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Research Methodology
“A systematic effort to gain new knowledge.
“A careful investigation or enquiry especially through search for a new facts in any branch of knowledge.”
A careful consideration of study regarding a particular concern or problem using scientific methods. According to the American sociologist Earl Robert Babbie, “Research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. Research involves inductive and deductive methods.”
Inductive research methods are used to analyze an observed event. Deductive methods are used to verify the observed event. Inductive approaches are associated with qualitative research and deductive methods are more commonly associated with quantitative research.
Research in common parlance refers to a search for knowledge. One can also define research as a scientific and systematic search for pertaining information on a specific topic.
In fact, research is an art of scientific investigation.
According to Clifford Woody research comprises defining, and redefining problems, formulating hypothesis of suggested solutions; collecting, organising and evaluating data; making deductions and reaching conclusions; and at last carefully testing the conclusions to determine whether they fit the formulating hypothesis.
Research is conducted with a purpose to understand:
· What do organizations or businesses really want to find out?
· What are the processes that need to be followed to chase the idea?
· What are the arguments that need to be built around a concept?
· What is the evidence that will be required for people to believe in the idea or concept?
Characteristics of research
1. A systematic approach must be followed for accurate data. Rules and procedures are an integral part of the process that set the objective. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
Objectives of research: The purpose of research is to discover answers to questions through the application of scientific procedures. The main aim of research is to find out the truth which is hidden and which has not been discovered as yet.
The objectives of research are as follows:
2. To portray accurately the characteristics of a particular individual, situation or a group
3. To determine the frequency with which something occurs with which it is associated with
4. To test a hypothesis of a casual relationship between variables (Hypothesis testing research)
Types of research: The basic types of research are as follows:
(i) Descriptive vs Analytical: descriptive research includes serveys and fact finding enquiries of
(ii) Applied vs fundamental: Research can either be applied( or action) research or fundamental (to
(iii) Quantitative vs. Qualitative: Quantitative research is based on the measurement of quantity or
(iv) Conceptual vs. Empirical: Conceptual research is that related to some abstract ideas or theory.
(v) Some other types of Research:
Research Process: Research process consists of series of actions or steps necessary to effectively carry out research and the desired sequencing of these steps.
1. Formulating the research problem: There are two types of research problems, viz.,those which
Criteria of Good research: Researcher expects scientific research to satisfy the following criteria:
Research Problem Formulation: The research problem undertaken for study must be carefully selected. A problem must spring from the researcher’s mind like a plant springing from its own seed.
Techniques involved in defining a problem:
e. Rephrasing the research problem
Unit II & III (Combined)
Research Design:
Research design, in fact, has a great bearing on the reliability of the results arrived at and as such constitutes the firm foundation of the entire edifice(Bhawan) of the research work.
Important concept relating to research design:
1. Dependent and independent variables: A concept which can take on different quantitative value is called a variable. As such the concepts like weight, height, income are all examples of variables.
2. Extraneous variable: Independent variables that are not related to the purpose of study, but may affect the dependent variable are termed as ' extraneous variables'.
3. Control: One important characteristics of a good Research Design is to minimise the influence or effect meaning of extraneous variables. The technical term ' control' is used when we design the study minimising the effects of extraneous independent variables. i.e., to restrain experimental conditions.
4. Confounded relationship: when the dependent variable is not free from the influence of extraneous variable, the relationship between the dependent and independent variables is said to be confounded by an extraneous variables.
5. Research hypothesis: when the prediction or a hypothesised relationship is to be tested by scientific methods it is termed as research hypothesis. Usually a research hypothesis must contain, at least one independent and one dependent variable.
6. Experimental and non experimental hypothesis testing research: when the purpose of research is to test a research hypothesis, it is termed as hypothesis testing research.
7. Experimental and control groups: In an experimental hypothesis testing research when a group is exposed to usual conditions, it is termed as 'Control group'.
8. Treatments: The different conditions under which experimental and control groups are put are usually referred to as 'Treatment'.
9. Experiment: The process of examining the truth of a statistical hypothesis, relating to some research problem, is known as experiment.
10. Experimental units: The predetermined plots or blocks where different treatments are used are known as experimental units.
Different Research Design: Different research designs can be conveniently described if we categorised them as:
(i) Before-and-after without control design: In such a design a single test group
or area is selected and the dependent variable is measured before the introduction of the treatment. The treatment is then introduced and the dependent variable is measured again after the treatment has been introduced.
(ii) After-only with control design: In this design two groups or area are selected and the treatment is introduced into the test area only. The dependent variable is then measured in both the areas at the same time. Treatment impact is assessed by subtracting the value of the dependent variable in the control area from its value in the test area.
(iii) Before-and-after with control design: In this design two areas are selected and the dependent variable is measured in both the areas for an identical time-period before the treatment. The treatment is then introduced into the test area only, and the dependent variable is measured in both for an identical time-period after the introduction of the treatment. The treatment effect is determined by subtracting the change in the dependent variable in the control area from the change in the dependent variable in test area.
i) Completely randomised design (C.R. Design): Involves only two principles viz., the principle of replication and the principle of randomisation of experimental designs.
(a) Two group simple randomised design:
(b) Simple replications design:
(ii) Randomised block design: R.B design is an improvement over the C.R. Design. In R.B design, subjects are first divided into groups, known as blocks, such that within each group the subjects are relatively homogenous in respect to some selected variable.
(iii)Latin Square design (L.S.Design): L.S design is an experimental design very frequently used in agricultural research.The conditions under which agricultural investigations are carried out are different from those in other studies for nature plays an important role in agriculture.
(iv) Factorial designs: Factorial designs are used in experiments where the effects of varying more than one factor are to be determined. They are specially important in several economic and social phenomena where usually a large number of factors are affect a particular problem.
Sampling Design: All items in any field of enquiry constitute a ‘Universe’ or ‘Population’. A complete enumeration of all items in the ‘population’ is known as a census enquiry.
Steps in Sample Design: The researcher must pay attention of the following:
(i) Types of universe: The first step in developing any sample design is to clearly define the set of objects, technically called the ‘Universe, to be studied. The universe can be finite or infinite.
(ii) Sampling Unit: Sampling unit may be a geographical one such as state, district, village, etc., or construction unit such as house, flat, etc., or it may be a social unit such as family, club, school, etc., or it may be an individual.
(iii)Source List: It is also known as ‘sampling frame’ from which sample is to be drawn. It contains the names of all items of a universe. If source list is not available, researcher has to prepare it. Such a list should be comprehensive, correct, reliable and appropriate.
(iv)Size of sample: This refers to the number of items to be selected from the universe to constitute a sample. The size of sample should neither be excessively large, nor too small. It should be optimum.
(v)Parameters of interest: In determining the sample design, one must consider the question of the specific population parameters which are of interest. There may also be important sub-groups in the population about whom we would like to make estimates.
(vi)Budgetary constraint: Cost consideration, from practical point of view, have a major impact upon decision relating to not only the size of the sample but also to the type of sample.
(vii) Sampling procedure: The researcher must decide the type of sample he will use i.e., this technique or procedure stands for the sample design itself. There are several sample designs out of which the researcher must choose one for study. He must select that design which, for a given sample size and for a given cost, has a smaller sampling error.
Measurement in Research: Measurement is defined as process of associating numbers or symbols to observations obtained in a research study. These observation could be qualitative or quantitative. It is difficult to measure abstract or qualitative characteristics than quantitative characteristics. It is easy to measure properties like weight, height etc. by some standard.
Objectives of research: The purpose of research is to discover answers to questions through the application of scientific procedures. The main aim of research is to find out the truth which is hidden and which has not been discovered as yet.
The objectives of research are as follows:
1. To gain familiarity with a phenomenon or to achieve new insights into it. Search
(Exploratory or formulated research)
2. To portray accurately the characteristics of a particular individual, situation or a group
(descriptive research)
3. To determine the frequency with which something occurs with which it is associated with
something else( Diagnostic research study)
4. To test a hypothesis of a casual relationship between variables (Hypothesis testing research)
Types of research: The basic types of research are as follows:
Types of research: The basic types of research are as follows:
(i) Descriptive vs Analytical: descriptive research includes serveys and fact finding enquiries of
different kinds. The major purpose of descriptive research is description of the state of affairs as it
exists at present. In social science and business research we quite often use the term Ex Post facto
research for descriptive research studies.
In analytical research, on the other hand, the researcher has to use facts or information already
available, and analyse these to make a critical evaluation of the material.
(ii) Applied vs fundamental: Research can either be applied( or action) research or fundamental (to
basic or pure) research. Applied research aims at finding a solution for an intermediate problem
facing the society or an industry/ business organization. Where as fundamental research is mainly
concerned with generalizations and with the formulation of a Theory.
(iii) Quantitative vs. Qualitative: Quantitative research is based on the measurement of quantity or
amount. Is applicable to phenomena that can be expressed in terms of quantity. Qualitative
research, on the other hand, is concerned with the qualitative phenomenon, i.e., phenomena
relating to or involving quality or kind. Attitude or opinion research i.e., Research Design to find
out how people feel or what they think about a particular subject or institution is also qualitative
research.
(iv) Conceptual vs. Empirical: Conceptual research is that related to some abstract ideas or theory.
It is generally used by philosophers and thinkers to develop new concepts or to reinterpret
existing ones.
On the other hand, empirical research relies on experience or observation alone often without
due regard for system and theory. It is data based research, coming up with conclusions which
are capable of being verified by observation or experiment.
(v) Some other types of Research:
Research Process: Research process consists of series of actions or steps necessary to effectively carry out research and the desired sequencing of these steps.
1. Formulating the research problem: There are two types of research problems, viz.,those which
relates to states of nature and those which relate to relationship between variables. Researcher
must decide the general area of interest or aspect of a subject matter that he would like to enquire
into. Essentially two steps are involved in formulating the research problem, viz., understanding
the problem thoroughly, and rephrasing the same into meaningful terms from an analytical point
of view.
2. Extensive Literature Survey: Once the problem is formulated, a brief summary of it should be
written down. It is compulsory for a research worker writing a thesis for a Ph.D. degree to write a
synopsis of the topic and submit it to the necessary Committee or the Research Board for
Approval.
3. Development of Working Hypothesis: After extensive literature survey, research should state in
clear terms the working hypothesis. Working hypothesis is tentative assumption made in order to
draw out and test its logical or empirical consequences.
4. Preparing the research design: The research problem having been formulated in clear cut terms,
the research will be required to prepare a research design, i.e., he will have to state the conceptual
structure within which research would be conducted.
5. Determining sample design: All the items under consideration if any field of enquiry constitute a
‘Universe’ or ‘population’. A complete enumeration of all items in the ‘population’ is known as a
census inquiry. It can be presumed that in such an inquiry when all the items are covered no
element of chance is left and highest accuracy is obtained.
6. Collecting the data: In dealing with real life problem it is often found that data at hand are
inadequate, and hence, it becomes necessary to collect data that are appropriate. There are several ways of collecting the appropriate data which differ considerably in context of money costs, time
and other resources at the disposal of the researcher.
7. Execution of the Project: Execution of the project is a very important step in the research
process. The researcher should see that the project is executed in a systematic manner and in time.
If the survey is to be conducted by means of structured questionnaires, data can be readily
machine –processed.
8. Analysis of data: After the data have been collected, the researcher turns to the task of analysing
them. The analysis of data requires a number of closely related operations such as establishment of
categories, the application of these categories to raw data through coding, tabulation and then
drawing statistical inferences.
9. Hypothesis Testing: After analysing the data the researcher is in a position to test hypothesis.
Hypothesis testing will result in either accepting the hypothesis or rejecting it. Various test such
as Chi-square test, t-test, F-test have been developed by statisticians for the purpose of hypothesis testing.
10. Generalisations and interpretation: If the hypothesis is tested and upheld several times, it may
be possible for the researcher to arrive at generalisation. i.e., to build a theory. As a matter of fact,
the real value of research lies in its ability at certain generalisations.
If the researcher had no hypothesis to start with , he might seek to explain his findings on the
basis of some theory. It is known as interpretation.
11. Preparation of the report or the thesis: Finally, the researcher has to prepare the report of what
has been done by him. Writing of report must be done with great care keeping in view the
following:
i. Introduction
ii. Summary of findings
iii. Main report
iv. Conclusions
Criteria of Good research: Researcher expects scientific research to satisfy the following criteria:
i. The purpose of the research should be clearly defined and common concepts be used.
ii.The research procedure used should be described in sufficient detail to permit another researcher to repeat the researcher for further advancement, keeping the continuity of what has already been attained.
iii. The Procedural design of the research should be carefully planned to yield results that are as objectives as possible.
iv. The researcher should report with complete frankness, flaws in procedural design and estimate their effects upon the findings.
v. The analysis of data should be sufficiently adequate to reveal its significance and the methods of analysis used should be appropriate. The validity and reliability of the data should be checked carefully.
vi. Conclusions should be confined to those justified by the data of the research and limited to those for which the data provide an adequate basis.
vii. Greater confidence in research is warranted if the researcher is experienced, has a good reputation in research and is a person of integrity.
Research Problem Formulation: The research problem undertaken for study must be carefully selected. A problem must spring from the researcher’s mind like a plant springing from its own seed.
If our eyes need glasses, it is not the optician alone who decides about the number of the loans we require. A research guides can at the most only help a researcher choose a subject.
The following points may be observed by a researcher in selecting a research problem or a subject for research.
a. Subject which is overdone should not be normally choosen, for it will be a difficult task to throw any new light in such a case.
b. Controversial subject should not become the choice of an average researcher.
c. Too narrow or too vague problem should be avoided.
d. The subject selected for research should be familiar and feasible so that the related research material or sources of research are within one’s reach.
e. The importance of the subject, the qualifications and the training of a researcher, the costs involved, the time factor are few other criteria that must also be considered in selecting a problem.
f. The selection of a problem must be preceded by a preliminary study. This may not be necessary when the problem requires the conduct of a research closely similar to one that has already been done.
Techniques involved in defining a problem:
a. Statement of the problem in a general way
b. Understanding the nature of the problem
c. Surveying the available literature
d. Developing the ideas through discussions
e. Rephrasing the research problem
Unit II & III (Combined)
Research Design:
"A 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."
Research design is the conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data.
The designing decisions happen to be in respect of:
(i) what is the study about?
(ii) Why is the study being made?
(iii) Where will the study be carried out?
(iv) What type of data is required?
(v) Where can the required data be found?
(vi) What periods of time will the study include?
(vii) What will be the sample design?
(viii) What techniques of data collection will be used?
(ix) How will the data be analysed?
(x) In what style will the report be prepared?
Preparation of the research design should be done with great care as any error in it may upset the entire project.
Research design, in fact, has a great bearing on the reliability of the results arrived at and as such constitutes the firm foundation of the entire edifice(Bhawan) of the research work.
Important concept relating to research design:
1. Dependent and independent variables: A concept which can take on different quantitative value is called a variable. As such the concepts like weight, height, income are all examples of variables.
If one variable depends upon or is a consequence of the other variable, it is termed as an independent variable and the variable that is antecedent to the dependent variable is termed as independent variable.
2. Extraneous variable: Independent variables that are not related to the purpose of study, but may affect the dependent variable are termed as ' extraneous variables'.
3. Control: One important characteristics of a good Research Design is to minimise the influence or effect meaning of extraneous variables. The technical term ' control' is used when we design the study minimising the effects of extraneous independent variables. i.e., to restrain experimental conditions.
4. Confounded relationship: when the dependent variable is not free from the influence of extraneous variable, the relationship between the dependent and independent variables is said to be confounded by an extraneous variables.
5. Research hypothesis: when the prediction or a hypothesised relationship is to be tested by scientific methods it is termed as research hypothesis. Usually a research hypothesis must contain, at least one independent and one dependent variable.
6. Experimental and non experimental hypothesis testing research: when the purpose of research is to test a research hypothesis, it is termed as hypothesis testing research.
Research in which the independent variable is manipulated is termed ' experimental hypothesis testing research' and a research in which an independent variable is not manipulated is called ' non experimental hypothesis testing research'.
7. Experimental and control groups: In an experimental hypothesis testing research when a group is exposed to usual conditions, it is termed as 'Control group'.
But when the group is exposed to some novel or a special condition, it is termed as experimental group.
8. Treatments: The different conditions under which experimental and control groups are put are usually referred to as 'Treatment'.
9. Experiment: The process of examining the truth of a statistical hypothesis, relating to some research problem, is known as experiment.
10. Experimental units: The predetermined plots or blocks where different treatments are used are known as experimental units.
Different Research Design: Different research designs can be conveniently described if we categorised them as:
a. Research design in case of exploratory research studies: Exploratory research studies are also termed as formulative research studies. The main purpose of such studies is that of formulating a problem for more precise investigation or of developing the working hypothesis from an operational point of view.
b. Descriptive research studies & diagnostic research studies: Descriptive research studies are those studies which are concerned with describing the characteristics of a particular individual or of a group whereas diagnostic research studies determine the frequency with which something occurs or its association with something else.
c. Hypothesis research studies: Hypothesis testing research studies are those where the researcher tests the hypothesis of casual relationship between variables. Such studies require procedures that will not only reduce bias and increase reliability, but will permit drawing inferences about causality. Usually experiments meet this requirement.
Important Experimental Designs: Experimental designs refers to the framework or structure of an experiment and as such there are several experiment designs.
(a) Informal experiment designs:
(i) Before-and-after without control design
(ii) After-only with control design
(iii) Before-and-after with control design
(b) Formal experiment design:
(i) Completely randomised design (C.R. Design)
(ii) Randomised block design (R.B. Design)
(iii) Latin-square design (L-S Design)
(iv) Factorial designs
(i) Before-and-after without control design: In such a design a single test group
or area is selected and the dependent variable is measured before the introduction of the treatment. The treatment is then introduced and the dependent variable is measured again after the treatment has been introduced.
(ii) After-only with control design: In this design two groups or area are selected and the treatment is introduced into the test area only. The dependent variable is then measured in both the areas at the same time. Treatment impact is assessed by subtracting the value of the dependent variable in the control area from its value in the test area.
(iii) Before-and-after with control design: In this design two areas are selected and the dependent variable is measured in both the areas for an identical time-period before the treatment. The treatment is then introduced into the test area only, and the dependent variable is measured in both for an identical time-period after the introduction of the treatment. The treatment effect is determined by subtracting the change in the dependent variable in the control area from the change in the dependent variable in test area.
i) Completely randomised design (C.R. Design): Involves only two principles viz., the principle of replication and the principle of randomisation of experimental designs.
(a) Two group simple randomised design:
(b) Simple replications design:
(ii) Randomised block design: R.B design is an improvement over the C.R. Design. In R.B design, subjects are first divided into groups, known as blocks, such that within each group the subjects are relatively homogenous in respect to some selected variable.
(iii)Latin Square design (L.S.Design): L.S design is an experimental design very frequently used in agricultural research.The conditions under which agricultural investigations are carried out are different from those in other studies for nature plays an important role in agriculture.
(iv) Factorial designs: Factorial designs are used in experiments where the effects of varying more than one factor are to be determined. They are specially important in several economic and social phenomena where usually a large number of factors are affect a particular problem.
Sampling Design: All items in any field of enquiry constitute a ‘Universe’ or ‘Population’. A complete enumeration of all items in the ‘population’ is known as a census enquiry.
A sample plan is a definite plan for obtaining a sample from a given population. It refers to the technique of the procedure the researcher would adopt in selecting items for the sample. Sample design may as well lay down the number of items to be included in the sample i.e., the size of the sample. Sample design is determined before data are collected. Researcher must select/prepare a sample design which should be reliable and appropriate for his research study.
Steps in Sample Design: The researcher must pay attention of the following:
(i) Types of universe: The first step in developing any sample design is to clearly define the set of objects, technically called the ‘Universe, to be studied. The universe can be finite or infinite.
(ii) Sampling Unit: Sampling unit may be a geographical one such as state, district, village, etc., or construction unit such as house, flat, etc., or it may be a social unit such as family, club, school, etc., or it may be an individual.
(iii)Source List: It is also known as ‘sampling frame’ from which sample is to be drawn. It contains the names of all items of a universe. If source list is not available, researcher has to prepare it. Such a list should be comprehensive, correct, reliable and appropriate.
(iv)Size of sample: This refers to the number of items to be selected from the universe to constitute a sample. The size of sample should neither be excessively large, nor too small. It should be optimum.
(v)Parameters of interest: In determining the sample design, one must consider the question of the specific population parameters which are of interest. There may also be important sub-groups in the population about whom we would like to make estimates.
(vi)Budgetary constraint: Cost consideration, from practical point of view, have a major impact upon decision relating to not only the size of the sample but also to the type of sample.
(vii) Sampling procedure: The researcher must decide the type of sample he will use i.e., this technique or procedure stands for the sample design itself. There are several sample designs out of which the researcher must choose one for study. He must select that design which, for a given sample size and for a given cost, has a smaller sampling error.
Measurement in Research: Measurement is defined as process of associating numbers or symbols to observations obtained in a research study. These observation could be qualitative or quantitative. It is difficult to measure abstract or qualitative characteristics than quantitative characteristics. It is easy to measure properties like weight, height etc. by some standard.
Nominal Scales:
Nominal scales are the easiest to use but provide the lowest measurement level. Unlike other techniques, they don't express any relationships or values between variables. Researchers use them to determine frequency counts, such as the number of men and women who prefer a specific product color or size.
Nominal scales are the easiest to use but provide the lowest measurement level. Unlike other techniques, they don't express any relationships or values between variables. Researchers use them to determine frequency counts, such as the number of men and women who prefer a specific product color or size.
Interval Scales:
Interval scales are commonly used in commercial marketing research. They indicate the order as well as the differences between variables. A distinctive feature of this method is that there is no absolute zero point. Examples include opinion scales and attitude scales.
Interval scales are commonly used in commercial marketing research. They indicate the order as well as the differences between variables. A distinctive feature of this method is that there is no absolute zero point. Examples include opinion scales and attitude scales.
Ordinal Scales:
This scaling technique helps measure non-numeric concepts, such as comfort, satisfaction, overall experience and more. A good example would be: Dissatisfied, Satisfied, Somehow Satisfied or Extremely Satisfied. Respondents will tick the box that best reflects their satisfaction level.
This scaling technique helps measure non-numeric concepts, such as comfort, satisfaction, overall experience and more. A good example would be: Dissatisfied, Satisfied, Somehow Satisfied or Extremely Satisfied. Respondents will tick the box that best reflects their satisfaction level.
Ratio Scales:
Ratio scales are the most comprehensive of all scaling techniques because they measure the exact value of responses. Additionally, they have a fixed origin or zero points. Respondents can provide compelling information, such as their annual household income, the amount spent on their last purchase, the time spent watching TV on a daily basis and more. From here, researchers can apply various statistics like mode, frequency, range, standard deviation and variance.
Sources of Error in measurement:
Test of Sound Measurement:
Scaling: Scaling is the assignment of objects to numbers or semantics according to a rule. In scaling, the objects are text statements, usually statements of attitude, opinion, or feeling.
A Likert Scale is a type of rating scale used to measure attitudes or opinions. With this scale, respondents are asked to rate items on a level of agreement. For example:
Census Survey Method:
- A statistical investigation in which the data are collected for each and every element/unit of the population, it is termed as Census Method.
- It is also known as ‘Complete Enumeration’ or ‘100% Enumeration or Complete survey.
- Useful in case Intensive Study is required or the area is limited.
- For example:
- Demographic data on birth and death rates, literacy; workforce, life expectancy, size and composition of a population
- Census of India conducted after every 10 years.
Sampling Survey Method:
- The sampling method is the one in which only some of the representative items of the population are selected and data are collected from these.
- Instead of collecting information for and from all the units of population, we select a sample i.e. only a few items of the population.
- Conclusions derived from the small sample are generalized for the whole population.
Ratio scales are the most comprehensive of all scaling techniques because they measure the exact value of responses. Additionally, they have a fixed origin or zero points. Respondents can provide compelling information, such as their annual household income, the amount spent on their last purchase, the time spent watching TV on a daily basis and more. From here, researchers can apply various statistics like mode, frequency, range, standard deviation and variance.
Sources of Error in measurement:
(1) Respondent
(2) Situation
(3) Measurer
(4) Instrument
Test of Sound Measurement:
(1) Test of Validity
(2) Test of Reliability
(3) Test of Practicality
Scaling: Scaling is the assignment of objects to numbers or semantics according to a rule. In scaling, the objects are text statements, usually statements of attitude, opinion, or feeling.
A Likert Scale is a type of rating scale used to measure attitudes or opinions. With this scale, respondents are asked to rate items on a level of agreement. For example:
· Strongly agree
· Agree
· Neutral
· Disagree
· Strongly disagree
Census Survey Method:
Census Survey Method:
- A statistical investigation in which the data are collected for each and every element/unit of the population, it is termed as Census Method.
- It is also known as ‘Complete Enumeration’ or ‘100% Enumeration or Complete survey.
- Useful in case Intensive Study is required or the area is limited.
- For example:
- Demographic data on birth and death rates, literacy; workforce, life expectancy, size and composition of a population
- Census of India conducted after every 10 years.
Sampling Survey Method:
- The sampling method is the one in which only some of the representative items of the population are selected and data are collected from these.
- Instead of collecting information for and from all the units of population, we select a sample i.e. only a few items of the population.
- Conclusions derived from the small sample are generalized for the whole population.
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 methods can be divided into two categories: secondary methods of data collection and primary methods of data collection.
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 methods can be divided into two categories: secondary methods of data collection and primary methods of data collection.
Primary Data Collection Methods:
Primary data collection methods can be divided into two groups: quantitative and qualitative.
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.
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.
Data Collection through Questionnaire
The method of collecting data by mailing the questionnaires to respondents is most extensively employed in various economic and business surveys. The merits claimed on behalf of this method are as follows:
Data Collection through Questionnaire
This method of data collection is quite popular, particularly in case of big enquiries. It is being adopted by private individuals, research workers, private and public organisations and even by governments. In this method a questionnaire is sent (usually by post) to the persons concerned with a request to answer the questions and return the questionnaire. A questionnaire consists of a number of questions printed or typed in a definite order on a form or set of forms. The questionnaire is mailed to respondents who are expected to read and understand the questions and write down the reply in the space meant for the purpose in the questionnaire itself. The respondents have to answer the questions on their own.
The method of collecting data by mailing the questionnaires to respondents is most extensively employed in various economic and business surveys. The merits claimed on behalf of this method are as follows:
The method of collecting data by mailing the questionnaires to respondents is most extensively employed in various economic and business surveys. The merits claimed on behalf of this method are as follows:
1. There is low cost even when the universe is large and is widely spread geographically.
2. It is free from the bias of the interviewer; answers are in respondents’ own words.
3. Respondents have adequate time to give well thought out answers.
4. Respondents, who are not easily approachable, can also be reached conveniently.
5. Large samples can be made use of and thus the results can be made more dependable and reliable.
Schedule method of Data collection in Research Methodology:
This schedule method of data collection is very much like the collection of data through questionnaire, with little difference which lies in the fact that schedules (proforma containing a set of questions) are being filled in by the enumerators who are specially appointed for the purpose. These enumerators along with schedules, go to respondents, put to them the questions from the proforma in the order the questions are listed and record the replies in the space meant for the same in the proforma. In certain situations, schedules may be handed over to respondents and enumerators may help them in recording their answers to various questions in the said schedules. Enumerators explain the aims and objects of the investigation and also remove the difficulties which any respondent may feel in understanding the implications of a particular question or the definition or concept of difficult terms.
This schedule method of data collection is very much like the collection of data through questionnaire, with little difference which lies in the fact that schedules (proforma containing a set of questions) are being filled in by the enumerators who are specially appointed for the purpose. These enumerators along with schedules, go to respondents, put to them the questions from the proforma in the order the questions are listed and record the replies in the space meant for the same in the proforma. In certain situations, schedules may be handed over to respondents and enumerators may help them in recording their answers to various questions in the said schedules. Enumerators explain the aims and objects of the investigation and also remove the difficulties which any respondent may feel in understanding the implications of a particular question or the definition or concept of difficult terms.
This method requires the selection of enumerators for filling up schedules or assisting respondents to fill up schedules and as such enumerators should be very carefully selected. The enumerators should be trained to perform their job well and the nature and scope of the investigation should be explained to them thoroughly so that they may well understand the implications of different questions put in the schedule. Enumerators should be intelligent and must possess the capacity of cross examination in order to find out the truth. Above all, they should be honest, sincere, hardworking and should have patience and perseverance.
This method of data collection is very useful in extensive enquiries and can lead to fairly reliable results. It is, however, very expensive and is usually adopted in investigations conducted by governmental agencies or by some big organisations. Population census all over the world is conducted through this method.
What is the difference between questionnaire and schedule ?
12. Along with schedules, observation method can also be used but such a thing is not possible while collecting data through questionnaires.
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Unit IV:
Processing Operations in Research Methodology
2. Coding: Coding refers to the process of assigning numerals or other symbols to answers so that responses can be put into a limited number of categories or classes. Such classes should be appropriate to the research problem under consideration. They must also possess the characteristic of exhaustiveness (i.e., there must be a class for every data item) and also that of mutual exclusively which means that a specific answer can be placed in one and only one cell in a given category set.
Classification according to attributes: As stated above, data are classified on the basis of common characteristics which can either be descriptive (such as literacy, sex, honesty, etc.) or numerical (such as weight, height, income, etc.). Descriptive characteristics refer to qualitative phenomenon which cannot be measured quantitatively; only their presence or absence in an individual item can be noticed.
What is the difference between questionnaire and schedule ?
Both questionnaire and schedule are popularly used methods of collecting data in research surveys. There is much resemblance in the nature of these two methods and this fact has made many people to remark that from a practical point of view, the two methods can be taken to be the same. But from the technical point of view there is difference between the two. The important points of difference are as under:
1. The questionnaire is generally sent through mail to informants to be answered as specified in a covering letter, but otherwise without further assistance from the sender. The schedule is generally filled out by the research worker or the enumerator, who can interpret questions when necessary.
2. To collect data through questionnaire is relatively cheap and economical since we have to spend money only in preparing the questionnaire and in mailing the same to respondents. Here no field staff required. To collect data through schedules is relatively more expensive since considerable amount of money has to be spent in appointing enumerators and in importing training to them. Money is also spent in preparing schedules.
3. Non-response is usually high in case of questionnaire as many people do not respond and many return the questionnaire without answering all questions. Bias due to non-response often remains indeterminate. As against this, non-response is generally very low in case of schedules because these are filled by enumerators who are able to get answers to all questions. But there remains the danger of interviewer bias and cheating.
4. In case of questionnaire, it is not always clear as to who replies, but in case of schedule the identity of respondent is known.
5. The questionnaire method is likely to be very slow since many respondents do not return the questionnaire in time despite several reminders, but in case of schedules the information is collected well in time as they are filled in by enumerators.
6. Personal contact is generally not possible in case of the questionnaire method as questionnaires are sent to respondents by post who also in turn return the same by post. But in case of schedules direct personal contact is established with respondents.
7. Questionnaire method can be used only when respondents are literate and cooperative, but in case of schedules the information can be gathered even when the respondents happen to be illiterate.
8. Wider and more representative distribution of sample is possible under the questionnaire method, but in respect of schedules there usually remains the difficulty in sending enumerators over a relatively wider area.
9. Risk of collecting incomplete and wrong information is relatively more under the questionnaire method, particularly when people are unable to understand questions properly. But in case of schedules, the information collected is generally complete and accurate as enumerators can remove the difficulties, if any, faced by respondents in correctly understanding the questions. As a result, the information collected through schedules is relatively more accurate than that obtained through questionnaires.
10. The success of questionnaire method lies more on the quality of the questionnaire itself, but in the case of schedules much depends upon the honesty and competence of enumerators.
11. In order to attract the attention of respondents, the physical appearance of questionnaire must be quite attractive, but this may not be so in case of schedules as they are to be filled in by enumerators and not by respondents.
12. Along with schedules, observation method can also be used but such a thing is not possible while collecting data through questionnaires.
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Unit IV:
Data processing is the conversion of data into usable and desired form. This conversion or “processing” is carried out using a predefined sequence of operations either manually or automatically. Most of the processing is done by using computers and thus done automatically. The output or “processed” data can be obtained in different forms like image, graph, table, vector file, audio, charts or any other desired format depending on the software or method of data processing used. When done itself it is referred to as automatic data processing.
Processing Operations in Research Methodology
With this brief introduction concerning the concepts of processing and analysis, we can now proceed with the explanation of all the processing operations.
1. Editing: Editing of data is a process of examining the collected raw data (specially in surveys) to detect errors and omissions and to correct these when possible. As a matter of fact, editing involves a careful scrutiny of the completed questionnaires and/or schedules. Editing is done to assure that the data are accurate, consistent with other facts gathered, uniformly entered, as completed as possible and have been well arranged to facilitate coding and tabulation.
2. Coding: Coding refers to the process of assigning numerals or other symbols to answers so that responses can be put into a limited number of categories or classes. Such classes should be appropriate to the research problem under consideration. They must also possess the characteristic of exhaustiveness (i.e., there must be a class for every data item) and also that of mutual exclusively which means that a specific answer can be placed in one and only one cell in a given category set.
3. Classification: Most research studies result in a large volume of raw data which must be reduced into homogeneous groups if we are to get meaningful relationships. This fact necessitates classification of data which happens to be the process of arranging data in groups or classes on the basis of common characteristics. Data having a common characteristic are placed in one class and in this way the entire data get divided into a number of groups or classes. Classification can be one of the following two types, depending upon the nature of the phenomenon involved:
Classification according to attributes: As stated above, data are classified on the basis of common characteristics which can either be descriptive (such as literacy, sex, honesty, etc.) or numerical (such as weight, height, income, etc.). Descriptive characteristics refer to qualitative phenomenon which cannot be measured quantitatively; only their presence or absence in an individual item can be noticed.
Classification according to class-intervals: Unlike descriptive characteristics, the numerical characteristics refer to quantitative phenomenon which can be measured through some statistical units. Data relating to income, production, age, weight, etc. come under this category. Such data are known as statistics of variables and are classified on the basis of class intervals.
4. Tabulation: When a mass of data has been assembled, it becomes necessary for the researcher to arrange the same in some kind of concise and logical order. This procedure is referred to as tabulation. Thus, tabulation is the process of summarising raw data and displaying the same in compact form (i.e., in the form of statistical tables) for further analysis. In a broader sense, tabulation is an orderly arrangement of data in columns and rows. Tabulation is essential because of the following reasons.
a) It conserves space and reduces explanatory and descriptive statement to a minimum.
b) It facilitates the process of comparison.
c) It facilitates the summation of items and the detection of errors and omissions.
d) It provides a basis for various statistical computations.
Element / types of analysis: Data analysis we mean the computation of certain indices or measures along with searching for patterns of relationship that exist among the data groups. Analysis, particularly in case of survey or experimental data, involves estimating the values of unknown parameters of the population and testing of hypotheses for drawing inferences. Analysis may, therefore, be categorised as descriptive analysis and inferential analysis (Inferential analysis is often known as statistical analysis). “Descriptive analysis is largely the study of distributions of one variable.
Causal analysis is concerned with the study of how one or more variables affect changes in another variable. It is thus a study of functional relationships existing between two or more variables. This analysis can be termed as regression analysis.
Types of analysis in Research Methodology
· Multiple regression analysis: This analysis is adopted when the researcher has one dependent variable which is presumed to be a function of two or more independent variables. The objective of this analysis is to make a prediction about the dependent variable based on its covariance with all the concerned independent variables.
· Multiple regression analysis: This analysis is adopted when the researcher has one dependent variable which is presumed to be a function of two or more independent variables. The objective of this analysis is to make a prediction about the dependent variable based on its covariance with all the concerned independent variables.
· Multiple discriminant analysis: This analysis is appropriate when the researcher has a single dependent variable that cannot be measured, but can be classified into two or more groups on the basis of some attribute. The object of this analysis happens to be to predict an entity’s possibility of belonging to a particular group based on several predictor variables.
· Multivariate analysis of variance (or multi-ANOVA): This analysis is an extension of twoway ANOVA, wherein the ratio of among group variance to within group variance is worked out on a set of variables.
· Canonical analysis: This analysis can be used in case of both measurable and non-measurable variables for the purpose of simultaneously predicting a set of dependent variables from their joint covariance with a set of independent variables.
· Inferential analysis: is concerned with the various tests of significance for testing hypotheses in order to determine with what validity data can be said to indicate some conclusion or conclusions. It is also concerned with the estimation of population values. It is mainly on the basis of inferential analysis that the task of interpretation (i.e., the task of drawing inferences and conclusions) is performed.
Q 5. What do you mean by Research Report?
Discuss its types in brief.
A technical report is
used whenever a full written report of the study is required whether for
recordkeeping or for public dissemination.
A popular report is used if the research results have policy
implications. We give below a few details about the said two types of reports:
Technical
Report
The order presented above only gives a
general idea of the nature of a technical report; the order of presentation may
not necessarily be the same in all the technical reports. This, in other words,
means that the presentation may vary in different reports; even the different sections
outlined above will not always be the same, nor will all these sections appear
in any particular report.
It should, however, be remembered that even in a technical report, simple
presentation and ready availability of the findings remain an important
consideration and as such the liberal use of charts and diagrams is considered
desirable.
Parametric Test
T-test Z-test F-test
T-test:-
(a) T-test is a Small Sample test,
(b) It was developed by William Gosset in 1908.
(c) It is also called students t-test (Pen Test)
Deviation from population parameter
t = ----------------------------------------------------------
Standard error of 0th Sample statistics
Uses of T-test /Apblication:
(i) Size of Sample is small (n<30)
Q 5. What do you mean by Research Report?
Discuss its types in brief.
Ans:
Research reports vary greatly in length
and type. In each individual case, both the length and the form are largely
dictated by the problems at hand. For instance, business firms prefer reports
in the letter form, just one or two pages in length. Banks, insurance
organisations and financial institutions are generally fond of the short
balance-sheet type of tabulation for their annual reports to their customers
and shareholders. Mathematicians prefer to write the results of their
investigations in the form of algebraic notations. Chemists report their
results in symbols and formulae. Students of literature usually write long
reports presenting the critical analysis of some writer or period or the like
with a liberal use of quotations from the works of the author under discussion.
In the field of education and psychology, the favourite form is the report on
the results of experimentation accompanied by the detailed statistical
tabulations. Clinical psychologists and social pathologists frequently find it
necessary to make use of the case-history form.
A technical report is used whenever a full written report of the study is required whether for recordkeeping or for public dissemination.
A popular report is used if the research results have policy
implications. We give below a few details about the said two types of reports:
Technical
Report
In the technical report the main
emphasis is on
i.
the methods employed,
ii. assumptions made in
the course of the study,
iii. the detailed
presentation of the findings including their limitations and supporting data.
A general outline of a technical report
can be as follows:
1.
Summary of results: A brief review of the
main findings just in two or three pages.
2.
Nature of the study: Description of the
general objectives of study, formulation of the problem in
operational terms, the
working hypothesis, the type of analysis and data required, etc.
3.
Methods employed: Specific methods used
in the study and their limitations. For instance, in
sampling studies we
should give details of sample design viz., sample size, sample selection, etc.
4.
Data: Discussion of data collected, their
sources, characteristics and limitations. If secondary data
are used, their
suitability to the problem at hand be fully assessed. In case of a survey, the
manner
in which data were
collected should be fully described.
5.
Analysis of data and presentation of
findings: The analysis of data and presentation of the findings
of the study with
supporting data in the form of tables and charts be fully narrated. This, in
fact,
happens to be the main
body of the report usually extending over several chapters.
6.
Conclusions: A detailed summary of
the findings and the policy implications drawn from the
results be explained.
7.
Bibliography: Bibliography of
various sources consulted be prepared and attached.
8.
Technical appendices: Appendices be given
for all technical matters relating to questionnaire,
mathematical derivations,
elaboration on particular technique of analysis and the like ones.
9.
Index: Index must be prepared and be given
invariably in the report at the end.
The order presented above only gives a
general idea of the nature of a technical report; the order of presentation may
not necessarily be the same in all the technical reports. This, in other words,
means that the presentation may vary in different reports; even the different sections
outlined above will not always be the same, nor will all these sections appear
in any particular report.
It should, however, be remembered that even in a technical report, simple presentation and ready availability of the findings remain an important consideration and as such the liberal use of charts and diagrams is considered desirable.
It should, however, be remembered that even in a technical report, simple presentation and ready availability of the findings remain an important consideration and as such the liberal use of charts and diagrams is considered desirable.
Popular
Report
The popular report is one which gives
emphasis on simplicity and attractiveness. The simplification should be sought
through clear writing, minimization of technical, particularly mathematical,
details and liberal use of charts and diagrams. Attractive layout along with
large print, many subheadings, even an occasional cartoon now and then is
another characteristic feature of the popular report. Besides, in such a report
emphasis is given on practical aspects and policy implications. We give below a
general outline of a popular report.
1.
The findings and their implications: Emphasis in the
report is given on the findings of most practical interest and on the
implications of these findings.
2.
Recommendations for action: Recommendations for
action on the basis of the findings of the study is made in this section of the
report.
3.
Objective of the study: A general review of
how the problem arise is presented along with the specific objectives of the
project under study.
4.
Methods employed: A brief and
non-technical description of the methods and techniques used, including a short
review of the data on which the study is based, is given in this part of the
report.
5.
Results: This section constitutes the main body
of the report wherein the results of the study are presented in clear and
non-technical terms with liberal use of all sorts of illustrations such as
charts, diagrams and the like ones.
6.
Technical appendices: More detailed
information on methods used, forms, etc. is presented in the form of
appendices. But the appendices are often not detailed if the report is entirely
meant for general public.
There can be several variations of the
form in which a popular report can be prepared. The only important thing about
such a report is that it gives emphasis on simplicity and policy implications
from the operational point of view, avoiding the technical details of all sorts
to the extent possible.
Parametric Test
T-test Z-test F-test
T-test:-
(a) T-test is a Small Sample test,
(b) It was developed by William Gosset in 1908.
(c) It is also called students t-test (Pen Test)
Deviation from population parameter
t = ----------------------------------------------------------
Standard error of 0th Sample statistics
Uses of T-test /Apblication:
(i) Size of Sample is small (n<30)
(ii) Degese of freedom is v=n-1
(iii) T- test as used for test of significance of regression coefficient in reguession modal.
