FDN123 Statistics Assignment: Graduate Employment Data Analysis

This assignment delves into the statistical analysis of employment data collected from a survey of business school graduates. The analysis includes identifying variables (ID Number, Area, Gender, Satisfaction, Search, and Salary) as quantitative and continuous, creating a histogram to visualize salary distribution, and determining central measures like mode and median to describe salary trends. Descriptive statistics, including average and standard deviation, are calculated for different employment areas (Accounting, Finance, General Management, Marketing/Sales, and Other) and presented alongside side-by-side boxplots for comparison. Pivot tables and bar charts are used to explore the relationship between job satisfaction and employment area, as well as gender distribution across different areas. The assignment concludes by highlighting key findings, such as the popularity of accounting jobs and the salary range in finance, and referencing relevant statistical sources. Desklib provides this assignment as a study resource, offering additional solved assignments and past papers for students.

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Running head: STATISTICS
Statistics
Authors Name
Institutional Affiliation

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STATISTICS
Statistics
Task 1: Variable List
Each variable listed in the given table i.e. ID Number, Area, Gender, Satisfaction, Search
and Salary is quantitative in nature. Since the figures of the identified variables are not observed
as decimals, the series of the data can be considered as a continuous one (CA Sri Lanka, 2019).
Task 2: Histogram
0
5
10
15
20
25
29
34
35
36
37
38
39
40
41
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43
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44
44
45
45
45
45
46
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52
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54
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57
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64
Frequency
Histogram
Figure 1: Histogram
Based on the above figure 1, it can be stated that the shape of the distribution is not
symmetric in nature and skewed in the left as well as the right side (Doane, & Seward, 2011).
However, the distribution is positively skewed rather than the negative side. Though an outlier
has been found in the distribution of salaries, wherein an individual receives 29 thousand salaries
in a month, it can be duly considered to lower the satisfaction limit.

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STATISTICS
Mode 44
Median 47
Table 1: Central Measures
With regard to the above presented table, the central measures of mode and median would
be best to describe the centre of the distribution of salaries. This is owing to the reason that
median shows actual mid value of salaries, whereas the mode presents the highest number of
individuals who receive similar salaries.
Task 3: Descriptive Statistics

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STATISTICS
1 = Accounting 2 = Finance , 3 = General management 4 = Marketing/Sales 5 = Other
Salary Salary Salary Salary Salary
51 49 45 38 51
52 54 45 52 34
51 58 46 49 37
48 62 41 49 45
57 53 41 45 45
51 64 43 47 37
56 53 41 47 46
52 51 48 44 36
50 49 34 35 47
55 48 47 42 38
43 53 45 45 39
49 55 36 48 36
62 58 41 40 50
57 37 42 54 37
51 53 41 44 36
55 52 45 52 44
50 54 45 38 36
52 55 46 37 33
44 58 42 47 35
48 43 37 47 38
47 53 43 42 43
44 47 38 49 34
57 59 48 45 46
46 59 54 39 44
48 60 44 45 46
47 44 44 41 32
44 39 49 42 26
44 54 52 39 29
56 55 40 44 #N/A
54 53 44 44 #N/A
50 46 48 50 #N/A
56 60 35 48 #N/A
51 65 41 47 #N/A
55 51 47 35 #N/A
52 59 45 43 #N/A
51 53 49 44 #N/A
53 53 #N/A 49 #N/A
48 49 #N/A 46 #N/A
44 51 #N/A 49 #N/A
55 41 #N/A 45 #N/A
55 45 #N/A 51 #N/A
42 45 #N/A 42 #N/A
50 63 #N/A 49 #N/A
51 45 #N/A 42 #N/A
53 46 #N/A 48 #N/A
53 55 #N/A 41 #N/A
58 46 #N/A 51 #N/A
45 46 #N/A 50 #N/A
44 59 #N/A 40 #N/A
61 44 #N/A 52 #N/A
43 58 #N/A 47 #N/A
49 46 #N/A 43 #N/A
40 #N/A #N/A 45 #N/A
52 #N/A #N/A 43 #N/A
60 #N/A #N/A 44 #N/A
47 #N/A #N/A 46 #N/A
61 #N/A #N/A 46 #N/A
46 #N/A #N/A 42 #N/A
42 #N/A #N/A 48 #N/A
54 #N/A #N/A 42 #N/A
40 #N/A #N/A 38 #N/A
49 #N/A #N/A 33 #N/A
51 #N/A #N/A 43 #N/A
49 #N/A #N/A 48 #N/A
54 #N/A #N/A #N/A #N/A
59 #N/A #N/A #N/A #N/A
60 #N/A #N/A #N/A #N/A
54 #N/A #N/A #N/A #N/A
51 #N/A #N/A #N/A #N/A
60 #N/A #N/A #N/A #N/A
49 #N/A #N/A #N/A #N/A
54 #N/A #N/A #N/A #N/A
45 #N/A #N/A #N/A #N/A
Average 50.91780822 52.07692308 43.66666667 44.6875 39.2857143
Standard Deviation 5.345697711 6.537512131 4.472135955 4.552602605 6.32957282
Table 2: Descriptive Statistics & Side-by-Side Boxplots

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STATISTICS
Based on the above portrayed table 2, significant differences could be observed in salaries
for each work site. For instance, the standard deviation values stood different from one work site
to other i.e. 50.92 (accounting), 52.08 (finance), 43.67 (general management), 44.69
(marketing/sales) and 39.29 (other).
Task 4: Pivot Table and Bar Chart
Sum of Satisfaction Area
Satisfaction 1 2 3 4 5 Grand Total
1 18 24 16 19 4 81
2 72 38 22 42 30 204
3 54 27 24 54 21 180
4 4 4 24 8 40
Grand Total 148 89 66 139 63 505
Table 3: Pivot Table Showing Satisfaction for Each Employment Area
Data
Satisfaction Frequency % Frequency
1 81 16.04%
2 204 40.40%
3 180 35.64%
4 40 7.92%
Grand Total 505 100.00%
Table 4: Pivot Table Frequency of Satisfaction

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STATISTICS
0
10
20
30
40
50
60
70
1 2
Sum of Genders' Working on Different
Areas
Gender
1
2
3
4
5
Figure 2: Pivot Chart
Area Gender Frequency Sum of Gender
1 1 40 10.67%
2 66 17.60%
1 Total 106 28.27%
2 1 21 5.60%
2 62 16.53%
2 Total 83 22.13%
3 1 18 4.80%
2 36 9.60%
3 Total 54 14.40%
4 1 39 10.40%
2 50 13.33%
4 Total 89 23.73%
5 1 13 3.47%
2 30 8.00%
5 Total 43 11.47%
Grand Total 375 100.00%
Table 5: Pivot Table of Gender Working in Different Areas

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STATISTICS
Based on the above table, differences could be observed amid male and female working in
different areas. For instance, with regard to areas 1, 2, 3, 4 and 5, a difference of 7%, 11%, 5%,
3% and 5% respectively is noticed.
Conclusion
Considering the main obtained findings, it can be inferred that most of the individuals
select accounting jobs, whereas general management and other job profiles are chosen by least
number of people. With respect to salaries, individuals earned a highest of 62 thousand from the
finance jobs.

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STATISTICS
References
CA Sri Lanka (2019). Probability distributions: discrete vs. continuous. Discrete vs. Continuous
Variables. Retrieved from
https://www.casrilanka.com/casl/images/stories/EDBA/chap_8_normal_distribution.pdf
Doane, D. P. & Seward, L. E. (2011). Measuring skewness: A forgotten statistic? Journal of
Statistics Education, 19(2), 1-18.