This document discusses the steps involved in conducting research. It begins by defining research and outlining its purposes such as building knowledge and increasing public awareness. It then describes the basic structure of a research paper as introduction, methods, results and discussion. The next sections explain each step of conducting research in detail, including identifying the research problem, literature review, specifying the research purpose and questions, developing hypotheses, choosing an appropriate methodology, collecting and verifying data, analyzing and interpreting results. Both qualitative and quantitative research methods are discussed. The importance of verification strategies in ensuring the reliability and validity of research findings is also highlighted.

1. RESEARCH PAPER
WRITING
Maullika Rai
Application No. –cc7d3b14e6ce11e9b762498e23bef2b7
Banaras Hindu University

2. DEFINITION
 Research is "creative and systematic work undertaken to increase
the stock of knowledge, including knowledge of humans, culture
and society, and the use of this stock of knowledge to devise new
applications."[
 "Any creative systematic activity undertaken in order to increase
the stock of knowledge, including knowledge of man, culture and
society, and the use of this knowledge to devise new applications.“
– OECD
 According to JohnW. Creswell “Research is a process of steps used
to collect and analyze information to increase our understanding
of a topic or issue“
 MerriamWebster Online Dictionary defines research as “Studious
inquiry or examination; especially : investigation or
experimentation aimed at the discovery and interpretation of
facts, revision of accepted theories or laws in the light of new
facts, or practical application of such new or revised theories or
laws"

3. PURPOSEOF
RESEARCH
WRITING

4. 1. A Tool for Building Knowledge and for Facilitating
Learning
2. Means to Understand Various Issues and Increase
Public Awareness
3. An Aid to previously written papers
4. A Way to predict , plan and control
5. Means to Find, Gauge, and Seize Opportunities
6. A Seed to Love Reading, Writing, Analyzing, and
Sharing Valuable Information
7. To find evidences
8. To add to the body of knowledge,
9. To contribute to previous predictions
10. To formulate better means and ways.

5. STRUCTUREOF
RESEARCH PAPER

6. The basic structure of a typical research paper is the sequence of
Introduction, Methods, Results, and Discussion (sometimes
abbreviated as IMRAD).
Each section addresses a different objective.The authors state:
(i) the problem they intend to address—in other terms, the research question—
in the Introduction;
(ii) what they did to answer the question in the Methods section;
(iii)what they observed in the Results section; and
(iv) what they think the results mean in the Discussion.

7. Introduction
State why the problem you address is important
State what is lacking in the current knowledge
State the objectives of your study or the research question
Methods
Describe the context and setting of the study
Specify the study design
Describe the ‘population’ (patients, doctors, hospitals, etc.)
Describe the sampling strategy
Describe the intervention (if applicable)
Identify the main study variables
Describe data collection instruments and procedures
Outline analysis methods

8. Results
Report on data collection and recruitment (response rates, etc.)
Describe participants (demographic, clinical condition, etc.)
Present key findings with respect to the central research question
Present secondary findings (secondary outcomes, subgroup analyses, etc.)
Discussion
State the main findings of the study
Discuss the main results with reference to previous research
Discuss policy and practice implications of the results
Analyse the strengths and limitations of the study
Offer perspectives for future work

9. STEPS IN
CONDUCTING
RESEARCH

11. Research is often conducted using the hourglass model structure of
research. The hourglass model starts with a broad spectrum for research,
focusing in on the required information through the method of the project (like
the neck of the hourglass), then expands the research in the form of discussion
and results. The major steps in conducting research are:
•Identification of research problem
•Literature review
•Specifying the purpose of research
•Determining specific research questions
•Specification of a conceptual framework, sometimes including a set of hypotheses
•Choice of a methodology (for data collection)
•Data collection
•Verifying data
•Analyzing and interpreting the data
•Reporting and evaluating research
•Communicating the research findings and, possibly, recommendations

12. Step 1
Identification
of research
problem
What is a research Problem ?
 A research problem is a definite or clear expression [statement]
about an area of concern, a condition to be improved upon, a
difficulty to be eliminated, or a troubling question that exists in
scholarly literature, in theory, or within existing practice that
points to a need for meaningful understanding and deliberate
investigation.A research problem does not state how to do
something, offer a vague or broad proposition, or present a value
question.
– Alan Byrma

13. STEP 1. SPECIFYTHE RESEARCHOBJECTIVES
A clear statement defining your objectives will help you develop effective research.
It will help the decision makers evaluate the research questions your project should
answer as well as the research methods your project will use to answer those questions.
It’s critical that you have manageable objectives. (Two or three clear goals will help to
keep your research project focused and relevant.)
STEP 2. REVIEWTHE ENVIRONMENTOR CONTEXT OFTHE RESEARCH PROBLEM
As a researcher, you must work closely in defining and testing environmental variables.
This will help you determine whether the findings of your project will produce enough
information to be worth the cost.
In order to do this, you have to identify the environmental variables that will affect the
research project and begin formulating different methods to control these variables.
STEP 3. EXPLORETHE NATURE OFTHE PROBLEM
Research problems range from simple to complex, depending on the number of variables
and the nature of their relationship. Sometimes the relationship between two variables is
directly related to a problem or questions, and other times the relationship is entirely
unimportant.

14. STEP 4. DEFINETHEVARIABLE RELATIONSHIPS
Such programs create a commitment to follow some behavioral pattern or method in the future.
Studying such a process involves:
Determining which variables affect the solution to the research problem.
Determining the degree to which each variable can be controlled and used for the purpose.
Determining the functional relationships between the variables and which variables are critical to the
solution of the research problem.
During the problem formulation stage, you will want to generate and consider as many courses of action
and variable relationships as possible.
STEP 5.THE CONSEQUENCESOF ALTERNATIVECOURSESOF ACTION
There are always consequences to any course of action used in one or more projects. Anticipating and
communicating the possible outcomes of various courses of action is a primary responsibility in the research
process

15. Step 2 –
Literature
Review

16. Literature reviews for dissertation/research article
Every research report/ thesis/research article begins with an introduction to the topic of research.This forms
the literature review for the article.The main purpose of the review is to introduce the readers to the need for
conducting the said research. A literature review should begin with a thorough literature search using the main
keywords in relevant online databases such as Google Scholar, PubMed, etc. Once all the relevant literature has
been gathered, it should be organized as follows:
1- Background literature about the broad research topic to introduce the readers to the field of study.
2- Recent progress on the study topic which can be organized thematically or chronologically. Ideally, separate
themes should be discussed in a chronological manner to describe how research in the field has evolved over
time and to highlight the progress in the field.
3 -The review should include a comparison and contrast of different studies. Discussing the controversial
aspects helps to identify the main gaps that need to be worked upon.This is essential for defining the problem
statement of the study and highlighting the significance of the research under question.
4- Once a problem statement has been defined, the strengths and pitfalls of other studies that have tackled the
problem statement should be discussed.This is important for outlining the need and novelty of the research.

17. Step 3 –
Specifying the
purpose of the
Research

18. Why do we need to specify the purpose of the research?
• To clearly state the nature and reason for the research
• Summarize the research purpose in one or two sentences
• Briefly explaining why and how the research is conducted
• Give direction to the research
• Specify if the research is yielding qualitative or quantitative methods

19. Step 4 –
Determining
Specific
Research
question

20. • Research question raises the inquiry that is to be answered in the
research
• Research question specifies the purpose of the research study into
specific areas of the research
• A research may include various domains and each domain answers
• a specific question that needs to be determined at the start of the
research
• A research question gives a purpose and direction to the conduction of
research

21. Step 5 –
Hypothesis

22. • A statement that narrows down the purpose statement into specific predictions
about the relationship among the variables is called a hypothesis
• The research question may be parallel to the hypothesis.
• The hypothesis is the supposition to be tested.
• The researcher(s) collects data to test the hypothesis.
• The researcher(s) then analyzes and interprets the data via a variety of statistical
methods , engaging in what is known as empirical research.
• The results of the data analysis in rejecting or failing to reject the null hypothesis
are then reported and evaluated.

23. Step 6 –
Choice of
menthodology

24. Research methods
The goal of the research process is to produce new knowledge or
deepen understanding of a topic or issue.This process takes
three main forms :
1. Exploratory research, which helps to identify and define a
problem or question.
2. Constructive research, which tests theories and proposes
solutions to a problem or question.
3. Empirical research, which tests the feasibility of a solution
using empirical evidence.

25. Exploratory research is a research conducted for a problem that has not been
studied more clearly, intended to establish priorities, develop operational
definitions and improve the final research design.
Exploratory research helps determine the best research design, data-
collection method and selection of subjects. It should draw definitive
conclusions only with extreme caution. Given its fundamental nature,
exploratory research often relies on techniques such as:
secondary research - such as reviewing available literature and/or data
informal qualitative approaches, such as discussions with consumers,
employees, management or competitors
formal qualitative research through in-depth interviews, focus groups,
projective methods, case studies or pilot studies

26. EMPIRICAL RESEARCH
Empirical research is research using empirical evidence. It is a way of gaining
knowledge by means of direct and indirect observation or experience.
Empiricism values such research more than other kinds. Empirical evidence (the
record of one's direct observations or experiences) can be analyzed quantitatively or
qualitatively. Quantifying the evidence or making sense of it in qualitative form, a
researcher can answer empirical questions, which should be clearly defined and
answerable with the evidence collected (usually called data).
Research design varies by field and by the question being investigated. Many
researchers combine qualitative and quantitative forms of analysis to better answer
questions which cannot be studied in laboratory settings, particularly in the social
sciences and in education.

27. There are two major types of empirical research design: qualitative research and quantitative research. Researchers
choose qualitative or quantitative methods according to the nature of the research topic they want to investigate
and the research questions they aim to answer:
Qualitative research
This involves understanding human behavior and the reasons that govern such behavior, by asking a broad question,
collecting data in the form of words, images, video etc. that is analyzed, and searching for themes.This type of
research aims to investigate a question without attempting to quantifiably measure variables or look to potential
relationships between variables. It is viewed as more restrictive in testing hypotheses because it can be expensive
and time-consuming and typically limited to a single set of research subjects. Qualitative research is often used as a
method of exploratory research as a basis for later quantitative research hypotheses. Qualitative research is linked
with the philosophical and theoretical stance of social constructionism.
Quantitative research
This involves systematic empirical investigation of quantitative properties and phenomena and their relationships,
by asking a narrow question and collecting numerical data to analyze it utilizing statistical methods.The quantitative
research designs are experimental, correlational, and survey (or descriptive). Statistics derived from quantitative
research can be used to establish the existence of associative or causal relationships between variables. Quantitative
research is linked with the philosophical and theoretical stance of positivism.

28. • The quantitative data collection methods rely on random sampling and structured data collection
instruments that fit diverse experiences into predetermined response categories.These methods
produce results that are easy to summarize, compare, and generalize. Quantitative research is
concerned with testing hypotheses derived from theory or being able to estimate the size of a
phenomenon of interest.
• In either qualitative or quantitative research, the researcher(s) may collect primary or secondary data.
Primary data is data collected specifically for the research, such as through interviews or
questionnaires. Secondary data is data that already exists, such as census data, which can be re-used
for the research. It is good ethical research practice to use secondary data wherever possible.
• Mixed-method research, i.e. research that includes qualitative and quantitative elements, using both
primary and secondary data, is becoming more common.This method has benefits that using one
method alone cannot offer. For example, a researcher may choose to conduct a qualitative study and
follow it up with a quantitative study to gain additional insights.
• Big data has brought big impacts on research methods so that now many researchers do not put much
effort into data collection; furthermore, methods to analyze easily available huge amounts of data have
also been developed.

29. Step 7 –
Data
Collection

30. Data Collection Methods
Data collection is a process of collecting information from all the relevant sources to find
answers to the research problem, test the hypothesis and evaluate the outcomes. Data
collection is the process of gathering and measuring information on targeted variables in an
established system, which then enables one to answer relevant questions and evaluate
outcomes.
Data collection methods can be divided into two categories: secondary methods of data
collection and primary methods of data collection.
1 – Primary Dtata Collection Method
2 – Secondary Data Collection Method

31. Primary Data Collection Methods
Primary data collection methods can be divided into two groups: quantitative and qualitative.
• Quantitative data collection methods are based in mathematical calculations in various formats. Methods of
quantitative data collection and analysis include questionnaires with closed-ended questions, methods of
correlation and regression, mean, mode and median and others. Quantitative methods are cheaper to apply
and they can be applied within shorter duration of time compared to qualitative methods. Moreover, due to a
high level of standardisation of quantitative methods, it is easy to make comparisons of findings.
• Qualitative research methods, on the contrary, do not involve numbers or mathematical calculations.
Qualitative research is closely associated with words, sounds, feeling, emotions, colors and other elements that
are non-quantifiable.Qualitative studies aim to ensure greater level of depth of understanding and qualitative
data collection methods include interviews, questionnaires with open-ended questions, focus groups,
observation, game or role-playing, case studies etc.
Your choice between quantitative or qualitative methods of data collection depends on the area of your research
and the nature of research aims and objectives.

32. Secondary Data Collection Methods
Secondary data is a type of data that has already been published in books,
newspapers, magazines, journals, online portals etc. There is an abundance of
data available in these sources about your research area in business studies,
almost regardless of the nature of the research area.
Therefore, application of appropriate set of criteria to select secondary data to be
used in the study plays an important role in terms of increasing the levels of
research validity and reliability.
These criteria include, but not limited to date of publication, credential of the
author, reliability of the source, quality of discussions, depth of analyses, the
extent of contribution of the text to the development of the research area etc.

33. Step 8 –
Verifictation

34. Verification is the process of checking, confirming, making sure, and being certain.
In qualitative research, verification refers to the mechanisms used during the process of research to
incrementally contribute to ensuring reliability and validity and, thus, the rigor of a study.
These mechanisms are woven into every step of the inquiry to construct a solid product (Creswell,
1997; Kvale, 1989) by identifying and correcting errors before they are built in to the developing
model and before they subvert the analysis.
If the principles of qualitative inquiry are followed, the analysis is self-correcting. In other words,
qualitative research is iterative rather than linear, so that a good qualitative researcher moves back
and forth between design and implementation to ensure congruence among question formulation,
literature, recruitment, data collection strategies, and analysis.
Data are systematically checked, focus is maintained, and the fit of data and the conceptual work of
analysis and interpretation are monitored and confirmed constantly.
Verification strategies help the researcher identify when to continue, stop or modify the research
process in order to achieve reliability and validity and ensure rigor

35. While much has been written about the use of these strategies in various methods, the literature
has focused on “how to do” rather than the contribution that these strategies make in optimizing
the research outcome. In actual fact, it is the analytical work of the investigator that underlies
these strategies that ensures their effectiveness. For example, many research decisions may
underlie the sampling selection, which requires responsiveness to the needs of developing
variation, verification, and the developing theory.
It is time to reconsider the importance of verification strategies used by the researcher in the
process of inquiry so that reliability and validity are actively attained, rather than proclaimed by
external reviewers on the completion of the project.We argue that strategies for ensuring rigor
must be built into the qualitative research process per se.
These strategies include investigator responsiveness, methodological coherence, theoretical
sampling and sampling adequacy, an active analytic stance, and saturation.These strategies,
when used appropriately, force the researcher to correct both the direction of the analysis and
the development of the study as necessary, thus ensuring reliability and validity of the completed
project.

36. Step 9 –
DataAnalysis
and
Interpretation

37. What Is Data Interpretation?
Data interpretation refers to the implementation of processes through which data is reviewed for the
purpose of arriving at an informed conclusion.The interpretation of data assigns a meaning to the
information analyzed and determines its signification and implications.
The importance of data interpretation is evident and this is why it needs to be done properly. Data is
very likely to arrive from multiple sources and has a tendency to enter the analysis process with
haphazard ordering. Data analysis tends to be extremely subjective.That is to say, the nature and goal
of interpretation will vary from business to business, likely correlating to the type of data being
analyzed.While there are several different types of processes that are implemented based on
individual data nature, the two broadest and most common categories are “quantitative analysis” and
“qualitative analysis”.

38. It should be understood that visual presentations of data findings are irrelevant unless a sound
decision is made regarding scales of measurement. Before any serious data analysis can begin,
the scale of measurement must be decided for the data as this will have a long-term impact on
data interpretation ROI.The varying scales include:
Nominal Scale: non-numeric categories that cannot be ranked or compared quantitatively.
Variables are exclusive and exhaustive.
Ordinal Scale: exclusive categories that are exclusive and exhaustive but with a logical order.
Quality ratings and agreement ratings are examples of ordinal scales (i.e., good, very good,
fair, etc., OR agree, strongly agree, disagree, etc.).
Interval: a measurement scale where data is grouped into categories with orderly and equal
distances between the categories.There is always an arbitrary zero point.
Ratio: contains features of all three.

39. How do we Interpret data?
When interpreting data, an analyst must try to discern the differences between correlation, causation and
coincidences, as well as many other bias – but he also has to consider all the factors involved that may have led
to a result.There are various data interpretation methods one can use.
The interpretation of data is designed to help people make sense of numerical data that has been collected,
analyzed and presented. Having a baseline method (or methods) for interpreting data will provide your analyst
teams a structure and consistent foundation. Indeed, if several departments have different approaches to
interpret the same data, while sharing the same goals, some mismatched objectives can result. Disparate
methods will lead to duplicated efforts, inconsistent solutions, wasted energy and inevitably – time and money.
In this part, we will look at the two main methods of interpretation of data: with a qualitative and a quantitative
analysis.
A key difference between qualitative and quantitative analysis is clearly noticeable in the interpretation stage.
Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and
labeling of data into identifiable themes. As person-to-person data collection techniques can often result in
disputes pertaining to proper analysis, qualitative data analysis is often summarized through three basic
principles: notice things, collect things, think about things.

40. Qualitative Data Interpretation
Qualitative data analysis can be summed up in one word – categorical.With qualitative analysis, data is
not described through numerical values or patterns, but through the use of descriptive context (i.e.,
text).Typically, narrative data is gathered by employing a wide variety of person-to-person techniques.
These techniques include:
Observations: detailing behavioral patterns that occur within an observation group.These patterns
could be the amount of time spent in an activity, the type of activity and the method of communication
employed.
Documents: much like how patterns of behavior can be observed, different types of documentation
resources can be coded and divided based on the type of material they contain.
Interviews: one of the best collection methods for narrative data. Enquiry responses can be grouped
by theme, topic or category.The interview approach allows for highly-focused data segmentation

41. Quantitative Data Interpretation
If quantitative data interpretation could be summed up in one word (and it really can’t) that word would be
“numerical.”There are few certainties when it comes to data analysis, but you can be sure that if the research you are
engaging in has no numbers involved, it is not quantitative research. Quantitative analysis refers to a set of processes
by which numerical data is analyzed. More often than not, it involves the use of statistical modeling such as standard
deviation, mean and median . Most common statistical terms:
Mean: a mean represents a numerical average for a set of responses.When dealing with a data set (or multiple data
sets), a mean will represent a central value of a specific set of numbers. It is the sum of the values divided by the
number of values within the data set. Other terms that can be used to describe the concept are arithmetic mean,
average and mathematical expectation.
Standard deviation: this is another statistical term commonly appearing in quantitative analysis. Standard deviation
reveals the distribution of the responses around the mean. It describes the degree of consistency within the
responses; together with the mean, it provides insight into data sets.
Frequency distribution: this is a measurement gauging the rate of a response appearance within a data set.When
using a survey, for example, frequency distribution has the capability of determining the number of times a specific
ordinal scale response appears (i.e., agree, strongly agree, disagree, etc.). Frequency distribution is extremely keen in
determining the degree of consensus among data points.

42. Step 10 –
Reporting and
evaluating
research

43. Research Evaluation
Research evaluation is the process in which the purpose of research, the methodology used and methods, such as
data collection and analysis, are rated to ascertain their relevance, value and their ability to achieve research
objectives, and to ascertain the significance of a research. In want to infer that though final evaluation of research
is by far very important, all procedures of research including data collection and analysis should be concurrent
with evaluation. For example, the purpose, design and availability of resources need evaluation. Also, preliminary
steps of data analysis involves careful evaluation of data collected to ensure that the data is suitable for analysis.
There is usually no formalized system of evaluation especially in qualitative research.This is because, most
evaluation methods can be emergent based on research purposes and design.General measures, such as peer
review evaluation and transparency, however, should be taken into account to enhance rigor of research. Mostly,
evaluation in research includes intra-disciplinary and interdisciplinary reviews.
Several systematic evaluations guidelines are used in peer-reviews. Generally, these emphasize (Coughlan, Cronin
and Ryan, 2007):
• Research believability elements–authors’ credentials, writing styles, abstract and title.
• Research robustness elements such–problem and purpose, background/literature research, theoretical
framework, aims, objectives, questions, hypothesis, sample, methods (collection, results, and analysis),
discussion, conclusions, references, ethical considerations, etc.

44. Since most evaluation may be emergent based on a specific research problem and overall methodology, there are
not so many differences in regard to evaluation objectives between both quantitative and qualitative approaches.
In establishing research credibility and robustness by emphasizing evaluation of the above elements, basic
questions, common to both quantitative approaches include the following (Russell andGregory, 2003):
• What are the findings?
• Are the findings valid?
• How can the finding be used and applied?
In spite of the similar objectives in the evaluation process used in both quantitative and qualitative approaches,
there are few general differences:
• Evaluation in quantitative approach tend to use mathematics and statistics than in qualitative approach
• Evaluation in quantitative opts to reach generalizability than in qualitative approach
• Evaluation in quantitative approach is more objective that in qualitative approach

45. REPORTING RESEARCH FINDINGS
Reporting of finding constitutes the last step in a research operation. Reporting is aimed at communicating the
research findings to the audience. It is shaped by the purpose of a research as well as the primary audience and
stakeholders. In reporting research results, a researcher usually considers the following aspects both in quantitative
and qualitative research approaches:
• Research goals
• Type of report
• Reporting style which including writing style, presentation style and communication style
• Ethics–plagiarism, audience values etc.
• Audience and stakeholders
Like in evaluation of research, only few differences exists regarding reporting between quantitative research and
qualitative research.The basic goal–to communicate research findings–is common to both approaches.Two
differences are identified here:
• Reporting in quantitative research study is usually fixed; reporting tends to be flexible in qualitative research study
• Reporting highly adopts an objective approach in quantitative research; reporting may adopt a subjective approach
in qualitative research because it is context sensitive.

46. Step 11 –
Communicating
the research
findings

47. Communicate research findings
It takes a lot of work, but conducting research projects at facility can result in significant changes in the field.
You can use research findings to promote changes to establish or develop guidelines, or to develop policy.
After the statistical results are calculated and analyzed, the findings need to be communicated. Relying on
word of mouth alone or simply writing a summary report will not help make needed changes in practice and
will not energize new people to conduct or participate in research
Communication can be formal or informal and can occur in a multitude of presentations.
To promote and disseminate research findings include:
• Publication of findings in scholarly journals
• Presentations at national or local professional conferences
• Written clinical summary statements
• Poster presentations at local and national conferences
• Presentations at local unit meetings and at various hospital committee meetings
• Presentations at journal clubs
• Dissertations
• Presentations at continuing educational inservices

48. Communicating change
When changes are proposed based on the research findings, the researcher should communicate this change with
confidence to the agencies or units affected. A sense of purpose must be identified, and a commitment to help
promote change should be encouraged.
When creating an effective dissemination plan, the researcher should consider:
• Goals and objectives of the research.The goal should be specific and clearly communicated. Collaborate with
existing relationships and networks as much as possible.
• The audiences that will most benefit from the study’s findings. Remember not to overload them with statistical
analysis, and use appropriate language geared toward your audience.
• The most effective route of delivery to reach your intended audience. Different methods can be considered,
such as written, electronic, verbal, and graphic mediums. If slides are to be used in the delivery of
communication, they should be limited to the most important points.

49. ThankYou
BY- Maullika Rai
Application No. – cc7d3b14e6ce11e9b762498e23bef2b7
Banaras Hindu University