df Sig. KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Approx. Chi-Square Sphericity q2a 565 538 421 .723 723 566 493 220 644 487 374 1.000 .346 272 289 320 379 125 238 347 q3a .244 .346 1.000 342 412 .411 .421 198 .369 325 Correlation Matrix q4a q5a .188 272 342 1.000 .676 540 .431 ,133 .585 471 .885 1592.443 45 <.001 275 289 412 .676 1.000 .548 441 233 591 539 q6a 340 320 411 540 548 1.000 491 219 412 .436 q7a 264 .379 421 431 441 .491 1.000 178 .385 411 q8a .151 125 .198 .133 .233 219 .178 1.000 .078 220 q9a 171 238 .369 .585 .591 412 385 .078 1.000 .408 q10a 195 347 325 471 539 .436 411 220 408 1.000
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