Description
Notice : when you finish from my assignment i have to submit in turnitin and that website its looking or searching in my assignment words if i taken from any resource of ( internet, students , books, newspaper ...) so you have be careful in that to not become higher then 5%
The topic of motivation to achieve the job satisfaction in private sector.
its project work i fifished but i have the last thing which is analyses the data by SPSS .
i already submit it in the SPSS and i make the table but i would like to use tow way for theanalysis and discussion of factor analysis and anova test.
I will attach file B about the Incentives of the company for the employees
and in the file C its about the what the employees want of the Incentives.
* please go through the attachment to get the details
Unformatted Attachment Preview
Purchase answer to see full attachment
Explanation & Answer
Now find the following attached. I am working on the last one question that of KMO. However I think you should know that your data did not open. Let me work in it will let you know
Now find the following attached. I am working on the last one question that of KMO. However I think you should know that your data did not open. Let me work in it will let you know
Factor Analysis of Employees want of the Incentives
Communalities
Communalities show how much of variance there is between variables. Our analysis indicates
that, 67.1% of the variance in ‘Accommodation’ is accounted for as well as 63.3% of the
variance in ‘communicate with employees’ is also accounted for in Table 1: Communalities
below. All the variables are well over 0.5 indicate the need for further analysis.
Table 1: Communalities
Accommodation
Transportation (From
work to home).
Provide own office for
you.
Health insurance for
me and my family.
Annual Bonus.
Give confidence to
employees
Grant the promotions
to employees.
Discipline reward at
work.
Motivate you by
feeling responsible.
Candidacy for training
courses.
Grant exceptional
vacation.
Conducting honouring
parties.
Participation in
decision-making.
Extractio
Initial
n
1.000
.671
1.000
.772
1.000
.362
1.000
.488
1.000
1.000
.635
.656
1.000
.665
1.000
.719
1.000
.546
1.000
.610
1.000
.696
1.000
.723
1.000
.620
Certificates of
1.000
.603
Appreciation.
Employee transfer
1.000
.598
privileges for a better
job.
Moral support and
1.000
.518
support in special and
emergency situations.
Loans and advances
1.000
.675
made to employees.
The sense of
1.000
.772
appreciation and
respect in the field of
work.
Improve the job
1.000
.771
situation.
Granting of travel
1.000
.615
tickets.
Periodic increments.
1.000
.648
Education and
1.000
.751
development the
employees.
Delegation of powers
1.000
.722
and granting of powers.
Put decorations on the
1.000
.648
plate of honour.
Reduce working hours
1.000
.477
to relieve pressure on
workers.
Communicate with
1.000
.636
employees.
Extraction Method: Principal Component
Analysis.
Total Variance Explained
Eigenvalue reflects the number of extracted factors whose sum should be equal to number of
items which are subjected to factor analysis. The next item shows all the factors extractable from
the analysis along with their eigenvalues. From the Eigenvalue table below, it has been divided
into three sub-sections, i.e. Initial Eigen Values, Extracted Sums of Squared Loadings and
Rotation of Sums of Squared Loadings. But for our analysis and interpretation purpose we are
only concerned with Extracted Sums of Squared Loadings. So from the table below, we take note
that the first factor accounts for 45.763% of the variance, the second accounts for 7.808%, the
third accounts for 6.050% and the fourth accounts for 4.224% of the total variance. All the
remaining factors are not significant as indicated in Table 2 below.
Table 2: Total Variance Explained
Component
1
2
3
4
5
6
dim
7
ensi
8
on0
9
10
11
12
13
14
Total
11.898
2.030
1.573
1.098
.983
.929
.799
.725
.640
.629
.603
.540
.491
.408
Initial Eigenvalues
% of
Cumulative
Variance
%
45.763
45.763
7.808
53.571
6.050
59.621
4.224
63.844
3.782
67.626
3.572
71.198
3.073
2.790
2.460
2.418
2.320
2.078
1.889
1.568
74.271
77.060
79.520
81.939
84.258
86.336
88.225
89.793
Extraction Sums of Squared Loadings
% of
Cumulative
Total
Variance
%
11.898
45.763
45.763
2.030
7.808
53.571
1.573
6.050
59.621
1.098
4.224
63.844
15
16
17
18
19
20
21
22
23
.390
.367
.311
.275
.251
.229
.199
.153
.151
1.500
1.412
1.194
1.059
.965
.881
.766
.589
.579
91.293
92.706
93.900
94.959
95.925
96.806
97.572
98.161
98.741
24
25
.132
.109
.507
.419
99.248
99.666
26
.087
.334
100.000
Extraction Method: Principal Component Analysis.
Component Matrix
The table 3 below shows the loadings (extracted values of each item under 4 variables) of the 26
variables on the four factors extracted. The higher the absolute value of the loading, the more the
factor contributes to the variable. From the analysis, 4 variables were extracted from the 26
variables according to most important items which similar responses in component 1, 2, 3 and 4
as indicated in Table 3 below. All the values which are less than 0.5 should be suppressed to
make the reading easier.
Table 3: Component Matrix
Accommodation
Transportation (From
work to home).
Provide own office for
you.
Health insurance for
me and my family.
1
.291
.244
Component
2
3
.657
.393
.717
.440
4
.005
.072
.577
-.005
.050
.160
.651
-.119
-.172
.143
Annual Bonus.
Give confidence to
employees
Grant the promotions
to employees.
Discipline reward at
work.
Motivate you by
feeling responsible.
Candidacy for training
courses.
Grant exceptional
vacation.
Conducting honoring
parties.
Participation in
decision-making.
Certificates of
Appreciation.
Employee transfer
privileges for a better
job.
Moral support and
support in special and
emergency situations.
Loans and advances
made to employees.
The sense of
appreciation and
respect in the field of
work.
Improve the job
situation.
Granting of travel
tickets.
Periodic increments.
Education and
develo...