BUACC5931: Research and Statistical Methods of Business Report

This report delves into the application of research and statistical methods within a business context, specifically examining a study on job insecurity and its effects on employee well-being. The report begins by explaining the concept of sampling, highlighting the rationale for a large sample size (21%) in the original research, and discussing the benefits such as increased accuracy, outlier identification, and reduced margin of error. The simple random sampling method used in the research is then analyzed, outlining its advantages (representation of the population, ease of use, reduced bias) and disadvantages (reliance on researcher skill, potential for sample selection bias). The report then assesses the reliability and validity of the variables, differentiating between test-retest, internal consistency, and interrater reliability, as well as face, content, criterion, and discriminant validity. Furthermore, the importance of collecting social demographic data is emphasized, including its role in survey design, analysis, and the collection of meaningful data. The research design, a survey, is then discussed, detailing its cost-effectiveness, data collection ease, and ability to reach a large sample, while also acknowledging its limitations such as sample choice issues and rigidity. The report concludes by summarizing the key findings and implications of the research, offering a comprehensive overview of the methodology and its application in understanding job insecurity and its impact on employees.

Running Head: RESEARCH AND STATISTICAL METHOD OF BUSINESS 1
Research and Statistical Methods of Business
Student’s Name
Institution’s Name

RESEARCH AND STATISTICAL METHOD OF BUSINESS 2
Research and Statistical Method of Business
Sample size
Sampling is a statistical analysis procedure where an established number of observations
are chosen from a bigger population. The sample size should be at most 10% of the population.
In this research the sample size is quite large (21%), which is necessary due to the following
reasons:
It provides a more accurate mean value. The bigger the sample size the closer its mean
values will be to the mean values of the actual population. In this research, therefore, such mean
values as of the age of employees and the number of employees having worries about keeping
their jobs closely reflect the true mean values.
Identifying outliers that could skew the data in a smaller sample. Since the mean values
of a larger sample are precise to the actual mean, it is very possible to identify outliers in the
research findings. For example, having an employer aged 18-24 years can be considered an
outlier to the mean grouped-age value.
Confidence level and margin of error. The sample size states the quantity of information
we have thus partially decides our accuracy. The bigger the sample size the more certain we are
and the lower the standard error. This large sample size reduces variation between sample
statistics and therefore decreases the confidence interval, increasing the confidence level.
The margin of error is the level of accuracy required. It is a percentage expression of the range of
the measurement estimated. The bigger the sample size the narrower the margin of error.
Power and effect size. The large sample size increases the likelihood of rejecting the null
hypothesis when it is false. This increases the power of the test and reduces the probability of
making a type II error. Effect size is the presumed difference between groups observed in the

RESEARCH AND STATISTICAL METHOD OF BUSINESS 3
sample. This large sample would mean a small effect size, that is, detecting a difference with a
defined power.
Sampling method
Simple random sampling is the method used in this research. This is because every
employee in the banking sector had an even chance of being chosen in the sample. The selection
depends entirely on probability. This method has its merits and demerits. The following are the
merits:
A random sample represents the population. Every individual has an even likelihood of
being chosen therefore better chances of the sample representing the whole population.
Involves a lesser degree of judgment. It eliminates bias by allowing all individuals an
even likelihood to be chosen.
Simple random sampling is easy to use. It does not involve any complicated and long
procedures. The researcher only needs to make a list from which he or she chooses the sample
randomly.
It results in a sample that is a true representative of the whole population. This is because
everyone in the population is given fair chance to be part of the sample. The final sample,
therefore, represents the population without bias.
When performed correctly it reduces sampling error. There is less bias and sample data is
well balanced relative to the population.
It can be done by non-technical researchers. Since it does not involve any complex
procedure, it can be done by any kind of person.

RESEARCH AND STATISTICAL METHOD OF BUSINESS 4
High confidence level. This is due to the large sample size and reduced margin of error.
There is a reduced confidence interval for the measures of the sample as a representation of the
measures of the population.
The following are the demerits:
It relies on the quality of the researcher's performance. The skills of the researcher are
used for information collection. The data quality is determined by the ability to abide by the
structure of the study failure to which would create gaps in information and therefore a
misinterpretation of overall demographic.
The large sample size is required to minimize the margin of error.
Sample selection bias. Some groups of intended individuals might not be represented
well in this method as it would be with other sampling methods.
No guarantee that the data conclusion will be accurate. Despite the low margin of error,
random pulling might include more weight on one factor thus end up with inaccurate results.
It does not work well in widely diverse areas. Simple random sampling only works well
when demographics under study fall in a unique geographic situation, household structure, and
employment pattern.
Measures of variables: Reliability and validity of the variables
Reliability means the measure is consistent in these three forms;
a) Test-retest reliability. This refers to consistency over time. Both the quantitative and
qualitative measures in this research were performed once. Therefore, we cannot
conclude that the measures are consistent over time. This would require more than a one-
time test to establish consistency.

RESEARCH AND STATISTICAL METHOD OF BUSINESS 5
b) Internal consistency. This is the consistency of employees’ reactions to the research
questions on multiple-item measures. In this research, each employee had a different
opinion and approach to the research questions. For instance, some felt they were sure of
maintaining their jobs while others were not.
c) Interrater reliability. Refers to the consistency of different observers' opinion on similar
research. In this research, the observer's judgment would be the same since the sample
employees gave their feedback via filled questionnaires which would thus be interpreted
the same by every observer.
Validity refers to the extent to which scores of a measure constitute the variable they are
purposed to. It is an important measure of variable besides reliability since a measure could
be consistent but have no validity whatsoever. We consider three basic forms of validity.
a. Face validity. The questionnaire included such items as to whether the employees
believed in themselves. Whether or not the employees had good qualities. These
research questions, therefore, had good face validity.
b. Content validity. Is the degree to which a measure covers the area of interest. As
seen in the research, the qualitative measures had content validity. Employees
were being asked about their interests in job security and job satisfaction.
c. Criterion validity. This refers to the depth in which an employee's response to a
certain measure relates to other variables that researchers would expect to be
correlated. For example, an employee's response to the question "am sure I will be
able to keep my job" should be positively correlated to the question "I feel secure
about the future of my job".

RESEARCH AND STATISTICAL METHOD OF BUSINESS 6
d. Discriminant validity. This is the opposite of criterion validity. It is the degree to
which response to a measure is not correlated with measures of variables that are
distinct conceptually. For instance, employees’ responses to job satisfaction
should not be very highly correlated with psychological distress as the two are not
the same.
Collection of data on social demographics
Data on social demographics such as gender, age, and education level are essential in
evaluating long-range trends and business opportunities.
Helps in deciding on who to survey. The research might determine that only employees
falling under a certain age bracket should be surveyed. Going directly to them would otherwise
create a form of insecurity and an invasion of privacy. Collecting data on social demographics
would, therefore, help in determining the exact intended respondents by the researcher thereafter
Analysing responses. Once the data is assembled. The researcher might group it
according to various demographic information gathered from the employees. The researcher
might be interested in knowing the responses of a group of employees say the high school
leavers on their job security. This data can help him rather than approaching them separately.
The researcher can also compare research data across various demographics through data
analysis. For the planning and development of the research, it may be helpful to understand if the
respondent is educated beyond high school or not.
Ensures the collection of meaningful data. Given a certain group of target social
demographic behaviour it may be tempting to ask many questions. This can lead to respondents'
concern about their privacy which makes them insecure and unwilling to provide accurate
answers. Collecting this meaningful data as general is not suspicious. The researcher adds these

RESEARCH AND STATISTICAL METHOD OF BUSINESS 7
questions to the standardized ones in the questionnaire and will surely get the feedback without
any respondent’s complications.
Consider employment, as in this research, understanding the demographics of who is
employed and to what level of seniority is crucial in evaluating the banking system by creating
more employment opportunities and offering promotions to current employees.
Enables the research and analysis of the distribution. It helps answers the questions
“who?” “when?” and “where?”. For example, the researcher is can know which group of people
is employed in the banking industry. He can also tell when employees start to lose hope in
maintaining their jobs.
Research design
The survey research design is employed here. The researcher selected a sample of
employees from the banking sector and administered standardized questionnaires to them. The
advantages of survey research are as follows:
Cost. Have a limited cost per participant. Unlike other designs, the researcher prepares
questionnaires and mail them to the respondents. He does not incur the cost of traveling by
himself.
Data collection. When using data sources that are easy to read, data collection becomes
much easier.
Sample size. It is the most important aspect of all research designs. The mistake of using
small samples is always enough to undermine the research findings. This design allows the
researcher to reach many participants, thus a more accurate sample to conclude from.
Accurate responses. Getting accurate data requires the participants to be honest. In
surveys, this is easily achieved since the answers remain confidential.

RESEARCH AND STATISTICAL METHOD OF BUSINESS 8
Little or no observer subjectivity. The respondents are free to answer as they think
without the bias of the researcher. This makes the responses reliable.
Precise results. Survey questions usually undergo standardization. Therefore, they give
uniform definitions to all respondents.
Abroad range of data can be collected. The questionnaire can include as many questions
as they are needed to extract all the data required in the research.
Standardized surveys are relatively free from some types of errors. This is achieved by
making the questions friendly and in accordance with the target respondents.
Many questions can be asked about different subjects. This gives immense flexibility
when it comes to data analysis.
Time. Compared to other research designs, survey research can be developed in less time.
High representativeness. Surveys represent a large population due to a high number of
people who answer them.
Below are the disadvantages of survey research:
Sample choice. In this research, assumptions are made about samples that might turn out
not to be accurate. For example, when researching rural areas, many voices might not be heard
due to lack of access to email access.
Rigidity. It is the lost data or inaccurate data due to lack of enough space for the
respondent to provide an accurate answer or the correct answer missing out on options given.
Researchers need to account for all possible answers before developing a survey.

RESEARCH AND STATISTICAL METHOD OF BUSINESS 9
Not ideal for controversial issues. Questions with controversies are not well answered
due to the difficulty of recalling certain events. Their truth might only be found when using other
research methods.
Inflexible design. In the whole process of data collection, the questionnaire or method of
administering it cannot be changed.
Possible inappropriateness of questions. Due to standardization, the researcher is forced
to generalize the population and create general questions. This might not be appropriate to all the
respondents as it should be.
Closed-ended queries may have low validity. Questions with limited options force the
respondent to pick among only the ones provided. He/she might be having a different answer in
mind and therefore fails to provide the valid response.
It can lead to unclear data since some options given may be interpreted wrongly by
respondents. For instance, the answer option “more than usual” may be understood differently by
each respondent.
Respondents may not feel motivated to give reliable answers. Some respondents want the
presence of the researcher in order to be persuaded to provide accurate, honest answers.
Respondents’ unawareness of their reasons for any given answer option due to boredom
or lack of knowledge on the subject.

RESEARCH AND STATISTICAL METHOD OF BUSINESS 10
References
Bell, E. B. (2018). Business research methods. Oxford university press.
Gentles, S. J. (2015). Sampling in qualitative research: Insights from an overview of the methods
literature. The Qualitative Report, 20(11), 1772-1779.
Kumar, R. (2019). Research methodology: A step-by-step guide for beginners. Sage Publications
Limited.
Patten, M. L. (2017). Understanding research methods: An overview of essentials (Tenth ed.).
New York: Routledge.
Quinlan, C. B. (2019). Business research methods. South Western Cengage.
Sekaran, U. &. (2016). Research methods for business: A skill building approach. John Wiley &
Sons.
Stewart, W. (2014). Leisure research to enhance social justice.