In this research for qualitative data I have selected
gender and in quantitative data I have selected Intrinsic Factor.
Reason for selecting Data
The purpose for selecting gender and intrinsic factor is to see the relationship between the gender & the intrinsic factor, i.e. how the intrinsic value changes as the gender change.
Intrinsic Factor
Intrinsic factor shows the personal job satisfaction, intrinsic rewards include the responsibilities, challenges, or feedback related to self satisfaction. Below are some findings of the Intrinsic factors.
Case Processing Summary
Cases
Included
Excluded
Total
N
Percent
N
Percent
N
Percent
Intrinsic
50
100.0%
0
.0%
50
100.0%
a. Limited to first 100 cases.
Case Summaries
Intrinsic
1
5.50
2
5.50
3
5.20
4
5.30
5
4.70
6
5.50
7
5.20
8
5.30
9
4.70
10
5.40
11
6.20
12
5.20
13
5.30
14
4.70
15
5.40
16
6.20
17
5.20
18
5.30
19
5.30
20
4.70
21
5.50
22
5.20
23
5.30
24
4.70
25
5.40
26
6.20
27
5.20
28
5.30
29
4.70
30
5.40
31
6.20
32
5.20
33
5.30
34
4.70
35
5.30
36
4.70
37
5.50
38
5.20
39
4.70
40
5.50
41
5.20
42
5.30
43
4.70
44
5.40
45
6.20
46
5.20
47
5.30
48
4.70
49
5.40
50
6.20
Total
N
50
Mean
5.2920
Median
5.3000
Grouped Median
5.2857
Std. Error of Mean
.06133
Sum
264.60
Minimum
4.70
Maximum
6.20
Range
1.50
First
5.50
Last
6.20
Std. Deviation
.43370
Variance
.188
a. Limited to first 100 cases.
Statistics
Intrinsic
N
Valid
50
Missing
0
Mean
5.2920
Std. Error of Mean
.06133
Median
5.3000
Mode
4.70a
Std. Deviation
.43370
Variance
.188
Skewness
.590
Std. Error of Skewness
.337
Range
1.50
Minimum
4.70
Maximum
6.20
Sum
264.60
a. Multiple modes exist. The smallest value is shown
Intrinsic
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
4.7
11
22.0
22.0
22.0
5.2
10
20.0
20.0
42.0
5.3
11
22.0
22.0
64.0
5.4
6
12.0
12.0
76.0
5.5
6
12.0
12.0
88.0
6.2
6
12.0
12.0
100.0
Total
50
100.0
100.0
Results
Overall the above calculations shows that the mean is 5.29 in case of intrinsic factor & the standard deviation is .434 in a sample size of 50 people, as the standard deviation is very low this shows that most of the people are satisfied with their jobs.
Gender
Although it's a qualitative measure & here test of central tendencies cannot be applied, as gender here only represents 1 as male and 2 as female, these calculation shows that why central of tendencies cannot be applied on this data.
Case Processing Summary
Cases
Included
Excluded
Total
N
Percent
N
Percent
N
Percent
Gender
50
100.0%
0
.0%
50
100.0%
a. Limited to first 100 cases.
Case Summaries
Gender
1
1.00
2
1.00
3
1.00
4
1.00
5
1.00
6
2.00
7
2.00
8
2.00
9
2.00
10
2.00
11
1.00
12
2.00
13
2.00
14
2.00
15
2.00
16
1.00
17
1.00
18
2.00
19
2.00
20
1.00
21
1.00
22
2.00
23
2.00
24
2.00
25
1.00
26
2.00
27
2.00
28
2.00
29
2.00
30
1.00
31
1.00
32
2.00
33
2.00
34
2.00
35
2.00
36
1.00
37
1.00
38
1.00
39
1.00
40
2.00
41
2.00
42
2.00
43
2.00
44
2.00
45
1.00
46
2.00
47
2.00
48
2.00
49
2.00
50
1.00
Total
N
50
Mean
1.6200
Median
2.0000
Grouped Median
1.6200
Std. Error of Mean
.06934
Sum
81.00
Minimum
1.00
Maximum
2.00
Range
1.00
Std. Deviation
.49031
Variance
.240
a. Limited to first 100 cases.
Statistics
Gender
N
Valid
50
Missing
0
Mean
1.6200
Std. Error of Mean
.06934
Median
2.0000
Mode
2.00
Std. Deviation
.49031
Variance
.240
Skewness
-.510
Std. Error of Skewness
.337
Range
1.00
Minimum
1.00
Maximum
2.00
Gender
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
1
19
38.0
38.0
38.0
2
31
62.0
62.0
100.0
Total
50
100.0
100.0
Importance of Charts & graphs
By using charts & graphs one can explain better, charts & graphs allow people to quickly examine and spot the trends, it normally gives the actual picture of the data in a summarized form.
Importance of Variance & Standard Deviation
These are the measure of statistics, Standard Deviation & Variance is an important tool to check the variation of the data, its shows how much the data ...