Synopsis Development for Post Graduate Student

Below is the format for Synopsis Development for Student Researchers. If more information is required, do feel free to contact. 

ANNEXURE—II

             PROFORMA FOR REGISTRATION OF SUBJECTS FOR DISSERTATION

	1.		NAME OF THE CANDIDATE AND ADDRESS		:
	2.		NAME OF INSTITUTE		:
	3.		COURSE OF STUDY AND SUBJECT		:
	4.		DATE OF ADMISSION TO COURSE		:
	5.		TITLE OF THE TOPIC		:
	6 6.1 6.2 6.3 6.4 6.5			Brief Resume of the intended work: INTRODUCTION:                     REVIEW OF LITERATURE : NEED FOR THE STUDY: RESEARCH QUESTION: OBJECTIVES:.
7 7.1 7.2 7.3 7.4		MATERIALS AND METHODS Source of Data:                 Methods of collection of data:       Study Design:       Study Period:       Data collection:       Study Population:         Sample Size :-  Sample Technique:      Inclusion Criteria:                     Exclusion Criteria:       Study Procedure: Data Collection: ANALYSIS: Does the study require any Investigation to be conducted on patients or other humans or animals? If so describe briefly. No  Has the ethical clearance been obtained from your institutional in case 7.3? Awaited. References:

9.	Name and Signature of candidate
10.	Remarks of the guide
11.	Name & Designation of
	11.1 Guide
	11.2 Signature
	11.3 Co-guide
	11.4 Signature
12	12.1  Head of the Department
	12.2 Signature
13	13.1Chairman, Institutional Ethical Committee
	13.2 Remarks/ Signature
14	14.1 Principal
	14.2 Remarks/Signature

Time Plan:

Phases	Time Period	Outline of Plan
Phase I Phase II Phase III Phase IV

VARIABLES AND TYPES OF VARIABLES

Variable is central idea in research.  Simply defined, variable is a concept that varies.  There are two
types of concepts: those that refer to a fixed phenomenon and those that vary in quantity, intensity, or
amount (e.g. amount of education).  The second type of concept and measures of the concept are
variables.  A variable is defined as anything that varies or changes in value.  Variables take on two or
more values.  Because variable represents a quality that can exhibit differences in value, usually
magnitude or strength, it may be said that a variable generally is anything that may assume different
numerical or categorical values.  Once you begin to look for them, you will see variables everywhere. 
For example gender is a variable; it can take two values: male or female.  Marital status is a variable; it
can take on values of never married, single, married, divorced, or widowed.  Family income is a
variable; it can take on values from zero to billions of Rupees. A person’s attitude toward women
empowerment is variable; it can range from highly favorable to highly unfavorable. In this way the
variation can be in quantity, intensity, amount,  or type; the examples can be production units,
absenteeism, gender, religion, motivation, grade, and  age.  A variable may be situation specific; for
example gender is a variable but if in a particular situation like a class of Research Methods if there are
only female students, then in this situation gender will not be considered as a variable

Types of Variable

1.  Continuous and Discontinuous variables

Variables have different properties and to these properties we assign numerical values.  If the values of a
variable can be divided into fractions then we call it a continuous variable.  Such a variable can take
infinite number of values.  Income, temperature,  age, or a test score are examples of continuous
variables.  These variables may take on values within a given range or, in some cases, an infinite set.
Any variable that has a limited number of distinct values and which cannot be divided into fractions, is a
discontinuous variable.  Such a variable is also called as categorical variable or classificatory variable,
or  discrete variable.  Some variables have only two values, reflecting the presence or absence of a
property: employed-unemployed or male-female have  two values.  These variables are referred to as
dichotomous.  There are others that can take added categories such as the demographic variables of race,
religion.  All such variables that produce data that fit into categories are said to be
discrete/categorical/classificatory, since only certain values are possible. An automotive variable, for
example, where “Chevrolet” is assigned a 5 and “Honda” is assigned a 6, provides no option for a 5.5
(i.e. the values cannot be divided into fractions).

2.  Dependent and Independent Variables

Researchers who focus on causal relations usually begin with an effect, and then search for its causes. 
The cause variable, or the one that identifies forces or conditions that act on something else, is the
independent variable.  The variable that is the effect or is the result or outcome of another variable is the
dependent variable (also referred to as outcome variable or effect variable).  The independent variable is
“independent of” prior causes that act on it, whereas the dependent variable “depends on” the cause.
It is not always easy to determine whether a variable is independent or dependent.  Two questions help
to identify the independent variable.  First, does it come before other variable in time?  Second, if the
variables occur at the same time, does the researcher suggest that one variable has an impact on another
variable?  Independent variables affect or have an impact on other variables.  When independent
variable is present, the dependent variable is  also present, and with each unit of increase in the
independent variable, there is an increase or decrease in the dependent variable also.  In other words, the
variance in dependent variable is accounted for by the independent variable. Dependent variable is also
referred to as criterion variable.
In statistical analysis a variable is identified by  the symbol (X) for independent variable and by the
symbol (Y) for the dependent variable.  In the research vocabulary different labels have been associated
with the independent and dependent variables like:

   Independent variable     Dependent variable
   Presumed cause     presumed effect
  Stimulus     Response
  Predicted from …    Predicted to …
  Antecedent     Consequence
  Manipulated     Measured outcome
  Predictor     Criterion                  .

Research studies indicate that successful new product development has an influence on the stock market
price of a company.  That is, the more successful the new product turns out to be, the higher will be the
stock market price of that firm.  Therefore, the success of the 
New product is the independent variable, and stock market price the dependent variable.
The degree of perceived success of the new product developed will explain the variance in the stock
market price of the company.
It is important to remember that there are no preordained variables waiting to be discovered “out there”
that are automatically assigned to be independent or dependent.  It is in  fact the product of the
researcher’s imagination demonstrated convincingly.

3.  Moderating Variables

A moderating variable is one that has a strong contingent effect on the independent variable-dependent
variable relationship.  That is, the presence of a third variable (the moderating variable) modifies the
original relationship between the independent and the dependent variable.
For example, a strong relationship has been observed between the quality of library facilities (X) and the
performance of the students (Y).  Although this relationship is supposed to be true generally, it is
nevertheless contingent on the interest and inclination of the students. It means that only those students
who have the interest and inclination to use the library will show improved performance in their studies.
In this relationship interest and inclination is moderating variable i.e. which moderates the strength of
the association between X and Y variables.   

4. Intervening Variables

A basic causal relationship requires only independent and dependent variable.  A third type of variable,
the  intervening variable, appears in more complex causal relationships.  It comes between the
independent and dependent variables and shows the link or mechanism between them. Advances in
knowledge depend not only on documenting cause and  effect relationship but also on specifying the
mechanisms that account for the causal relation. In a sense, the intervening variable acts as a dependent
variable with respect to independent variable and acts as an independent variable toward the dependent
variable.
A theory of suicide states that married people are less likely to commit suicide than single people.  The
assumption is that married people have greater social integration (e.g. feelings of belonging to a group
or family). Hence a major cause of one type of suicide was that people lacked a sense of belonging to
group (family).  Thus this theory can be restated as a three-variable relationship: marital status
(independent variable) causes the degree of social  integration (intervening variable), which affects
suicide (dependent variable).  Specifying the chain of causality makes the linkages in theory clearer and
helps a researcher test complex relationships.
Look at another finding that five-day work week results in higher productivity.  What is the process of
moving from the independent variable to the dependent variable?  What exactly is that factor which
theoretically affects the observed phenomenon but cannot be seen? Its effects must be inferred from the
effects of independent variable  on the dependent variable. In this work-week hypothesis, one mightview the intervening variable to be the job satisfaction.  To rephrase the statement it could be: the
introduction of five-day work week (IV) will increase job satisfaction (IVV), which will lead to higher
productivity (DV).

5.  Extraneous Variables

An almost infinite number of extraneous variables  (EV) exist that might conceivably affect a given
relationship. Some can be treated as independent or moderating variables, but most must either be
assumed or excluded from the study. Such variables have to be identified by the researcher.  In order to
identify the true relationship between the independent and the dependent variable, the effect of the
extraneous variables may have to be controlled. This is necessary if we are conducting an experiment
where the effect of the confounding factors has to be controlled.  Confounding factors is another name
used for extraneous variables.

Relationship among Variables

Once the variables relevant to the topic of research have been identified, then the researcher is interested
in the relationship among them.  A statement containing the variable is called a proposition.  It may
contain one or more than one variable. The proposition having one variable in it may be called as
univariate proposition, those with two variables as bivariate proposition, and then of course multivariate
containing three or more variables.  Prior to the formulation of a proposition the researcher has to
develop strong logical arguments which could help in establishing the relationship. For example, age at
marriage and education are the two variables that could lead to a proposition: the higher the education,
the higher the age at marriage. What could be the logic to reach this conclusion?  All relationships have
to be explained with strong logical arguments.
If the relationship refers to an observable reality, then the proposition can be put to test, and any testable
proposition is hypothesis.

The Time Dimension in Research

Another dimension of research is the treatment of time.  Some studies give us a snapshot of a single,
fixed time point and allow us to analyze it in detail.  Other studies provide a moving picture that lets us
follow events, people, or sale of products over a period of time. In this way from the angle of time
research could be divided into two broad types:

a.  Cross-Sectional Research.  In  cross-sectional research, researchers observe at one point in
time. Cross-sectional research is usually the simplest and least costly alternative.  Its
disadvantage is that it cannot capture the change processes. Cross-sectional research can be
exploratory, descriptive, or explanatory, but it is most consistent with a descriptive approach to
research.
b.  Longitudinal Research.  Researchers using longitudinal research examine features of people or
other units at more than one time.  It is usually more complex and costly than cross-sectional
research but it is also more powerful, especially when researchers seek answers to questions
about change.  There are three types of longitudinal research: time series, panel, and cohort.

CLASSIFICATION OF RESEARCH

Research comes in many shapes and sizes.  Before a  researcher begins to conduct a study, he or she
must decide on a specific type of research.  Good researchers understand the advantages and
disadvantages of each type, although most end up specializing in one.
For classification of research we shall look from four dimensions: 
1.  The purpose of doing research;
2.  The intended uses of research;
3.  How it treats time i.e. the time dimension in research; and 
4.  The research (data collection) techniques used in it.
The four dimensions reinforce each other; that  is, a purpose tends to go with certain techniques and
particular uses.  Few studies are pure types, but the dimensions simplify the complexity of conducting
research.

1.  Purpose of Doing Research 

If we ask someone why he or she is conducting a study, we might get a range of responses: “My boss
told me to do”; “It was a class assignment”; “I was curious.” There are almost as many reasons to do
research as there are researches.  Yet the purposes of research may be organized into three groups based
on what the researcher is trying to accomplish – explore a new topic, describe a social phenomenon, or
explain why something occurs.  Studies may have multiple purposes (e.g. both to explore and to
describe) but one purpose usually dominates.
 
a. Exploratory/Formulative Research

You may be  exploring a new topic or issue in order to learn about it.  If the issue was new or the
researcher has written little on it, you began at the beginning.  This is called exploratory research.  The
researcher’s goal is to formulate more precise questions that future research can answer.  Exploratory
research may be the first stage in a sequence of  studies. A researcher may need to know enough to
design and execute a second, more systematic and extensive study.
Initial research conducted to clarify the nature of the problem. When a researcher has a limited
amount of experience with or knowledge about a research issue, exploratory research is useful
preliminary step that helps ensure that a more rigorous, more conclusive future study will not begin with
an inadequate understanding of the nature of the management problem.  The findings discovered
through exploratory research would the researchers to emphasize learning more about the particulars of
the findings in subsequent conclusive studies.
Exploratory research rarely yields definitive answers.  It addresses the “what” question: “what is this
social activity really about?”  It is difficult to conduct because there are few guidelines to follow. 
Specifically there could be a number of goals of exploratory research.

Goals of Exploratory Research:

1.  Become familiar with the basic facts, setting, and concerns;
2.  Develop well grounded picture of the situation;
3.  Develop tentative theories,  generate new ideas, conjectures, or hypotheses; 
4.  Determine the feasibility of conducting the study;
5.  Formulate questions and refine issues for more systematic inquiry; and 
6.  Develop techniques and a sense of direction for future research.
7.  Test a theory’s predictions or principles

2.  The Uses of Research
Some researchers focus on using research to advance general knowledge, whereas others use it to solve
specific problems.  Those who seek an understanding of the fundamental nature of social reality are
engaged in basic research (also called academic research or pure research or fundamental research).
Applied researchers, by contrast, primarily want to apply and tailor knowledge to address a specific
practical issue.  They want to answer a policy question or solve a pressing social and economic problem.

a. Basic Research

Basic research advances fundamental knowledge about the human world. It focuses on refuting or
supporting theories that explain how this world operates, what makes things happen, why social
relations are a certain way, and why society changes.  Basic research is the source of most new scientific
ideas and ways of thinking about the world.  It can be exploratory, descriptive, or explanatory; however,
explanatory research is the most common.
Basic research generates new ideas, principles and theories, which may not be immediately utilized;
though are the foundations of modern progress and development in different fields.  Today’s computers
could not exist without the pure research in mathematics conducted over a century ago, for which there
was no known practical application at that time.
Police officers trying to prevent delinquency or counselors of youthful offenders may see little relevance
to basic research on the question, “Why does deviant behavior occur?”  Basic research rarely helps
practitioners directly with their everyday concerns.   Nevertheless, it stimulates new ways of thinking
about deviance that have the potential to revolutionize and dramatically improve how practitioners deal
with a problem. 
A new idea or fundamental knowledge is not generated only by basic research.  Applied research, too,
can build new knowledge.  Nonetheless, basic research is essential for nourishing the expansion of
knowledge.  Researchers at the center of the scientific community conduct most of the basic research.

Rationalism

Science is fundamentally a rational activity, and the scientific explanation must make sense. Religion
may rest on revelations, custom, or traditions, gambling on faith, but science must rest on logical reason.
There are two distinct logical systems important to the scientific quest, referred to as deductive logic
and inductive logic. Beveridge describes them as follows:

Logicians distinguish between inductive reasoning (from particular instances to general
principles, from facts to theories) and deductive reasoning (from the general to the particular,
applying a theory to a particular case).  In induction one starts from observed data and
develops a generalization which explains the relationships between the objects observed.  On
the other hand, in deductive reasoning one starts from some general law and applies it to a
particular instance.

The classical illustration of deductive logic is the familiar syllogism: “All men are mortal; Mahmood is
man; therefore Mahmood is mortal.”  A researcher might then follow up this deductive exercise with an
empirical test of Mahmood’s mortality.
Using inductive logic, the researcher might begin by noting that Mahmood is mortal and observing a
number of other mortals as well.  He might then note that all the observed mortals were men, thereby
arriving at the tentative conclusion that all men are mortal. 
In practice, scientific research involves both inductive and deductive reasoning as the scientist shifts
endlessly back and forth between theory and empirical observations.
There could be some other aspects of scientific method (e.g. self correcting) but what is important is that
all features are interrelated.  Scientists may not adhere to all  these characteristics.  For example,
objectivity is often violated especially in the study of human behavior, particularly when human beings
are studied by the human beings.  Personal biases of the researchers do contaminate the findings. 
Looking at the important features of scientific method one might say that there are two power bases of
scientific knowledge: (1) empiricism i.e. sensory experiences or observation, and (2) rationalism i.e. the
logical explanations for regularity and then consequent ional argumentation for making generalizations
(theory). 

Finally it may be said that anybody who is following the scientific procedure of doing research is doing
a scientific research; and the knowledge generated by such research is scientific knowledge. Depending
upon the subject matter, we try to divide the sciences into physical or natural sciences and the social
sciences.  Due to the nature of the subject matter of the social sciences, it is rather very difficult to apply
the scientific method of research rigorously and that is why the predictions made by the social
researchers are not as dependable as the predictions made by the natural scientists.

Ethical and Ideological Neutrality

The conclusions drawn through interpretation of the results of data analysis should be objective; that is,
they should be based on the facts of the findings derived from actual data, and not on our own subjective
or emotional values.  For instance, if we had a hypothesis that stated that greater participation in
decision making will increase organizational commitment, and this was not supported by the results, it
makes no sense if the researcher continues to  argue that increased opportunities for employee
participation would still help. Such an argument would be based, not on the factual, data based research
findings, but on the subjective opinion of the researcher. If this was the conviction of the researcher all
along, then there was no need to do the research in the first place.
Researchers are human beings, having individual ideologies, religious affiliations, cultural differences
which can influence the research findings.  Any interference of their personal likings and dis-likings in
their research can contaminate the purity of the data, which ultimately can affect the predictions made
by the researcher.  Therefore, one of the important characteristics of scientific method is to follow the
principle of objectivity, uphold neutrality, and present the results in an unbiased manner.

Important Characteristics of Scientific Method

1. Empirical

Scientific method is concerned with the realities that are observable through “sensory experiences.” It
generates knowledge which is verifiable by experience or observation. Some of the realities could be
directly observed, like the number of students present in the class and how many of them are male and
how many female. The same students have attitudes, values, motivations, aspirations, and commitments. 
These are also realities which cannot be observed directly, but the researchers have designed ways to
observe these indirectly.  Any reality that cannot be put to “sensory experience” directly or indirectly
(existence of heaven, the Day of Judgment, life hereafter, God’s rewards for good deeds) does not fall
within the domain of scientific method.

2. Verifiable

Observations made through scientific method are to be verified again by using the senses to confirm or
refute the previous findings. Such confirmations may have to be made by the same researcher or others. 
We will place more faith and credence in those findings and conclusions if similar findings emerge on
the basis of data collected by other researchers using the same methods.  To the extent that it does
happen (i.e. the results are replicated or repeated) we will gain confidence in the scientific nature of our
research.  Replicability, in this way, is an important characteristic of scientific method.  Hence
revelations and intuitions are out of the domain of scientific method. 

3.  Cumulative

Prior to the start of any study the researchers try to scan through the literature and see that their study is
not a repetition in ignorance.  Instead of reinventing the wheel the researchers take stock of the existing
body of knowledge and try to build on it.  Also the researchers do not leave their research findings into
scattered bits and pieces.  Facts and figures are to be provided with language and thereby inferences
drawn.  The results are to be organized and systematized.  Nevertheless, we don’t want to leave our
studies as stand alone. A linkage between the present and the previous body of knowledge has to be
established, and that is how the knowledge accumulates.  Every new crop of babies does not have to
start from a scratch; the existing body of knowledge provides a huge foundation on which the
researchers build on and hence the knowledge keeps on growing.

4.  Deterministic

Science is based on the assumption that all events have antecedent causes that are subject to
identification and logical understanding. For the scientist, nothing “just happens” – it happens for a
reason. The scientific researchers try to explain the emerging phenomenon by identifying its causes.  Of
the identified causes which ones can be the most important? For example, in the 2006 BA/BS
examination of the Punjab University 67 percent of the students failed.  What could be the determinants
of such a mass failure of students?  The researcher may try to explain this phenomenon and come up
with variety of reasons which may pertain to students, teachers, administration, curriculum, books,
examination system, and so on.  Looking into such a large number of reasons may be highly
cumbersome model for problem solution.  It might be appropriate to tell, of all these factors which one
is the most important, the second most important, the third most important, which two in combination
are the most important.  The researcher tries to narrow down the number of reasons in such a way that
some action could taken.  Therefore, the achievement of a meaningful, rather than an elaborate and
cumbersome, model for problem solution becomes a critical issue in research. That is parsimony which
implies the explanation with the minimum number of variables that are responsible for an undesirable
situation.