Research Methodology
Dr. Kanchan Fulmali
1 Introduction to Research
Features and Importance of research in
business, Objectives and Types of research-
Basic, Applied, Descriptive, Analytical and
Empirical Research.
Formulation of research problem, Research
Design, significance of Review of Literature
Hypothesis: Formulation, Sources, Importance
and Types
Sampling: Significance, Methods, Factors
determining sample size
Systematic investigative process employed
to increase or revise current knowledge by
discovering new facts. It is divided into
two general categories.
• Basic research is inquiry aimed at
increasing scientific knowledge, and
• Applied research is effort aimed at
using basic research for solving
problems or developing new processes,
products, or techniques.
1. Should be systematic in nature.
2. Should be logical.
3. Should be empirical and replicable in nature.
4. Should be according to plans.
5. Should be according to the rules and the
assumptions should not be based on the false
bases or judgments.
6. Should be relevant to what is required.
7. Procedure should be reproducible in nature.
8. Controlled movement of the research
procedure.
Money
Management
Experimental
Formulation Of research Problem
Hypothesis
In science, a hypothesis is an idea
or explanation that you then test
through study and
experimentation. Outside
science, a theory or guess can
also be called a hypothesis.
“A Hypothesis is a conjectural
statement, a tentative
proposition about relation
between two or more
phenomena or variables”. It is a
tentative generalization, the
validity of which remains to be
tested.
The etymological meaning of hypothesis, therefore, is a
theory which is not full reasoned, derived out of the
combination of two words ‘hypo’ and ‘thesis’ meaning
‘less than’ and ‘reasoned theory of rational view point’
respectively.
Accordingly Mill defines hypothesis as “any supposition
which we make (either without actual evidence or an
evidence avowedly insufficient) in order to endeavor to
deduce conclusions in accordance with facts which are
known to be real, under the idea that if the conclusions
to which the hypothesis leads are known truths, the
hypothesis itself either must be or at least likely to be,
true”.
Likewise, Goode and Hatt define it as “a proposition
which can be put to test to determine validity”.
P.V. Young says that a hypothesis “is
provisional central idea which becomes
the basis for fruitful investigation,
known as working theory”
Coffey defines hypothesis as “an
attempt at explanation : a provisional
supposition made in order to explain
scientifically some facts or
phenomena”.
There are five steps in hypothesis
Define problem
Find out reasons
Visit respondents
Use segmentation for data collection
Articulate hypothesis
SOURCE OF HYPOTHESIS :-
General culture.
Scientific theories
Analogy.
Personal experience.
Null hypotheses
These are used when the researcher believes there is no relationship
between two variables or when there is inadequate theoretical or
empirical information to state a research hypothesis
Null hypotheses can be:
simple or complex;
associative or causal.
Simple hypothesis - this predicts the relationship between
a single independent variable (IV) and a single dependent
variable (DV)
For example: Lower levels of exercise postpartum (IV)
will be associated with greater weight retention (DV).
Complex hypothesis - this predicts the relationship
between two or more independent variables and two or
more dependent variables.
Directional hypotheses : These are usually derived from theory. They may
imply that the researcher is intellectually committed to a particular
outcome. They specify the expected direction of the relationship between
variables i.e. the researcher predicts not only the existence of a
relationship but also its nature.
Non-directional hypotheses: Used when there is little or no theory, or
when findings of previous studies are contradictory. They may imply
impartiality. Do not stipulate the direction of the relationship.
Associative hypotheses: Propose relationships between variables -
when one variable changes, the other changes. Do not indicate cause
and effect.
Causal hypotheses: Propose a cause and effect interaction between
two or more variables. The independent variable is manipulated to
cause effect on the dependent variable. The dependent variable is
measured to examine the effect created by the independent variable.
Testable hypotheses
Contain variables that are measurable or able
to be manipulated.
They need to predict a relationship that can be
'supported' or 'not
supported' based on data collection and
analysis.
Research Hypotheses:
Ho: Null Hypothesis
H1: Alternative Hypothesis Attributive Associative Causal Null vs.
Alternative Hypothesis : What we are attempting to demonstrate
(or support) Descriptive Predictive Causal (Understanding)
Attributive Research Hypothesis states that a behavior exists can
be measured, and can be distinguished from other similar
behaviors We can “describe” something
H1: Most of the population has heard of Disneyland.
H2: Disneyland visitors are diverse in demographics.
H3: Most of the population is ready to visit Disneyland.
Associative Research Hypothesis states that a relationship exists
between two behaviors Knowing the amount or kind of one
behavior helps you to predict the amount or kind of the other
behavior
H1: Knowledge of Disneyland is associated with visiting Disneyland.
H2: Income level is correlated with visiting Disneyland.
H3: People who live closer to Disneyland are more apt to visit
Disneyland. Corresponds with Predictive Knowledge Bivariate
hypothesis (two variables)
Causal Research Hypothesis states that differences in the
amount or kind of one behavior causes differences in
amount or kind of the other behavior
H1: Frequent exposure to Disneyland advertising results
in increased attendance at the Disneyland.
H2: An increase in consumer confidence translates into
increased attendance at Disneyland.
H3: Discount tickets for local residents produces an
increase in the crowds at Disneyland. To support a causal
hypothesis: demonstrate a statistical relationship
temporal precedence elimination of alternative
explanations
Sampling
Significance
a large sample size is more representative of the population,
limiting the influence of outliers or extreme observations.
A sufficiently large sample size is also necessary to produce
results among variables that are significantly different.
a large sample size broadens the range of possible data and
forms a better picture for analysis.
Sample size is also important for economic and ethical
reasons.
an over-sized one uses more resources than are necessary.
In an experiment involving human or animal subjects, sample
size is a essential issue for ethical reasons.
An under-sized experiment exposes the subjects to
potentially harmful treatments without advancing knowledge.
In an over-sized experiment, an unnecessary number of
subjects are exposed to a potentially harmful treatment, or
are denied a potentially beneficial one.
Have a
Beautiful
Night
