Business Analysis Report of Cuteen Employees Data - Deakin MIS171

This business analysis report examines Cuteen employee data to address questions from the Human Resources Manager. It includes calculations and interpretations related to average working hours, employee retention likelihood, and differences between male and female employees. The report validates or refutes claims made by senior management using statistical analysis and provides sample size calculations for future studies. Correlation between working hours and salary, as well as years of work experience, are also explored through regression analysis. This document is available on Desklib, where students can find a variety of past papers and solved assignments.

Running head: BUSINESS ANALYSIS REPORT
Business Analysis Report
Name of the Student:
Name of the University:
Author Note:

1BUSINESS ANALYSIS REPORT
Part 2
Report for problem 1.
(a) The estimate mean of working hours spent by all Cuteen employees holds the value
45.26888889  45. It suggests that the entire data is centred at the single value 45. It
shows that most of the employees are working in the company with an average of 45
working hours. However, if there is presence of outliers or any extreme value then the
interpretation of mean is violated.
(b) The estimate of the proportion of all Cuteen employees who are very likely to stay in
their job is obtained by using a Pivot table and chart. The number of employees whose
Stayorg variable’s value is “very likely” is first calculated and the count is divided by
450 which is the total number of Cuteen employees. Then, the pie chart and bar chart
are plotted which show the percentage of very likely as 17.78%. Thus the estimate of
the proportion can be written as 0.1778.
Report for problem 2.
According to the calculation of problem 1(a), the average value of working of the
Cuteen employees is 45. Thus it is less than the industry average working hours and the claim
of the senior management is valid and true. Comparison between the mean values can be
taken as the proof of the validity of the claim.
Report for problem 3.
The senior management’ belief on the proportion of the employees who like to stay in
the job is to be checked from the calculation performed on the Excel sheet. From the graph
(bar chart and pie chart), it is clearly seen that the percentage of proportion of likely to stay

2BUSINESS ANALYSIS REPORT
employees is 42.22% which is 2.2% more than 40%. Thus, the senior management’s claim is
true in this case and the claim is mathematically valid.
Report for problem 4.
The significant difference of the mean number of working hours between male and
female employees can be represented by pivot table with the sum of working hours based on
males and females. First, the calculation of descriptive statistics is calculated separately for
all males and females. Then, the pivot table is evaluated which shows that sum of hours
worked for males is 61.02% and that for female sis 38.90%. Thus, it can be concluded that
there is significant difference between these two sums of hours worked.
Report for problem 5.
The sample size helps to determine how many observations one needs to be estimated
for any parameter. The size of the sample size depends mainly on three factors-
i. Magnitude of the margin of error as larger the sample size, smaller is the margin of
error.
ii. Confidence level; larger confidence level requires larger sample size.
iii. The variability; if the standard deviation is large, then sample size is required to be
large.
The sample size is calculated using the formula n = σ2z2/m2; where z = confidence
coefficient, σ = standard deviation, m = margin of error.
(a) Thus, for the mean number of working hours for all Cuteen employees, the sample
size should be, n = 96.27274932 * (1.96)2 /22 ≈ 92.

3BUSINESS ANALYSIS REPORT
(b) The sample size, required to calculate the proportion who are very likely to stay
with the job, is n ≈ 49.
Report for problem 6.
The scatter plot shows quite good correlation between working hours and salary.
Also, there is positive correlation between the working hours and wok years. The regression
equation is given as Y = 42.25530642 + 0.138186 X1 + 0.035420 X2 + 0.041514 X3. It shows
that for one unit change in X1, X2, and X3, Y changes by 0.138 units, 0.0354 units, and 0.0415
units respectively.