Research design description

1. RESEARCH
METHODOLOGY
K B Bindu
Assistant Professor,
Department of Geography,
H M College, Manjeri
UNIT IV

2. UNIT IV CONTENT
INTRODUCTION TO RESEARCH METHODOLOGY.
STEPS OF A RESEARCH PROCESS.
IDENTIFICATION OF A RESEARCH PROBLEM IN
GEOGRAPHY.
APPLICATION OF HYPOTHESIS AND ITS FORMULATION.
USE OF MODELS AND EMPHERICAL TECHNIQUES IN
GEOGRAPHICAL RESEARCH.
INTRODUCTION TO RESEARCH DESIGN.

3. RESEARCH - DEFINITION
“ in the broadest sense of the world ,the definition of
research includes any gathering of data ,information
and facts for the advancement of knowledge” –
Martyan Shuttleworth
Research always begins with a question or a problem

4. Its purpose is to find answers to questions through the
application of systematic and scientific methods
Research is an academic activity
Its an art of scientific investigation
Research in common parlance refers to a search for
knowledge.
It is a careful investigation or inquiry specially through search
for new facts in any branch of knowledge
Research as a movement , a movement from the known to
the unknown .

5. STEPS IN A RESEARCH PROCESS
defining the research problem and reviewing the
literature
formulation of hypothesis
research design : developing the research plan and
implementing the research plan
collecting data
Analyzing data and testing hypothesis
Preparation of report and preliminary analysis
Interpreting and reporting of the findings

6. DEFINING RESEARCH PROBLEM
Identification of research problem – first and foremost step
Research problem , in general refers to some difficulty which a
researcher experiences in the context of either a theoretical or
practical situation and wants to obtain a solution for the same .
Research problem is one which requires a researcher to find
out the best solution for the given problem

7. Research problem -in areas
Exploratory – gathering preliminary information that
may help in defining the problem and suggest hypothesis
Major emphasis- discovery of ideas and clarify concepts
and subsequently make more extensive research
Descriptive – describe things
Casual – to test hypothesis about cause and effect of
relationship

8. Selection of research problem
Researcher has to identified two or more problems
Select a problem based on priority ,limited finance , time
constraints
To choose the problem which is likely to have maximum
net value of research

9. Facts about selection of the research
problem
search for new features
Avoid too narrow to too vague
Research material
Subject is familiar and feasible
Qualification and training
Cost factor
Time factor

10. Steps involved in defining a problem
Statement of the problem in general way
Understanding the nature of the problem
Surveying the available literature
Developing the ideas through discussions
Rephrasing the research problem into a working
proposition

11. Formulations of the problems
It means defining the problems precisely
Formulation of problem is often more essential that is
solution

12. INTRODUCTION TO HYPOTHESIS
Hypothesis is a presumptive statement of a
proposition which the investigator seeks to
prove.
Hypothesis in the theory stated as a testable
proposition formally and clearly and subjected
to empirical or experimental verification.

13. “Hypothesis are single tentative guesses, good hunches
–assumed for use in devising theory or planning
experiments intended to be given a direct experimental
test when possible”. (Eric Rogers, 1966)
“A hypothesis is a conjectural statement of the relation
between two or more variables”. (Kerlinger, 1956)
“Hypothesis is a formal statement that presents the
expected relationship between an independent and
dependent variable.”(Creswell, 1994)

14. NATURE OF HYPOTHESIS
The hypothesis is a clear statement of what is intended to be
investigated. It should be specified before research is
conducted and openly stated in reporting the results.

15. Identify the research objectives
Identify the key abstract concepts involved in the research
Identify its relationship to both the problem statement and the
literature review
A problem cannot be scientifically solved unless it is reduced
to hypothesis form
It is a powerful tool of advancement of knowledge, consistent
with existing knowledge and conducive to further enquiry
It can be tested –verifiable or falsifiable
Hypotheses are not moral or ethical questions
It is neither too specific nor to general
It is a prediction of consequences
It is considered valuable even if proven false

16. IMPORTANCE OF HYPOTHESIS
A researcher’s ‘eye’
It focuses a research
It formulates clear and specific goals
It links related facts
It prevents blind research
It works as a beacon light

17. FUNCTIONS OF HYPOTHESIS
Provides temporary solution to a problem
Leads to formulation of another hypothesis
Provides a definite statement which may be objectivity
tested
Sensitize the researcher to work selectivity
Offers simple means of data collection and verification

18. TYPES OF HYPOTHESIS
Null hypotheses
Alternative hypotheses

19. Null hypothesis
The null hypothesis represents a theory that has
been put forward, either because it is believed to
be true or because it is to be used as a basis for
argument, but has not been proved.
Has serious outcome if incorrect decision is
made.

20. Alternative hypothesis
The alternative hypothesis is a statement of what
a hypothesis test is set up to establish.
Opposite of Null Hypothesis.
Only reached if H0is rejected.
Frequently “alternative” is actual desired
conclusion of the researcher!

21. FORMULATION OF THE HYPOTHESIS
The formulation of the hypothesis basically varies with
the kind of research project conducted:
Qualitative Research
Quantitative Research

22. Testing of Hypothesis
Testing determines the validity of the assumption
Hypothesis testing is based on the basis of
sample data nature
Z-tests
T- tests
Chi-square test
F-test

23. Procedure For Testing Hypothesis
Designing of a hypothesis : If accepting null
hypothesis then the alternative hypothesis will be
rejected and so
Significance level : The difference between actual
and population parameters .
Computations : selecting an appropriate probability
distribution for the testing of hypothesis
Decisions : draw conclusions based on the statistical
tools and devices

24. Z -test
Z-test is used for larger sample
Introduced by Prof. Fisher
Usually for comparison of the mean for sample and
population
Also used to test the significance of median ,mode,
coefficient of correlation

25. T –test
T-test is very popular introduced by W.S Gosset
Based on ‘t’ distribution
Appropriate test for judging the significance of a sample
mean
Useful to test the significance of means of two samples
of small samples when population variance is not known

26. Is based on chi-square distribution
Used for comparing a sample variance to a
theoretical population variance
Chi-square - Test

27. F –test ( ANOVA )
Based on ‘F’ distribution
Used to compare the variance of the two
independent samples
Used for judging the significance of more than
two samples means at one and the same time

28. Non –parametric tests
They do not require length and laborious
computations
Sign tests
Fisher Irwin tests
Mc –Newer test
Signed rank test
Rank sum test
One sample runs test
Spearman’s Rank Correlation
Kendall ‘s co-efficient of concordance

29. USE OF MODELS AND EMPHERICAL
TECHNIQUES
What is a model?
◦ an abstracted representation of reality
What is a mathematical model?
◦ A model built with the ‘tools’ of mathematics
What is a model in Geography?
◦ Use models to simulate effect of actual or
hypothetical set of processes
◦ to forecast one or more possible outcomes

30. Functional model representation
PROCESS
INPUTS OUTPUTS
I O
f(I)
O=f(I)

31. TYPE OF MODEL
Main choice:
Statistical / empirical
 ‘calibration model’
Physically-based
 model physics of interactions
 in Geography, also used to include many empirical
models, if it includes some aspect of physics
 e.g. conservation of mass/energy - e.g. USLE
 similar concepts:
 Theoretical model
 Mechanistic model

32. Type of Mathematical Model
May chose (or be limited to) combination in any
particular situation
Definitions / use varies

33. Other options:
◦ deterministic
 relationship a=f(b) is always same
no matter when, where calculate it
◦ stochastic
 exists element of randomness in relationship
repeated calculation gives different results

34. Type of Environmental Model
Practically, and especially in environmental modeling,
always need to consider:
uncertainty
◦ in measured inputs
◦ in model
◦ and so should have distribution of outputs
scale
◦ different relationships over different scales
 principally consider over time / space

35. Why Modelling?
Improve process / system understanding
◦ by attempting to describe important aspects of
process/system mathematically
e.g.
◦ measure and model to planetary geology /geomorphology to
apply understanding to Earth
◦ build statistical model to understand main factors
influencing system

36. Derive / map information through surrogates
e.g.:
REQUIRE spatial distribution of biomass
DATA spatial observations of microwave backscatter
MODEL model relating backscatter to biomass
Crop biomass map ??
Soil moisture map ??

37. Make past / future predictions from current observations
(extrapolation)
tend to use ‘physically-based’ models
e.g.:
short term:
weather forecasting, economic models
longer term:
climate modeling

38. Interpolation based on limited sample of
observations
- use statistical or physically-based models
e.g.:
◦ vegetation / soil surveys
◦ political surveys

39. How useful are these models?
Model is based on a set of assumptions
‘As long as assumptions hold’, should be valid
When developing model
◦ Important to define & understand assumptions
and to state these explicitly
When using model
◦ important to understand assumptions
◦ make sure model is relevant

40. Statistical / empirical models
Basis: simple theoretical analysis or empirical
investigation gives evidence for relationship
between variables
Basis is generally simplistic or unknown, but
general trend seems predictable
Using this, a statistical relationship is proposed

41. Statistical / empirical models
E.g.:
 From observation & basic theory, we observe:
◦ vegetation has high NIR reflectance & low red
reflectance
◦ different for non-vegetated
FCC NDVI

42. Which type of model to use?
Statistical
◦ advantages
 simple to formulate
 generally quick to calculate
 require little / no knowledge of underlying
(e.g. physical) principles
 (often) easy to invert
as have simple analytical formulation

43. Statistical
◦ disadvantages
 may only be appropriate to limited range of
parameter
 may only be applicable under limited
observation conditions
 validity in extrapolation difficult to justify
 does not improve general understanding of
process

44.  Physical/Theoretical/Mechanistic
◦ advantages
 if based on fundamental principles,
applicable to wide range of conditions
 use of numerical solutions (& fast
computers) allow great flexibility in
modelling complexity
 may help to understand process
e.g. examine role of different assumptions

45. Physical/Theoretical/Mechanistic
◦ disadvantages
 more complex models require more time to
calculate
get a bigger computer!
 Supposition of knowledge of all important
processes and variables as well as
mathematical formulation for process
 often difficult to obtain analytical solution
 often tricky to invert

46. Research design is the plan , structure and strategy of
investigation conceived so as to obtain answers to
research questions and control variance -KERLINGER
Research design is the arrangement of conditions for
collection and analysis of data in a manner that aims to
combine relevance to the research purpose with
economy in procedure – CLAIRE SELLTIZ
Research Design – definition

47. Research design as a blue print for the collection ,
measurement and analysis of data –BERNHARD PHILIPS
Research design provides a flow of activities from
problem formulation to hypothesis development to a
data collection to data analysis to final results to
implications - S.L.GUPTA & HITESH GUPTA
In short…..
“the plan, structure, and strategy of investigation conceived
so as to obtain answers to research question and control
variance”

48. Design Of Research –Exploratory / Conclusive
Descriptive / Casual Or Experimental )
Type of data required for information gathering
Measurement and scaling requirements
Form of data collection such as questionnaire
Sampling process and sampling size required
Data analysis to be done
A research design provides

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Decisions regarding
what, where, when, how much ????....
Research design would depend upon
 Questions which research is expected to answer
 Variables involved in the research
 Measurement of the variables

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The important features of a research design
a plan
specifies the sources & types of information relevant to
the research problem
a strategy
which approach be used for gathering and analyzing the
data.
the time and cost budgets
most studies are done under these two constraints

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Research design must, at least, contain
a clear statement of the research problem;
procedures and techniques to be used for gathering
information;
the population to be studied;
methods to be used in processing and analyzing data

52. TYPES OF RESEARCH DESIGN
Design of Exploratory or Formulative Studies.
Design of Descriptive Studies.
Design of Diagnostic Studies
Design of Experimental studies.
Design of Non experimental studies.

53. EXPLORATORY DESIGN
Are usually more appropriate in the case of problems
with little knowledge.
It will be effective in and turn out fruitful if the
following methods are adopted
(a) The survey of concerning literature.
(b) Experience survey
(c) Analysis of insight stimulation

54. DESCRIPTIVE STUDIES DESIGN
Aims at portraying accurately the characteristics of a
particular group or situation.
It is the geared solution for a specific problem by the
discovery of relevant variables that are associated with it
in varying degrees

55. EXPERIMENTAL DESIGN
Prof .R..A Fisher is associated with this design.
It is most commonly linked with laboratory works.
The observer can observe the effect of independent
variable on the dependable variable.
It is used to test the causal hypothesis.
Purpose is to studies is to test a hypothesis of causal
relationship between variables

56. DIAGNOSTIC DESIGN
determine the frequency with which something
occurs
or its association with something else

57. NON EXPERIEMNTAL DESIGN
Do not involves a manipulation of the situation,
circumstances or experience of the participants.
it is classified into 3 types
 Relational design
 Comparative research design
 Longitudinal research design

59. Comparison Of Basic Research
Design
Exploratory Descriptive Casual
objective Discovery of
ideas and
insights
Describe market
characteristics of
functions
Determine cause
and effect
relationship
Characteristics Flexible ,
versatile
Marked by the
prior formulation
of specific
hypothesis
Manipulation of
one or more
independent
variables
Often the front
end of total
research design
Preplanned and
structured
design
Control of other
mediating
variables
Methods Expert surveys
Pilot surveys
Secondary data
Qualitative
research
Secondary data
Surveys panels
Observation and
other data
Experiments

60. CONCLUSION
 Research design is a systematic plan to study a
scientific problem.
 There are various types of designs used according
to the nature and character of the research topic.
 A research scholar must be aware of available
tools and models before selecting the
methodology and applying it in research design.

61. THANK YOU…