Business Research Report: Pakistani Bank Workforce Analysis

This business research management report provides a comprehensive analysis of a Pakistani bank's workforce, incorporating both quantitative and qualitative assessments. The quantitative section utilizes statistical tools like histograms, descriptive statistics, ANOVA, and chi-square tests to examine age distribution, ethnic proportions, average income, the relationship between years worked and salary, salary variations across skill categories, and gender differences in meeting attendance. The qualitative part delves into work-family conflict, exploring the impact of joint families, levels of family support for working women, and challenges related to financial permissions. The study reveals insights into the dynamics of the Pakistani banking sector, highlighting the interplay of statistical findings, cultural influences, and work-life balance considerations.

Business Research Management

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
PART A: QUANTITATIVE ASSESSMENT.................................................................................1
1. Presenting the age distribution of workforce...........................................................................1
2. Stating the proportion of employees belongs to each ethnic group.........................................3
3. Highlighting average income of employees............................................................................3
4. Presenting the extent to which number of years worked related to salary..............................4
5. Analyzing the extent to which average salaries of the different skill categories vary.............6
6. Presenting difference between the proportion of males and females who attended the firm’s
meeting last month.......................................................................................................................7
PART B: QUALITATIVE ASSESSMENT..................................................................................10
Theme 1: Impact of joint families on work and personal life....................................................11
Theme 2: Moderate level of support is given by the families towards the job (women)..........12
Theme 3: Complication pertaining to taking permission with the reference to Pakistani women
...................................................................................................................................................12
CONCLUSION..............................................................................................................................13
REFERENCES..............................................................................................................................14

INTRODUCTION
Business research management implies for the systematic inquiry which in turn helps in
solving specific business problems and thereby assists in developing suitable framework. The
present report is based on two different parts which in turn shed light on both quantitative and
qualitative evaluation. Hence, fist part will provide deeper understanding about the manner in
which different statistical tools help in analyzing data set. Further, second part will highlight
qualitative aspects regarding work-family conflict in the context of Pakistani Bank’s.
PART A: QUANTITATIVE ASSESSMENT
1. Presenting the age distribution of workforce

Row Labels Count of age
0-9 1
10-19 4
20-29 17
30-39 14
40-49 16
50-59 15
60-69 3
Grand Total 70
Interpretation: Tabular presentation and histogram shows that out of 70, 17 personnel
fall into the age group of 20-29 years. On the other side, employees who are in the age range or
group of 40-49 years old implies for 16. Further, 15 personnel having age between 50-59 years
which in turn shows that majority of the workforce is old.

2. Stating the proportion of employees belongs to each ethnic group
Interpretation: The above mentioned bar chart presents that proportion of African
employees are higher over other ethnic groups. Thereafter, in comparison to Asian and West
Indian, proportion of white personnel is higher. Further, graphical presentation clearly entails
that in against to Asian personnel; employees who fall into the category of West Indian are
higher.
3. Highlighting average income of employees
In order to analyze the average income earns by personnel is determined through the
means of descriptive analysis tool. Hence, descriptive statistics pertaining to average income of
employees (n = 70) is as follows:

Descri
ptive
Statist
ics
N Range Minimu
m
Maximu
m
Mean Std.
Deviatio
n
Variance Skewness Kurtosis
Statisti
c
Statisti
c
Statistic Statistic Statisti
c
Std.
Error
Statistic Statistic Statisti
c
Std.
Erro
r
Statisti
c
Std.
Erro
r
Income 68 4600 5900 10500 7819.1
2
121.01
9 997.947 995897.71
7 .370 .291 -.294 .574
Valid N
(listwise
)
68
Interpretation: The above depicted descriptive analysis presents that average income of
personnel, when n=70, implies for 7819.12 significantly. Along with this, results of evaluation
present that minimum and maximum income of personnel accounts for 5900 & 10500
respectively.
4. Presenting the extent to which number of years worked related to salary
Linear regression
Hypothesis
H0 (Null hypothesis): There is no significant difference in the mean values of salary and
number of years worked.
H1 (Alternative hypothesis): There is a significant difference in the mean values of salary and
number of years worked.
Regression
Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .340a .115 .102 945.711
a. Predictors:
(Constant), Years
Worked
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 7696787.937 1 7696787.937 8.606 .005b
Residual 59028359.122 66 894369.078
Total 66725147.059 67
a. Dependent
Variable:
Income
b. Predictors:
(Constant),
Years Worked
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 7410.810 180.346 41.092 .000
Years Worked 31.841 10.854 .340 2.934 .005
a. Dependent
Variable:
Income

Interpretation: By doing statistical analysis, it has found that value of R and R square
accounts for .34 & .11 significantly. Considering this, it can be stated that moderate relationship
exists between the two variable undertaken for the study such as salary and number of years
worked. Further, ANOVA table presents that P<0.05 which means alternative hypothesis is true
and other one is rejected (Linear Regression Analysis using SPSS Statistics, 2017). Hence, it can
be depicted that salaries of personnel are highly related to the number of years worked.
5. Analyzing the extent to which average salaries of the different skill categories vary
One way ANOVA
Hypothesis
H0 (Null hypothesis): There is no significant difference in the mean values of average salaries of
personnel with different skills.
H1 (Alternative hypothesis): There is a significant difference in the mean values of average
salaries of personnel with different skills.
Descriptiv
es
Income
N Mean Std.
Deviation
Std. Error 95% Confidence Interval for
Mean
Minimum Maximum
Lower Bound Upper Bound
unskilled 14 7628.57 730.046 195.113 7207.06 8050.09 6500 8800
semi-skilled 18 7288.89 741.135 174.687 6920.33 7657.45 5900 8800
fairly skilled 20 8095.00 931.029 208.185 7659.26 8530.74 6200 9500
highly skilled 16 8237.50 1267.478 316.869 7562.11 8912.89 6400 10500
Total 68 7819.12 997.947 121.019 7577.56 8060.67 5900 10500

ANOVA
Income
Sum of Squares df Mean Square F Sig.
Between Groups 9891797.852 3 3297265.951 3.713 .016
Within Groups 56833349.206 64 888021.081
Total 66725147.059 67
Means Plots

Interpretation: Results of One way Anova shows that mean or average income of
personnel from skilled to unskilled vary significantly. Further, ANOVA table shows that
significance value is 0.016 respectively. Referring such result it can be depicted that statistical
significant difference takes place in the mean salaries of personnel having varied skills.
6. Presenting difference between the proportion of males and females who attended the firm’s
meeting last month
Chi-square test or Crosstabs
Hypothesis
H0 (Null hypothesis): There is no significant association between gender and aspects of
attending firm’s meeting held on last month.
H1 (Alternative hypothesis): There is no significant association between gender and aspects of
attending firm’s meeting held on last month.
Case
Processing
Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
Gender * attended meeting 70 100.0% 0 0.0% 70 100.0%
Gender *
attended
meeting
Crosstabulation
attended meeting Total
yes no
Gender male Count 21 18 39
% within Gender 53.8% 46.2% 100.0%

% within attended meeting 58.3% 52.9% 55.7%
% of Total 30.0% 25.7% 55.7%
female
Count 15 16 31
% within Gender 48.4% 51.6% 100.0%
% within attended meeting 41.7% 47.1% 44.3%
% of Total 21.4% 22.9% 44.3%
Total
Count 36 34 70
% within Gender 51.4% 48.6% 100.0%
% within attended meeting 100.0% 100.0% 100.0%
% of Total 51.4% 48.6% 100.0%
Chi-Square
Tests
Value df Asymp. Sig. (2-
sided)
Exact Sig. (2-
sided)
Exact Sig. (1-
sided)
Pearson Chi-Square .206a 1 .650
Continuity Correctionb .045 1 .831
Likelihood Ratio .206 1 .650
Fisher's Exact Test .810 .416
Linear-by-Linear Association .203 1 .652
N of Valid Cases 70
a. 0 cells (0.0%)
have expected
count less than 5.
The minimum
expected count is
15.06.
b. Computed only
for a 2x2 table
Symmetric Measures
Value Approx. Sig.
Nominal by Nominal Phi .054 .650

Cramer's V .054 .650
N of Valid Cases 70
a. Not assuming the null
hypothesis.
b. Using the asymptotic
standard error assuming
the null hypothesis.
Interpretation: Statistical evaluation shows that person chi-square value is .20
respectively which in turn higher than standard figure such as 0.05. Referring such as result it
can be mentioned that no significant association takes place between gender and aspect related to
the presence in the firm’s meeting of last month (Cronk, 2016). Overall evaluation presents that
both men and women attend meetings equally.