SOCIAL RESEARCH

​
and SOCIAL WORK
RESEARCH
Unit 1
• Social work Research:
  Any study to create new knowledge or to add to the existing
store house of knowledge, may it be through observation or
by any other methods is called research. Social work research
is the application of research methods to solve problems that
social workers confront in the practice of social work. It aims
at providing information that can be taken into consideration
by social workers provide to making decisions which are
likely to affect their clients or schemes of things or agencies
which are involved in the use of alternative intervention
techniques or transformation or modification of client /
programme / objectives etc.
Search implies thorough investigation and the term 'research'
which has been derived from the French word 'rechercher',
're' and 'chercher', means a critical examination of a topic or
subject to discover new facts for increasing the sum total of
human knowledge. It is a method for discovery of new
knowledge which augments to the existing body of organized
facts, ideals and aspiration,
 "Research is considered to be the more formal, systematic,
intensive process of carrying on the scientific method of
analysis. It involves a more systematic structure of
investigation, usually resulting in some sort of formal record
of procedures and a report of results or conclusions".
Research per se constitutes a method for the discovery of
truth which necessitates critical thinking. "It comprises
defining and redefining problems; formulating hypothesis or
suggested solutions, collecting, organising, and evaluating
data; making deductions and reaching conclusions; and at
least, carefully testing the conclusions to determine whether
they fit the formulated hypotheses."
 "It is the manipulation of things, concepts or symbols for the
purpose of generalising to extend, correct or verify
knowledge, whether that knowledge aids in construction of
theory or in the practice of an art." Thus, research is a
"systemised effort to, gain new knowledge."
  Research is characterised by :

  a specific problem. involvement in original work, resting

upon a mental attitude of curiosity, requirement of an open
mind, resting upon the assumption that everything is subject
to law and order, discovery of laws and generalisations study
of cause and effect measurement and involvement in a
conscious technique.
• Objectives :
1) Manipulation of Things, Concepts and Symbols,

2) Generalisation,

3) Verification of Old Facts,

4) Extension of Knowledge, and

5) Knowledge May be Used for Theory Building or Practical

Application.
• Importance of Social Research:
Source of Knowledge
Social research is an important source of knowledge. It opens
new ways of knowledge and wisdom. When something
unknown brings to a researcher, there is a sort of inner
pleasure and happiness. It gives knowledge to the researcher
about the unknown facts. It paves out the way of ignorance
and gives new direction in a social life.
Research in Informative.
It provides updated, proved, authentic and very useful
information to the end users. Researchers and common
people can take advantages from research. It is not only
informative. Its findings are scientific based therefore the
results and information are reliable.

Solution of Social Problems.

Social research also helps in the solution of social problems it
is the research through which we can find the causative
factors of an existing social problem and guide us about his
solution.
Social Control. 
For smooth running of society social control is necessary. For
this purpose we apply social research to a society for bringing
social order and control.
New Techniques. 
Social Research introduces new techniques and improves the
old ones. It also modifies the existing tools of research. It
gives us the methods of knowing new ways for using our
research procedure.
• Identifying and formulating a problem:
A good statement of a problem must restrict the scope of the
study to specific and workable research questions. These
questions are the questions that the researcher would like to
be answered or addressed. Research questions are the more
specific situations from a general presentation of ideas.
A researcher begins with a broad formulation of a problem,
for example 'Information Technology'. From this he moves to
a specific situation like 'Role of Information Technology' in
developing teaching models.
To study this problem, the researcher then reformulates the
problem into a statement of intent or purpose 'how
information technology contributes-to developing teaching
models' After this, the investigator still requires to narrow the
intent to a specific question, "Can information technology
help in the development of teaching models?"
Thus, after having studied a lot in the area of his interest, the
researcher tries to ultimately decide what exactly should be
his1 her problem of research. It is not always possible for the
researcher to formulate his problem simply, clearly and
completely. He may often have only a rather general, diffused
and even vague notion of the problem.
This is in the nature of the complexity of scientific research.
If the problem has been formulated in either in a broad
manner or in a narrow way it gives results which are either
very vague or very trivial. This is the stage when he finally
chooses or states the problem
• Clarifying concepts and variables formulation of
Hypothesis:
What is Hypothesis in Research?
A hypothesis is a tentative statement of a proposition which
the researcher seeks to prove. It’s basically a concrete
generalization.
When a theory stated as a testable proposition formally and
subject to empirical verification we can define it as a
hypothesis. Researchers make a hypothesis on the basis of
some earlier theories and some rationale that generally
accepted as true. The hypothesis test finally will decide
whether it is true or rejected.
So, to clarify a hypothesis is a statement about the
relationship between two or more variables. The researcher
set out the variables to prove or disprove. Hypothesis
essentially includes three elements. For example-
1. Variables

2. Population

3. Relationship between variables.

Example of Hypothesis:
1. Rewards increase reading achievements

2. Rewards decrease reading achievements

3. Or rewards have no effect on reading achievements.

In the above examples- variables are- Rewards &

Achievements
Steps in Formulation of Hypothesis:
A hypothesis is a tentative assumption drawn from practical
knowledge or theory. A hypothesis is used as a guide in the
inquiry of other facts or theories that a researcher does not
know. However, the formulation of the hypothesis is one of
the most difficult steps in the entire scientific research
process.
Define Variables:
At first, with a view to formulating a hypothesis, you must
define your variables. What do you want to test? Will you test
that rewards increase reading achievement? Or rewards
decrease reading achievement? Whatever your goals are, they
need to be clearly defined, quantifiable, and measurable. This
will provide you with a clear idea of what to follow to achieve
results.

Study In-Depth the Variables:

If we do think that your variables are Rewards &
Achievements, then you need to intense study how rewards
increase reading achievements? An in-depth study, rigorous
questions, and data of rewards increase reading
achievements will make you able to confirm your hypothesis.
Specify dependent and independent variables.
Specify the Nature of Relationship
Then, identify what relationship there exist between the
variables. What variable influences the other? That is what is
the dependent variable and what is the independent variable?
How Rewards impact achievements? If reward plays a key
role in reading achievements, then reward is the independent
variable.
Identify Study Population
The population in research we mean the entire group of
individuals is going to study. If you want to test how rewards
increase reading achievements in the United Kingdom, you
need not study the whole population of the United Kingdom.
Because the total population does not involve in reading
achievements. Therefore, the researcher must identify the
study population.
Make Sure Variables are Testable
Variables in your hypothesis must be testable. Otherwise, the
hypothesis would be worthless. Because your research study
must accept or reject a variable. So, variables you must need
to test. Testable variables can only be accepted or rejected.
Moreover, the sole aim of a research hypothesis is to test
variables in the long run.
UNIT 2
• Research Design
Research design definition
Research design is the framework of research methods and
techniques chosen by a researcher. The design allows
researchers to hone in on research methods that are suitable
for the subject matter and set up their studies up for success.
The design of a research topic explains the type of research
(experimental, survey research, correlational, semi-
experimental, review) and also its sub-type (experimental
design, research problem, descriptive case-study).
There are three main types of designs for research: Data
collection, measurement, and analysis.
The type of research problem an organization is facing will
determine the research design and not vice-versa. The design
phase of a study determines which tools to use and how they
are used.
An impactful research usually creates a minimum bias in
data and increases trust in the accuracy of collected data. A
design that produces the least margin of error in
experimental research is generally considered the desired
outcome.
 The essential elements are:

1. Accurate purpose statement

2. Techniques to be implemented for collecting and analyzing

research
3. The method applied for analyzing collected details
4. Type of research methodology

5. Probable objections for research

6. Settings for the research study

7. Timeline

8. Measurement of analysis

Proper research design sets your study up for success.

Successful research studies provide insights that are accurate
and unbiased. You’ll need to create a survey that meets all of
the main characteristics of a design. 
There are four key characteristics:
Neutrality: When you set up your study, you may have to
make assumptions about the data you expect to collect. The
results projected in the research should be free from bias and
neutral.
Reliability: With regularly conducted research, the researcher
involved expects similar results every time. Your design
should indicate how to form research questions to ensure the
standard of results. You’ll only be able to reach the expected
results if your design is reliable.
Validity: There are multiple measuring tools available.
However, the only correct measuring tools are those which
help a researcher in gauging results according to the
objective of the research. The questionnaire developed from
this design will then be valid.
Generalization: The outcome of your design should apply to a
population and not just a restricted sample. A generalized
design implies that your survey can be conducted on any part
of a population with similar accuracy.
researcher must have a clear understanding of the various
types of research design to select which model to implement
for a study.
• Case study Survey ( exploratory and explanatory ):
Explanatory case studies aim to answer ‘how’ or ’why’
questions with little control on behalf of researcher over
occurrence of events. This type of case studies focus on
phenomena within the contexts of real-life situations.
Example: “An investigation into the reasons of the global
financial and economic crisis of 2008 – 2010.”
Exploratory case studies aim to find answers to the questions
of ‘what’ or ‘who’. Exploratory case study data collection
method is often accompanied by additional data collection
method(s) such as interviews, questionnaires, experiments
etc. Example: “A study into differences of leadership practices
between private and public sector organizations in Atlanta,
USA.”
• Experimentation
An experiment is a study in which the researcher
manipulates the level of some independent variable and then
measures the outcome. Experiments are powerful techniques
for evaluating cause-and-effect relationships. Many
researchers consider experiments the "gold standard" against
which all other research designs should be judged.
Experiments are conducted both in the laboratory and in real
life situations
Ex Post Facto
The ex-post facto research is a kind of research in which the
researcher predicts the possible causes behind an effect that
has already occurred. For example, if a child is delinquent
(that is, one who indulges in criminal activities), then in order
to find the basic reason behind such delinquency, the
researcher would try to find out the various events that have
occurred and the many possibilities that could have
contributed to the concerned delinquent behaviour.
The expected possibilities may be lack of discipline at school/
family history/ peer effect/ neighbourhood or socialisation.
It is an interesting point to note that, the researcher predicts
a cause on the basis of a controlled effect (since no variation
can be done on the effect which has already taken place on
the basis of the independent variable or the cause).
Thus, an ex-post facto research can be defined as an
empirically based investigation which does not involve the
researchers’ direct control over the independent variables
because they have already led to effects which can no more
be manipulated
Quasi
Like a true experiment, a quasi-experimental design aims to
establish a cause-and-effect relationship between an
independent and dependent variable.However, unlike a true
experiment, a quasi-experiment does not rely on random
assignment. Instead, subjects are assigned to groups based
on non-random criteria.
Quasi-experimental design is a useful tool in situations where
true experiments cannot be used for ethical or practical
reasons.
• Field Research vs. Controlled Laboratory Research :
Field research is a research conducted in the real world or a
natural setting. It tends to observe, analyse, and describe
what exists rather than manipulating a factor under study .
The research settings resemble the situations encountered in
daily living, preserving the naturalness of the setting.
Participants in a field research may or may not know that
they are being studied.
On the other hand, controlled laboratory research is a
research conducted in a setting specifically designed for
research.
Laboratory research is often described as tightly controlled
investigation in which the researcher manipulates the
particular factor under study to determine if such
manipulation generates a change in the subjects .
The subjects in laboratory research can be selected and
placed in conditions more systematically and they usually
know that they are participating in a research study.
Field research studies are more likely to be descriptive,
developmental, correlational, and survey in design than they
are to be experimental.
The principal advantage of field research is its
generalizability to real-life contexts because
It represent a greater variety of situations and environments
that subjects experience in their natural habitat
Due to the greater control that researchers are generally able
to exert in a laboratory setting than in a naturalistic setting,
laboratory research studies are more likely to represent a true
experimental design.
Laboratory studies have the advantage of greater control of
irrelevant variables that might otherwise influence the results
and thus of clearer clues of the behavior being observed .
• Impact studies :
Impact studies is a field of research which is used to measure
levels of improvement within various sectors. Impact studies
most often measure the effectiveness of new policy or
initiative on a group of people or an organisation.
An impact study is a research conducted to observe and
understand the effects of introduction of a new policy or
strategy. A new policy, for example a law, may have outcomes
that were both expected and unexpected. An impact study
helps in understanding these. -Effect of Internet Censorship
Laws implemented on March 6.
• Cost benefit studies :
Cost benefit analysis is a systematic process for calculating
and comparing benefits and costs of a project. A cost benefit
analysis finds, quantifies, and adds all the positive factors
(the benefits). Then it identifies, quantifies, and subtracts all
the negatives (the costs). The difference between the two
indicates whether the planned action is advisable. The real
trick to doing a cost benefit analysis well is making sure you
include all the costs and all the benefits and properly quantify
them.
• Social Indicator :
Since its foundation in 1974, Social Indicators Research has
become the leading journal on problems related to the
measurement of all aspects of the quality of life. The journal
continues to publish results of research on all
aspects of the quality of life and includes studies that reflect
developments in the field.
It devotes special attention to studies on such topics as
sustainability of quality of life, sustainable
development, and the relationship between quality of life and
sustainability.
The topics represented in the journal cover and involve a
variety of segmentations, such as social groups, spatial and
temporal coordinates, population composition, and life
domains.
The journal presents empirical, philosophical and
methodological studies that cover the entire spectrum of
society and are devoted to giving evidences through
indicators. It considers indicators in their different
typologies, and gives special attention to indicators that are
able to meet the need of understanding social realities and
phenomena that are increasingly more complex, interrelated,
interacted and dynamical. In addition, it presents studies
aimed at defining new approaches in constructing indicators.
• Is the leading journal on quality of life measurement and
indicators.
• Covers all aspects of the measurement of the quality of life.
• Incorporates developments occurring in the field.
• Is a reference point on models, methods, and data.
• Enhances the understanding of social reality and its
complexity .
UNIT 3 

• Research Tools :
Data collection or research tools are any tool used to measure
a variable, or to collect the information needed to answer a
research question. Careful selection of data collection tools
can help the researcher achieve goals and save time.Any
research is only as good as the data that drives it, so choosing
the right technique of data collection can make all the
difference.
• Questionnaire:
A questionnaire is a research instrument consisting of a
series of questions for the purpose of gathering information
from respondents. Questionnaire is a kind of inquiry form
which has many uses, including in market research, political
polling, customer service feedback, evaluations, opinion
polls, and social science research, most notably to discover
what the respondents are thinking.
•Interview:
Interview is a process of communication or interaction in
which the subject or interviewee gives the l information
verbally in a face-to-face situation. In a sense, it is an oral
questionnaires . In a research situation it may be seen as an
effective, informal: conversation, initiated for a specific
purpose as it focuses on certain areas. The main objective
may be the exchange of ideas and experiences and eliciting of
information. Interviews can be conducted in many ways.
Interviews are also classified as structured and 'unstructured .
A 'structured interview' is one in which the whole situation is
carefully structured and the major areas of inquiry are
mapped out.
However, the interviewee is given considerable freedom to
express his /her definition of the presented situation. In this
type of interview, the interviewer uses a highly standardised
tool and a set of pre-determined questions. 'Structured
interview is also designated as 'directive interview'.
Unstructured ' also termed as uncontrolled ,unguided or 'non-
directive' interview is one. Where the interview does not
follow a list of predetermined questions.
The interviewees are encourage relate their concrete
experiences with no or little direction from the interviewer,
to dwell on whatever events seem significant to them. to
provide their own definition 01 their social situations and
reveal their opinion and views as they like.

• Observation:
Observation may be defined as a process in which one or
more observe some real life situation process/event and
record pertinent occurrences.It is used to evaluate the overt
behaviour traits of the individuals i n controlled and
uncontrolled situations.
• Types of Observation:
  Observations may be classified into two types :

  a) Participant observation

  b) Non-participant observation

  Participant observation: : In the process of 'participant

observation' the observer becomes more or less one of the
group members and may actually participate in some activity
or the other of the group.
  The observer may play any one of the several roles in
observation, with varying degrees of participation, as a
visitor, an attentive listener, an eager learner, or as a
participant observer.
  Non-Participant observation: In the process of 'non-
participant observation', the observer takes a position where
his-her presence is not felt by the group. His/ her may follow
closely the behaviour trait of an individual or characteristics
of one or more groups.
• Methods of Data collection :
A data collection method consists of a detailed plan of
procedures that aims to gather data for a specific purpose ,
that is to answer a research question or to test a research
hypothesis .Any data collection method can tap into a variety
of data sources . The primary source of data in most social
work research studies is people.
Data collected directly from people can be first or second
hand data . First hand data are obtained from people who are
closest to the problem we are study, Second hand data may
come from other people who are indirectly connected to the
primary problem. 
•Pilot studying and Pre testing:
A pilot study is a small-scale implementation of a larger study
or a part of a larger study. Pilot studies last for shorter period
of time and usually involve a smaller number of participants,
sites or organisations.
Pilot studies can be used in any methodological setting,
especially when attempting to collect data in a new format or
location or to simply examine potential roadblocks before full
implementation. A pilot study may also be viewed as a
feasibility study.
Pre-tests are preliminary tests of the measures used on a
small sample of the population to be studied. It is the final
stage in the tool development process. Pre-testing is the use
of questionnaire in a small pilot study to ascertain how well
the questionnaire works.
• Sources of Data:
The sources of data can be classified into two types: statistical
and non-statistical. Statistical sources refer to data that is
gathered for some official purposes, incorporate censuses,
and officially administered surveys. Non-statistical sources
refer to the collection of data for other administrative
purposes or for the private sector.
The following are the two sources of data:
1. Internal sources:

When data is collected from reports and records of the

organisation itself, they are known as the internal sources.
For example, a company publishes its annual report’ on profit
and loss, total sales, loans, wages, etc.
2. External sources:

When data is collected from sources outside the organisation,

they are known as the external sources. For example, if a tour
and travel company obtains information on Karnataka
tourism from Karnataka Transport Corporation, it would be
known as an external source of data.
• Primary and secondary :
primary data is one which is collected for the first time by the
researcher while secondary data is the data already collected
or produced by others.
There are many differences between primary and secondary
data, which are discussed in this work. But the most
important difference is that primary data is factual and
original whereas secondary data is just the analysis and
interpretation of the primary data. While primary data is
collected with an aim for getting solution to the problem at
hand, secondary data is collected for other purposes.
The fundamental differences between primary and
secondary data are; the term primary data refers to the data
originated by the researcher for the first time while
secondary data is the already existing data collected by the
investigator agencies and organisations earlier. Primary data
is a real-time data whereas secondary data is one which
relates to past . 
• Published Source :
Various investigation organisations, research organisations,
government departments, corporations, collect data on
various subjects and publish them from time to time.
Example : Govt, publications, Reports of Committee and
commissions, etc.
•Unpublished Source :
Sometimes, the government or other institutions or
individuals (especially investigators) collect material
associated with important subjects, but these remain
unpublished. Such unpublished data can be found from the
papers, documents, registers of the offices, diaries of
investigators, etc.

• Sampling :
A sample is defined as a smaller set of data that a researcher
chooses or selects from a larger population by using a pre-
defined selection method. These elements are known as
sample points, sampling units, or observations. Creating a
sample is an efficient method of conducting research. In
most cases, it is impossible or costly and time-consuming to
research the whole population. Hence, examining the sample
provides insights that the researcher can apply to the entire
population.
• Need of Research :
1. Research expands your knowledge base

2. Research gives you the latest information

3. Research helps you know what you’re up against

4. Research builds your credibility

5. Research helps you narrow your scope

6. Research introduces you to new ideas
7.Research helps with problem-solving
8.Research helps you reach people
9.Research encourages curiosity.
 • Types and Procedures :

There are a variety of approaches to research in any field of

investigation, irrespective of whether it is applied research or
basic research. Each particular research study will be unique
in some ways because of the particular time, setting,
environment, and place in which it is being undertaken.

Nevertheless, all research endeavors share a common goal of

furthering our understanding of the problem and thus all
traverse through certain basic stages, forming a process
called the research process.
38. These 8 stages in the research process are;

1. Identifying the problem.

2. Reviewing literature.

3. Setting research questions, objectives, and hypotheses.

4. Choosing the study design.

5. Deciding on the sample design.

6. Collecting data.
7. Processing and analysing data.

8. Writing the report.

• Determination of sample size :

Sample size is a research term used for defining the number
of individuals included in a research study to represent a
population. The sample size references the total number of
respondents included in a study, and the number is often
broken down into sub-groups by demographics such as age,
gender, and location so that the total sample achieves
represents the entire population.
Determining the appropriate sample size is one of the most
important factors in statistical analysis. If the sample size is
too small, it will not yield valid results or adequately
represent the realities of the population being studied. On the
other hand, while larger sample sizes yield smaller margins
of error and are more representative, a sample size that is too
large may significantly increase the cost and time taken to
conduct the research.
Unit 4
• Bivariate Data Defined:
Bivariate data deals with two variables that can change and
are compared to find relationships. If one variable is
influencing another variable, then you will have bivariate
data that has an independent and a dependent variable.
This is because one variable depends on the other for change.
An independent variable is a condition or piece of data in an
experiment that can be controlled or changed. A dependent
variable is a condition or piece of data in an experiment that
is controlled or influenced by an outside factor, most often
the independent variable.
•Univariate Analysis:
Univariate analysis is a basic kind of analysis technique for
statistical data. the data contains just one variable and does
not have to deal with the relationship of a cause and effect.
Like for example consider a survey of a classroom. The
analysts would want to count the number of boys and girls in
the room.
The data here simply talks about the number which is a
single variable and the variable quantity. The main objective
of the univariate analysis is to describe the data in order to
find out the patterns in the data. This is done by looking at
the mean, mode, median, standard deviation, dispersion, etc.
Univariate analysis is basically the simplest form to analyse
data. Uni means one and this means that the data has only
one kind of variable. The major reason for univariate analysis
is to use the data to describe. The analysis will take data,
summarise it, and then find some pattern in the data.

• Measures of Central Tendency : Statistics analyses and

interprets large sets of numbers. To make the lists of data
more comprehensible, central tendencies are calculated. A
measure of central tendency points the statistician toward a
centralised, repeated, or average number. There are three
different ways to calculate central tendency. Each reveals
different information about the number set. Yet, each method
uncovers an important value, and each is used extensively by
mathematicians to make sense of data.
The mean, median and mode are all valid measures of central
tendency, but under different conditions, some measures of
central tendency become more appropriate to use than
others. 
• Measures of variation :
The Range
A range is one of the most basic measures of variation. It is
the difference between the smallest data item in the set and
the largest. For example, the range of 73, 79, 84, 87, 88, 91, and
94 is 21, because 94 – 73 is 21.
•Standard deviation :
The standard deviation is the average amount by which
scores differ from the mean. The standard deviation is the
square root of the variance, and it is a useful measure of
variability .
Unit 5
Interpreting data , writing a short report :
An essential step in the research process is the interpretation
of results and preparation of the research report. The entire
data collected has no practical relevance till the time the
findings are not interpreted in the light of problem being
faced. It is through proper interpretation of result that the
researcher can convey the obvious and latent relationships
that underlie his findings.
Interpretation is the search for a more intense and broader
meaning of the research results. It is an explanation of the
statistical results with the intention of establishing some new
explanatory concepts and at the same time linking these
results with some other previous findings or studies.
•Field Research?
Field research is defined as a qualitative method of data
collection that aims to observe, interact and understand
people while they are in a natural environment.
Field research typically begins in a specific setting although
the end objective of the study is to observe and analyse the
specific behavior of a subject in that setting. The cause and
effect of a certain behavior, though, is tough to analyze due to
presence of multiple variables in a natural environment
, Most of the data collection is based not entirely on cause and
effect but mostly on correlation. While field research looks
for correlation, the small sample sizemakes it difficult to
establish a causal relationshipbetween two or more variables.