Business Information Systems - Doc

Running head: BUSINESS INFORMATION SYSTEMS
Business Information Systems
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BUSINESS INFORMATION SYSTEMS 1
Table of Contents
Data analysis:.............................................................................................................................2
Assignment 9..........................................................................................................................2
Assignment 9. a).................................................................................................................2
Assignment 9. b)................................................................................................................2
Assignment 9. c).................................................................................................................3
Assignment 9. d)................................................................................................................4
Assignment 10. Conclusion of data analysis:........................................................................6
References:.................................................................................................................................8
Table of Figures
Figure 1: Histogram of average increment.................................................................................3
Figure 2: The distribution of average increment rates with respect to the types of genders......4
Figure 3: Residual plot and normal probability plot of linear regression model for female
employees...................................................................................................................................6
Figure 4: Residual plot and normal probability plot of linear regression model for male
employees...................................................................................................................................7

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Table of Tables
Table 1: Table of frequency distribution of average increment.................................................3
Table 2: Table of location measures of average increment of females and males.....................4
Table 3: Linear regression model of Start salary and Current salary for females......................5
Table 4: Linear regression model of Start salary and Current salary for males.........................6

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Data analysis:
Assignment 9.
Assignment 9. a)
The formula used for making “Length Empl” column is given as-
“Length Empl” = (2014 - Start Yr) ……………………………………. (1)
(Working period is assumed till the end of 2014).
The formula used for making “Avg Incr” column is given as -
“Avg Incr” = ( Current Salary−Start Salary
Length Empl ) ……………………………... (1)
Assignment 9. b)
Table 1: Table of frequency distribution of average increment
Bin
Frequen
cy
0 1
5000 88
10000 9
15000 0
20000 2
25000 0
More 0
Figure 1: Histogram of average increment

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0 5000 10000 15000 20000 25000 More
0
10
20
30
40
50
60
70
80
90
100
Histogram of Avearge Increment
Classes of Average Increment
Frequency
The histogram indicates that the distribution of average salary increase is rightly
skewed. The distribution is also known as a positively skewed distribution. For this
distribution, the modal value is greater than median and mean value (Huck, Cormier and
Bounds 1974). Again, median of the distribution is greater than mean. Therefore, it could be
interpreted that the distribution is totally asymmetric. Most of the average increment rate
belongs to the group of class width $0 to $5000.
Assignment 9. c)
Table 2: Table of location measures of average increment of females and males
Gender
Avg Incr of
females
Avg Incr of
males
Minimu
m 144.00 -760.00
Q1 1219.943 1403.526
Median 1384.29 1509.00
Q3 1467.828 1612.782
Maximu
m 15960.00 15480.00
Figure 2: The distribution of average increment rates with respect to the types of
genders

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Avg Incr of females Avg Incr of males
0
200
400
600
800
1000
1200
1400
1600
1800
Distribution of gender wise average increment
Gender
Average Increment
The grouped box plot or side by side box plot refers that the range of average
increment rate of salary or wages is very large for both the male employees and female
employees. The 50% samples are concentrated in a very small range of current salary of both
the genders. Surely, we can find the outliers for both the distributions. It could be easily
observed as per range. The range is the difference of maximum and minimum value of any
data set. The spread in terms of range of the average increment rates of male employees is
depicted greater than female employees in the graph. The average increment rate of middle-
most half of the employees is higher for males than females. These average increment
amounts of the employees are accounted as the values of interquartile range.
Assignment 9. d)
It is a fact of determination whether salary increment of male employees is greater
than males or not. The two variables that are considered here- “Start Salary” and “Current
Salary”. For this analysis, the researcher used the simple linear regression model It helps to
find the significance of linear association between a dependent variable and an independent
variable. In this case, the independent variable is “Start salary” and the dependent variable is
“Current salary” (Härdle and Simar 2012). Two simple linear models are executed here for
testing the proposition whether the salary increases for females been lesser than those for
males or not.

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Simple Linear regression models for male employees and female employees predicting the
rate of salary increment:
Table 3: Linear regression model of Start salary and Current salary for females
Simple Linear Regression Model for Females
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.760877
R Square 0.578934
Adjusted R
Square 0.564898
Standard
Error 8661.939
Observation
s 32
ANOVA
df SS MS F
Significance
F
Regression 1 3.09E+09
3.09E+0
9
41.2476
5
4.30836E-
07
Residual 30 2.25E+09
7502919
2
Total 31 5.35E+09
Coefficient
s
Standard
Error t Stat P-value Lower 95%
Upper
95%
Intercept 19804.76 6217.111 3.185524
0.00336
2
7107.72457
7
32501.793
8
Start Salary 0.949268 0.147805 6.422434 4.31E-07 0.64740993
1.2511262
8
Figure 3: Residual plot and normal probability plot of linear regression model for
female employees

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30000 40000 50000 60000 70000 80000
-20000
-10000
0
10000
20000
Start Salary Residual
Plot
Start Salary
Residuals
0 20 40 60 80 100 120
0
20000
40000
60000
80000
100000
Normal Probability
Plot
Sample Percentile
Current Salary
The linear equation for predicting the increment of “Current Salary” of the female employees
is–
Current salary = 19804.76 + 0.949268*Start salary (It 2015)
Table 4: Linear regression model of Start salary and Current salary for males
Simple Linear Regression Model for Males
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.745124
R Square 0.555209
Adjusted R
Square 0.54847
Standard
Error 6291.643
Observations 68
ANOVA
df SS MS F
Significanc
e F
Regression 1
3.26E+0
9 3.26E+09 82.3844 3.18E-13
Residual 66
2.61E+0
9 39584776
Total 67
5.87E+0
9
Coefficient
s
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Intercept 33118.57 3408.196 9.71733
2.36E-
14 26313.88
39923.249
6
Start Salary 0.774997 0.085384 9.076585
3.18E-
13 0.604522
0.9454722
5

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Figure 4: Residual plot and normal probability plot of linear regression model for male
employees
30000
40000
50000
60000
70000
80000
-30000
-20000
-10000
0
10000
20000
Start Salary Residual
Plot
Start Salary
Residuals
0 20 40 60 80 100 120
0
20000
40000
60000
80000
100000
120000
Normal Probability Plot
Sample Percentile
Current Salary
The linear equation for increment of “Current Salary” of male employees–
Current salary = 33118.57 + 0.774997 *Start salary
The role of slopes or beta-value is important in this regard. It is obtained as per both
the linear equations that per unit growth of “Starting salary”, the “Current salary” also would
be enhanced in both the linear models. However, for male employees, for 1-unit growth of
“Starting salary”, the “Current salary” would increase by 0.774 units. For female employees,
due to 1-unit growth of “Starting salary”, the “Current salary” would enhance by 0.949 units
(Holmes and Rinaman 2014). Hence, the increase rate of salary is higher for female
employees than the increase rate of salary of male employees. Hence, the proposition that the
salary increment of the female employees is than salary increment of male employees is
found to be false.
Assignment 10. Conclusion of data analysis:
The average current salary is not much greater of male employees of the company
than the female employees of the company. The graphs and numerical summaries support
that fact. However, it is 95% evident that as per hypothesis testing, the mean “Current
Salary” of male employees is almost equal to the mean “Current salary” of female
employees. The female employees serve mostly in department 3 while male employees serve
mostly in position 2 with highest frequencies. The number of male employees is highest in
department 2 (25) and lowest in department 1 and 3 simultaneously (13). The female
employees serve maximum in department 3 (11) and serve minimum in department 2 (5). The
females work minimum in department 1 (11) and males work maximum in department 2 (7).
Therefore, department 2 is favorable for male employees whereas department 3 is favorable
for female employees.
The frequencies of average increment rate are highest in the class of income level $0-
$5000. The average increment amount is little greater for male workers. However, the rate of
increment found greater in females than males. As per amount of current salary, both the
male and female employees prefer to work in position 2 and both of these two genders
receive lesser salary in position 3.

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References:
Härdle, W. and Simar, L., 2012. Applied multivariate statistical analysis.
Holmes, W.H. and Rinaman, W.C., 2014. Simple Linear Regression. In Statistical Literacy
for Clinical Practitioners(pp. 341-366). Springer, Cham.
Huck, S.W., Cormier, W.H. and Bounds, W.G., 1974. Reading statistics and research (pp.
74-102). New York: Harper & Row.
It, X., 2015. Simple linear regression.