Comprehensive Stats Report: Personality, Cognitive Ability & Job Role

This assignment presents a detailed statistical analysis of the relationships between personality traits, cognitive abilities, and job performance. It employs factor analysis to reduce the dimensionality of personality traits, cognitive ability measures, and job performance indicators. The analysis extracts key components from each of these domains. Subsequently, regression analysis is used to examine the predictive power of experience, personality traits, and cognitive abilities on job performance, testing the hypothesis of significant differences in mean values. The report also explores mediation analysis to understand the underlying mechanisms through which personality and cognitive factors influence job outcomes. The correlation matrices provide insights into the inter-relationships among the variables. This document is available on Desklib, a platform offering a wide range of study tools and solved assignments for students.

Stats

Table of Contents
Question 1: Factor analysis......................................................................................................................................................................3
Question 2: Regression analysis............................................................................................................................................................13
Q.3 examining hypothesis using mediation analysis.............................................................................................................................17
Question 4:.............................................................................................................................................................................................33
Question 5:.............................................................................................................................................................................................33

Question 1: Factor analysis
Personality traits
Factor Analysis
Communalities
Initial Extraction
a1 1.000 .707
a2 1.000 .551
a3 1.000 .613
a4 1.000 .556
a5 1.000 .391
c1 1.000 .481
c2 1.000 .685
c3 1.000 .492
c4 1.000 .679
c5 1.000 .708
e1 1.000 .589
e2 1.000 .455
e3 1.000 .547
e4 1.000 .612
e5 1.000 .503
n1 1.000 .539
n2 1.000 .597
n3 1.000 .644
n4 1.000 .487
n5 1.000 .403
o1 1.000 .597

o2 1.000 .516
o3 1.000 .540
o4 1.000 .530
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 4.508 18.784 18.784 4.508 18.784 18.784
2 2.278 9.490 28.274 2.278 9.490 28.274
3 1.742 7.259 35.533 1.742 7.259 35.533
4 1.320 5.499 41.032 1.320 5.499 41.032
5 1.282 5.341 46.373 1.282 5.341 46.373
6 1.233 5.138 51.511 1.233 5.138 51.511
7 1.059 4.411 55.922 1.059 4.411 55.922
8 .927 3.861 59.784
9 .915 3.812 63.595
10 .851 3.546 67.141
11 .787 3.280 70.421
12 .750 3.124 73.546
13 .724 3.019 76.564
14 .694 2.890 79.454
15 .643 2.681 82.135
16 .608 2.533 84.669
17 .560 2.332 87.001
18 .538 2.243 89.243

19 .529 2.203 91.446
20 .457 1.902 93.349
21 .444 1.848 95.197
22 .425 1.769 96.966
23 .396 1.648 98.614
24 .333 1.386 100.000
Extraction Method: Principal Component Analysis.

Component Matrixa
Component

1 2 3 4 5 6 7
a1 .318 -.142 .288 .594 -.076 .022 .378
a2 -.216 .541 -.092 .112 .374 .225 -.001
a3 -.267 .432 -.326 -.297 .231 .327 .019
a4 .264 -.414 .097 .057 -.506 .169 -.134
a5 .434 .155 -.056 .136 -.193 .345 .002
c1 .552 -.093 .216 -.028 .327 -.065 .095
c2 .303 .104 .470 -.322 .153 -.393 -.284
c3 .372 .152 .191 -.187 .245 -.386 .225
c4 .307 .217 .625 -.183 .046 .322 .084
c5 .194 .015 .704 -.015 .138 .384 -.086
e1 -.543 -.253 .191 .297 .294 .049 .130
e2 .622 -.149 -.040 .173 -.092 -.073 .003
e3 -.496 -.315 .037 .124 .320 .086 -.275
e4 .600 .252 -.135 -.073 -.086 -.136 .373
e5 .531 .401 -.063 .103 .036 -.200 .066
n1 -.470 .364 .104 .310 -.039 -.266 .078
n2 .604 -.307 -.269 .034 .212 .139 .028
n3 -.602 .218 .230 -.095 -.376 -.094 .150
n4 .561 -.306 -.112 -.072 .142 .161 -.119
n5 -.476 .214 .313 .083 -.158 -.008 -.014
o1 .301 .338 .087 .308 -.123 .001 -.523
o2 -.285 -.216 .076 -.327 -.083 .306 .417
o3 -.315 -.484 .059 .250 .323 -.157 .103
o4 .181 .523 -.127 .373 .115 .226 .067
Extraction Method: Principal Component Analysis.
a. 7 components extracted.

Cognitive ability
Factor Analysis
Communalities
Initial Extraction
x1 1.000 .593
x2 1.000 .393
x3 1.000 .371
x4 1.000 .554
x5 1.000 .443
x6 1.000 .525
x7 1.000 .524
x8 1.000 .500
x9 1.000 .504
x10 1.000 .490
x11 1.000 .429
x12 1.000 .214
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %
1 3.061 25.512 25.512 3.061 25.512 25.512
2 1.301 10.839 36.351 1.301 10.839 36.351
3 1.178 9.815 46.166 1.178 9.815 46.166
4 .961 8.006 54.172
5 .909 7.573 61.746
6 .807 6.725 68.471
7 .758 6.319 74.790
8 .707 5.892 80.682
9 .636 5.301 85.984
10 .627 5.228 91.212
11 .551 4.591 95.803
12 .504 4.197 100.000
Extraction Method: Principal Component Analysis.

Component Matrixa
Component

1 2 3
x1 .118 .299 .700
x2 .532 .063 -.325
x3 .424 .038 -.436
x4 .518 .477 -.241
x5 .608 .264 -.061
x6 .546 -.428 .209
x7 .551 -.434 -.176
x8 .601 -.367 .068
x9 .631 .310 .098
x10 .435 -.447 .318
x11 .458 .281 .375
x12 .432 .164 .016
Extraction Method: Principal Component Analysis.
a. 3 components extracted.
Job performance
Factor Analysis
Communalities
Initial Extraction

R1 1.000 .956
R2 1.000 .658
R3 1.000 .610
R4 1.000 .653
R5 1.000 .680
R6 1.000 .645
R7 1.000 .705
R8 1.000 .657
R9 1.000 .793
R10 1.000 .693
R11 1.000 .581
Extraction Method: Principal
Component Analysis.
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 5.219 47.442 47.442 5.219 47.442 47.442
2 1.399 12.719 60.161 1.399 12.719 60.161
3 1.013 9.210 69.372 1.013 9.210 69.372
4 .772 7.018 76.389
5 .568 5.159 81.549
6 .494 4.487 86.036
7 .403 3.663 89.698
8 .333 3.026 92.724
9 .316 2.875 95.600
10 .263 2.394 97.994