Business Research Methods

This document discusses the analysis of a survey conducted to determine the health status of male employees above 38 years. It includes the analysis of age distribution, health status, average weight and height, linear regression model, hypothesis tests, and conclusion. The document also includes an interview extract discussing the role of family, husband, and society in determining the situation of female entrepreneurs.

BUSINESS RESEARCH METHODS
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PART A
Introduction
A survey has been conducted so as to determine the health status of the company’s male
employees who have a age in excess of 38 years. IBM SPSS is the data analysis tool which
has been used for carrying out data analysis. Taking into consideration the software based
outputs, responses are provided in the report with regards to the questions posed.
.
Analysis
1) The age distribution of the surveyed employees is summarised using the histogram
indicated as follows.
The first observation that can be drawn is that the shape of the histogram is asymmetric since
the maximum value tends to exist at the edge of the histogram rather than the middle of the
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histogram. The concentration of age values on the lower end is quite evident which implies
that some of the employees with age as high as 85 to 90- years would be outliers. Owing to
presence of these outliers on the right of the mean, it would be correct to conclude that the
presence of positive skew is detected. Since normal distribution requires no skew, hence the
age distribution cannot be referred to as normal distribution (Eriksson and Kovalainen, 2015).
2) The following pie chart tends to represent the health status of the surveyed employees.
.
From the above, it can be inferred that about 27% of the employees assessed their current
health as excellent. Further, about 50% of the employees who took part in the survey believed
that their health status was good. There were lower than 4% employees who believed that
their current health status was poor. There were some employees who did not know about the
current status of their health but this represented about 1% of total employees that
participated in the survey.
3) The required output to indicate the average weight and height of the sample is shown
below.
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Hence, it could be concluded that mean male employee height based on sample is 172.406
cm while the corresponding average weight is 75.295 kg.
4) The linear regression model needs to be estimated between age and lung function. The
independent variable would be defined as age while the defined variable would be lung
function represented by HYFEV. The linear regression output derived from IBM SPSS is
indicated as follows.
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The requisite relationship for the two variables may be captured using the equation indication
as follows.
The first observation from the above equation is the negative sign of the slope coefficient
which would hint at the negative correlation between the two variables which is not
surprising. Considering the regression output, it is evident that slope coefficient of age
variable is significant owing to p value being calculated as 0.000. Owing to slope being
significant, the linear regression model would also be significant which is also confirmed
from the ANOVA output (Fehr and Grossman, 2013).
The coefficient of determination is 0.37 which highlights that changes in age can only explain
37% of the changes in HYFEV (lung function). Since a majority amount of the changes in
the dependent variable remain unexplained, it makes sense for insertion of additional
independent variables for improvement in predictive power of the linear regression model
(Flick, 2015).
5) For performing hypothesis test, the requisite hypotheses need to be listed as carried out
below.
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Assumed significance level = 5%
T statistic based hypothesis test would be suitable as for neither of the two variables, the
population standard deviation is known (Hillier, 2016). The relevant output for the two
sample t test is illustrated as shown below.
P value (0.00) < Significance level (0.05)
Hence, null hypothesis would be rejected in favour of alternate hypothesis. Thus, it is
apparent that for the two social classes, the average lung function as captured by HYFEV is
different
6) For performing hypothesis test, the requisite hypotheses need to be listed as carried out
below.
Assumed significance level = 5%
Chi –square statistic is an appropriate choice as the variables presented are categorical. The
SPSS output for the relevant test is indicated as follows.
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P value (0.891) > Significance level (0.05)
Hence, null hypothesis would not be rejected in favour of alternate hypothesis. Thus, it is
apparent that no relation of significance is present between the mental state of male
employees and smoking (Saunders, Lewis and Thornhill, 2016).
Conclusion
Based on the results obtained above, it is fair to describe the distribution of age as non-
normal. Also, the self- assessment of health of employees does not raise any concern owing
to limited cases where health was termed as poor. Additionally, negative linear relation tends
to exist between age of employee and corresponding lung function. Besides, the average lung
function across the two social classes tends to differ significantly. Further, male employees
mental health and smoking does not seem related.
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References
Eriksson, P. and Kovalainen, A. (2015). Quantitative methods in business research, 3rd ed.
London: Sage Publications.
Fehr, F. H., and Grossman, G. (2013). An introduction to sets, probability and hypothesis
testing 3rd ed. Ohio: Heath.
Flick, U. (2015). Introducing research methodology: A beginner's guide to doing a research
project, 3rd ed.New York: Sage Publications.
Hillier, F. (2016). Introduction to Operations Research. 4th ed. New York: McGraw Hill
Publications.
Saunders, M., Lewis, P. and Thornhill, A. (2016) Research Methods for Business Students.
7th ed. Harlow: FT Prentice Hall.
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PART B
In this case, the interview extract of a Pakistani female has been provided who works in a
bank. From this interview, based on the frequency of the usage of these, some keywords can
be identified which are used quite often indicating that they have a critical influence on the
overall situation (Saunders, Lewis and Thornhill, 2016). Two such words have indeed been
identified in the form of “Family” and “Husband” and hence it seems that these two levers
would play a crucial role in determining the female entrepreneur situation in any given
setting.
To take these forward, it is imperative to list down the themes and establish relation with the
sub-themes as has been done as follows.
Identification of Themes & Sub-Themes
Family Type
The conflict between work and personal life is clearly apparent in the joint family setting.
Having more family members helps with regards to managing daily chores but these are other
issues that potentially have adverse impact on the female entrepreneurs’ situation. A key
issue would be that rewards cannot be garnered by the women entrepreneur as the same needs
to be divided amongst the various families in the joint family as high disparity in wealth and
progress is not tolerated. Further, considering the collective view in a joint family,
individualism takes a back seat slowing down decision making and presents an unfavourable
environment to assume risks by initiating business.
In a nuclear family setting, it would be easier to take risk as the returns would be more
lucrative owing to independence of spending the same without any interference from distant
family members. Also, considering that less members are involved in making any decision,
hence it can be made more effectively in a quick manner. This is expected to improve the
female entrepreneur situation.
Support Mechanism
Considering the hurdles that any entrepreneur has to face in business, the situation would be
dependent on the extent of support from key stakeholders. In this regards, the following sub-
themes emerge based on the analysis of the interview.
Husband’s Role
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The husband plays a crucial role for a married woman which is especially the case in male
dominated societies. For every decision that women takes, it needs to be consulted and
garner approval from the husband. There is no control on the resource spend even if the
female has arranged the same on her own or earned it. Thus, in such a setting starting and
flourishing in a business without husband support is virtually impossible. However, the role
of husband and associated support may water down in a society where equality of gender is
practiced both in letter and spirit.
Society’s Role
The society also needs to provide support to female entrepreneurs by considering them role
models and providing the requisite financial and non-financial support. However, in a male
dominated society, this is unlikely to happen considering that gender roles are expected to be
strictly followed. Also, in such societies, women are expected to look after husband and
children and thereby remain within the confines of domestic affairs and not meddle with
commercial affairs. Women entrepreneurs in such societies are treated as anomalies which
adversely impacts the situation.
Learning Derived
Based on the above discussion, it may be concluded that three actors in the form of husband,
society and family type play a crucial role in determining the situation of female
entrepreneurs in any given region. From the perspective of a female entrepreneur, it is better
is the underlying society is not male centric which would lower the interference from
husband and also ensure support from various actors such as family and society. This would
increase the chances of success for women entrepreneur and lead to situation improvement.
Relevance to Study
The objective of exploratory study is to explore potential variables which can determine the
variable of interest and hence paves way for formulation of hypothesis. To determine the
situation of women entrepreneurs in Russia, the following relevant independent variables
ought to be considered (Hair et. al., 2015).
 Male centric nature of society ( 1 to 5 rating).
 Acceptance of females as entrepreneurs in Russia (Strong disapproval, Mild
Approval, Neutral, Mild Approval, Strong Approval).
 Family Type (Captured by dummy variable)
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Considering the variables cited above, data would be collected from the sample obtained
from the population of interest (i.e. female entrepreneurs) and further hypothesis testing
should be performed so that theory formation can be facilitated (Taylor and Cihon, 2014).
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References
Hair, J. F., Wolfinbarger, M., Money, A. H., Samouel, P.,and Page, M. J. (2015). Essentials
of business research methods, 4th ed.New York: Routledge
Taylor, K. J. and Cihon, C. (2014). Statistical Techniques for Data Analysis, 2nd
ed. .Melbourne: CRC Press
Saunders, M., Lewis, P. and Thornhill, A. (2016) Research Methods for Business Students.
7th ed. Harlow: FT Prentice Hall.
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