Ridha Rahim

Research Methodology

MSMS-2019

Q.1. Difference between Basic and Applied Research with Examples

Basic Research Applied Research

Basic research is meant to expand one’s Applied research is aiming to solve particular life
current knowledge. problems.
more theoretical since it generally More practical and descriptive in nature as it seeks to
generates theories and explores alleviate current problems in various fields and is
information which may not be presently mostly concerned with end-usage.
applied
basic research aims to predict future Seeks to prevent predicted problems or come with
phenomena solutions for future challenges.
Examples: how Universe Begins? What Examples: improve agriculture crop production, treat
are protons and neutrons? Increase in or cure of a specific disease,
students absentees, burnout level
existence in employees. (Basic and Applied
Research, n.d)

Q. 2. Difference between Deductive and inductive Research with Examples.

Deductive Inductive

From more general to more specific More specific to general

Begins with theory Begins with observations

Collection of quantitative data Collection of qualitative data

Examples: All employees come office daily, Mr. Examples: Atif, Haider comes to school regularly. Atif,
Atif is an employee, and Mr. Atif comes office Haider receive high grades, regular students receive
daily. high grades.
All Muslims celebrate Eid holidays. Miss Sadia Anita, Monica comes for picnic on Sunday. They’re
is Muslim. Miss Sadia celebrate Eid holidays. employee and have holiday on Sunday. So all
employees go for picnic on Sunday.
 Q.3) Difference between Qualitative and Quantitative Research with Examples.

Quantitative Research Qualitative Research

Data which can be measured and expressed Classification of objects is based on attributes and
numerically. properties.
Research is conclusive Research is exploratory
Collection of data structured, survey, close- Collection of data un-structured, groups, open-ended
ended question how many? How much? question why? When?
Large number of representative samples Small number of non-representative samples

Approach is objective Approach is Subjective

Examples: Examples:

Do you want increment in your salary? Why you feel stress during your work?

Do you fell emotional exhaustion while your Why you want increment in your salary?
work?

If you wish to carry out statistical analysis of

the opinions of a group of people about a There are, therefore, a wide variety of methods for
particular issue or element of their lives, you analyzing them, many of which involve structuring
can ask them to express their relative agreement and coding the data into groups and themes. There are
with statements and answer on a five- or seven- also a variety of computer packages to support
point scale, where 1 is strongly disagree, 2 is qualitative data analysis. (Quantitative and
disagree, 3 is neutral, 4 is agree and 5 is Qualitative, n.d)
strongly agree (the seven-point scale also has
slightly agree/disagree).

Such scales are called Likert scales, and enable

statements of opinion to be directly translated
into numerical data

Q4) Exploratory, Explanatory, Descriptive and hypothesis Research with Examples.

EXPLORATORY RESEARCH

Exploratory research, as the name implies, intends merely to explore the research questions
and does not intend to offer final and conclusive solutions to existing problems. This type of
research is usually conducted to study a problem that has not been clearly defined yet.

Examples
A study into the role of social networking sites as an effective marketing communication
channel
An investigation into the ways of improvement of quality of customer services within
hospitality sector in London.
DESCRIPTIVE RESEARCH

A descriptive study is one in which information is collected without changing the

environment (i.e., nothing is manipulated). It is used to obtain information concerning the
current status of the phenomena to describe "what exists" with respect to variables or
conditions in a situation. The methods involved range from the survey which describes the
status quo, the correlation study which investigates the relationship between variables, to
developmental studies which seek to determine changes over time. (Descriptive research, n.d)

EXPLANATORY RESEARCH

Explanatory research is an attempt to connect different ideas and to understand the different
reasons, causes, and their effects. Mostly the research starts from exploratory research, then
descriptive research and then explanatory research. Explanatory research is the attempt to
find the question of why? (Explanatory research, n.d)

Examples

Descriptive research can tell that 20% of the students are failed in the exam. Explanatory
research can tell that what the reason behind this failure is.

Descriptive research answers that a computer system with more RAM has more speed.
Explanatory research answers the question that why a computer system with more RAMS has
more speed as compared to a computer system with less RAM.

HYPOTHESES RESEARCH

A research hypothesis is a specific, clear, and testable proposition or predictive statement

about the possible outcome of a scientific research study based on a particular property of a
population, such as presumed differences between groups on a particular variable or
relationships between variables. Specifying the research hypotheses is one of the most
important steps in planning a scientific quantitative research study. A quantitative researcher
usually states an a priori expectation about the results of the study in one or more research
hypotheses before conducting the study, because the design of the research study and the
planned research design often is determined by the stated hypotheses. 

Examples

 If salary increases then performance of employees will also increases

 If you walk daily then you remain healthy
 If I brush my teeth every day, then I will not develop cavities.

Q5. Casual vs Correlation with examples.

 CASUAL

It indicates that one event is the result of the occurrence of the other event; i.e. there is a
causal relationship between the two events. This is also referred to as cause and effect.

Examples

 I brush my teeth less so I got two cavities.

 Omer made a wrong comment so Atif hit him.
 Mantasha was hungry so she eat banana.

CORRELATION

Statistical measure (expressed as a number) that describes the size and direction of a
relationship between two or more variables. A correlation between variables, however, does
not automatically mean that the change in one variable is the cause of the change in the
values of the other variable. Correlation is a term in statistics that refers to the degree of
association between two random variables. So the correlation between two data sets is the
amount to which they resemble one another. (Correlation and causation, n.d)

Examples

 Employee don’t get extra bonus because they don’t achieve targets.
 The more vitamins one takes, the less likely one is to have a deficiency.
 The more one eats, the less hunger one will have.
 As the temperature goes up, the sale of cold drinks also goes up.
 When employees make a high salary, efficiency increases.

Q6) Cross-sectional vs longitudinal data with Examples

CROSS-SECTIONAL DATA

Cross-sectional data are data that are collected from participants at one point in time. Time is
not considered one of the study variables in a cross-sectional research design. However, it is
worth noting that in a cross-sectional study, all participants do not provide data at one exact
moment. Even in one session, a participant will complete the questionnaire over some
duration of time. Nonetheless, cross-sectional data are usually collected from respondents
making up the sample within a relatively short time frame (field period). In a cross-sectional
study, time is assumed to have random effect that produces only variance, not bias

Example

1000 people will be selected randomly from that population. It is also called a cross section
of that particular population range). Now, their Blood Pressure will be measured. Their
height, weight and other health factors will also be noted.

LONGITUDINAL DATA
Longitudinal data, sometimes referred to as panel data, track the same sample at different
points in time. The sample can consist of individuals, households, establishments, and so on.
In contrast, repeated cross-sectional data, which also provides long-term data, gives the same
survey to different samples over time.

Longitudinal data have a number of advantages over repeated cross-sectional data.

Longitudinal data allow for the measurement of within-sample change over time, enable the
measurement of the duration of events, and record the timing of various events. For example,
suppose the unemployment rate remained high for a long period of time. One can use
longitudinal data to see if the same group of individuals stays unemployed over the entire
period or if different groups of individuals move in and out of unemployment over the time
period. (Longitudinal data, n.d)

Differentiate between Time Series Analysis, Panel Analysis, and Cohort Analysis with
examples.

TIME-SERIES DATA

These are observations which are collected at equally spaced time intervals.

Example

You can consider the daily closing price of a particular stock recorded over the past four
weeks. One thing is to be noted, and that is, too short or too long time can lead towards time
bias.

PANEL DATA

Panel data analysis refers to the statistical analysis of data sets consisting of multiple
observations on each sampling unit. This could be generated by pooling time-series
observations across a variety of cross-sectional units, including countries, firms, or randomly
sampled individuals or households. This also encompasses longitudinal data analysis in
which the primary focus is on individual histories. Two well-known examples of U.S. panel
data are the Panel Study of Income Dynamics (PSID) and the National Longitudinal Surveys
of Labor Market Experience (NLS). European panels include the German Socio-Economic
Panel, the British Household Panel Survey, and the European Community household pane.

COHORT DATA

In cohort analysis the data is same but the individual got categorize and when doing the
analysis again the person is choosing from that category whereas the person may be different
but the category not. A cohort is a group of people who share a common characteristic over a
certain period of time.

Example
 Let’s look at a group of students. All of these students graduated in 2010. This group of
students is a cohort. All of the students graduated in the same year, and this is their
commonality.

Assignment 2

Create Linkages between Research Topic, SOP, Research Question and Objective
with Examples

TOPIC 1

Impact of absentees on employee performance

SOP

Increase of absentees among employee

RESEARCH QUESTION

Does absentees impact on employee performance?

RESEARCH OBJECTIVE

Strong factor that cause absentees among the employee

TOPIC 2

Impact of burnout on employee performance

SOP

Increase of burnout among employees during work

RESEARCH QUESTION

Do you feel burnout while doing your work?

RESEARCH OBJECTIVE

Analyze the strong factor that cause burnout

Assignment 3

LITERATURE REVIEW

A literature review surveys books, scholarly articles, and any other sources relevant to a
particular issue, area of research, or theory, and by so doing, provides a description,
summary, and critical evaluation of these works in relation to the research problem being
investigated. Literature reviews are designed to provide an overview of sources you have
explored while researching a particular topic and to demonstrate to your readers how your
research fits within a larger field of study.

PURPOSES

 Place each work in the context of its contribution to understanding the research
problem being studied.
 Describe the relationship of each work to the others under consideration.
 Identify new ways to interpret prior research.
 Reveal any gaps that exist in the literature.
 Resolve conflicts amongst seemingly contradictory previous studies.
 Identify areas of prior scholarship to prevent duplication of effort.
 Point the way in fulfilling a need for additional research.
 Locate your own research within the context of existing literature [very important].

KNOWLEDGE GAP

The gap, also considered the missing piece or pieces in the research literature, is the area that
has not yet been explored or is under-explored. This could be a population or sample (size,
type, location, etc.), research method, data collection and/or analysis, or other research
variables or conditions.

Continue to ask critical questions of your topic – who, what, when, where and how – about
the population or setting, conditions or variables, methods or analysis, and measurement or
outcomes. Also consider what has not been explored in the study and what may be a possible
‘gap’ or opening for your potential research and contribution to the topic. Use organizational
tools such as charts or Venn diagrams to map out the research you find from scholarly
articles. These methods may be helpful to organize what information you have found and
what is shared among the literature, as well as to identify what areas may be missing in the
research. This page provides a matrix for organizing research from multiple articles.
(Literature gap, n.d)
 REFERENCES

Research methods. (n.d). Retrieved from http://methods.sagepub.com/reference/encyclopedia-

of-survey-research-methods/n119.xml

Basic and Applied Research. (n.d). Retrieved from https://keydifferences.com/difference-

between-basic-and-applied-research.html

Quantitative and Qualitative. (n.d). Retrieved from

https://www.skillsyouneed.com/learn/quantitative-and-qualitative.html

Explanatory research. (n.d). Retrieved from https://t4tutorials.com/what-is-explanatory-

research-research-methodology/

Descriptive research. (n.d). Retrieved from

https://www.researchgate.net/post/What_do_we_mean_by_Descriptive_Research

Longitudinal data. (n.d). Retrieved from https://www.nlsinfo.org/content/getting-started/what-

are-longitudinal-data

Correlation and causation. (n.d). Retrieved from

https://www.abs.gov.au/websitedbs/a3121120.nsf/home/statistical+language+-
+correlation+and+causation

Literature gap. (n.d). Retrieved from http://ncu.libguides.com/researchprocess/literaturegap

Test Questions
Q1. A manager believes that limiting the availability of a product increases product
desirability. What is Dependent Variable?

Product Availability Product Desirability

Independent Variable Dependent Variable

Q2. A manager believes that good supervision and training will increase production
level of workers. Identify the dependent variable and independent variable and also
draw frame work.

Supervision & Training Production level of Workers

Independent Variable Dependent Variable

Q3. A manager finds that off the job classroom training has a great impact on
productivity of employee. However she also observed that employee over 60 years of age
do not seem to drive much benefit and do not improve with such training. List & label
the variables used and draw frame work of variables.

Independent Variable: Classroom training

Dependent Variable: Productivity of employee

Moderator: employee over 60 years no benefit

Productivity of employee
Classroom training

Independent Variable Dependent Variable

Age

Moderator

Q4. A manager observe that moral of employee is low in the company. She think if she
improve working condition pay scale and vacation benefits the moral will be boosted.
She doubt however if an increase in pay would increase moral of all employees. Her
 argument is that those employees that have supplementary income will just not be turn
on by higher pay & only those without side income will be happy by increasing salary.

List & label the variables used and draw frame work of variables. Write down SOP and
develop hypothesis.

FRAMEWORK

working condition pay scale

moral of employee
vacation benefits

Independent Variable Moderator Dependent Variable

SOP

Low Moral of Employee in Company.

HYPOTHESIS

If the Working Condition, pay scale and vacation benefits are increased then the moral of
employee will boost up.

Q5. The probability of cancer victims successfully recovering under treatment was studied
by researcher in hospital. She found that 3 variables to be important for recovery.

A: Early & Correct diagnosis

B: Nurse careful follow Doctors instruction.

C: Peaceful & quite environment.

Define SOP and develop theoretical framework, also develop hypothesis.

 SOP
Probability of cancer victims in hospital.

FRAMEWORK

Early & Correct diagnosis

careful followup instructions. Probability of cancer

Peaceful & quite environment. victims

Independent Variable Dependent Variable

HYPOTHESIS

If the cancer is diagnosed early and correct with healthy environment then the victims
will successfully recovers from disease.

Q6. A production manager is concerned about low output of his employees. The article
he has read on job performance mention 4 variables.

A: Skill required for the job

B: Reward

C: Motivation

D: Satisfaction

In several other articles it was also indicated that only if the reward were attractive to
the recipients did motivation, satisfaction, job performance increases, not otherwise.

1. Define SOP.

2. Develop theoretical framework.

3. Develop at least 6 hypothesis.

 SOP

Low output of employees.

FRAMEWORK

Skill

Motivation Reward Job Performance

Satisfaction

Independent Variable Moderator Dependent Variable

HYPOTHESIS

1. If skills required for job is increase then the employee output is increase.
2. If rewards increase then the output of employee also increase.
3. If motivation increase then the output of employee also increase.
4. If satisfaction increase then the output of employee also increase.
5. If reward increase then then motivation, satisfaction, job performance increases.
6. Ho = No output increase in employees.
H1= reward were attractive to the recipients did motivation, satisfaction, job performance
increases.

Q7. A foreman thinks that low efficiency of machine operator is directly linked with
fumes emitted in workshop. He would like to impose this to his supervisor through
research.

1. Causal or correlational study and why?

It is a causal study as fumes effect the efficiency of machine operator.

2. Is this Exploratory, Descriptive, Explanatory or Hypothesis study?

Hypothesis study, as foreman is not sure about the reason of low efficiency of
machine operator.

3. A Field study, lab experiment or field experiment and why?

 It is a field experiment as it shows cause and effect relation.

4. Unit of analysis and why?

Individual, as one machine operator is being discussed.

5. Would this be cross-sectional or longitudinal study?

It is a longitudinal study as the foreman observed the machine operator more than once.

Q8. Many were concern about the operations of infamous BCCI the international
banking institution. If government had wished to probe into the detail would this
investigation have called for?

1. Causal or correlational study and why?

It is a correlational study because the above statement shows factors associated with
problem i-e the government does not investigate the issue.

2. Is this Exploratory, Descriptive, Explanatory or Hypothesis study and why?

It is explanatory study because the problem is being known and it focus to explain the
issue.

3. A Field study, lab experiment or field experiment and

why?
It is a field study as it is a correlational study.

Would this be cross-sectional or longitudinal study?

It is a cross-sectional study as data is gathered once