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Research Methodology
 

Research Methodology

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A useful presentation for all those interested in Research Methodology

A useful presentation for all those interested in Research Methodology

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    Research Methodology Research Methodology Presentation Transcript

    • Shashikant S Kulkarni
      • Research is Search for Knowledge
      • It is an Art of Scientific Investigation
      • According to Redman and Mory, Research is a “ Systematized effort to gain new knowledge ”
      • Research is an original addition to the available knowledge, which contributes to it’s further advancement
      • In sum, Research is the search for knowledge, using objective and systematic methods to find solution to a problem
      • To gain familiarity with new insights into a phenomenon
      • To accurately portray the characteristics of a particular individual, group, or a situation
      • To analyze the frequency with which something occurs
      • To examine the Hypothesis of a casual relationship between two variables
      • Research Method s are the methods that the researcher adopts for conducting the research Studies
      • Research Methodology is the way in which research problems are solved systematically.
      • It is the Science of studying how research is conducted Scientifically
      • Quantitative Approach
      • (Uses experimental, inferential and simulation approaches to research)
      • Qualitative Approach
      • (Uses techniques like in-depth interview, focus group interviews)
      • Descriptive
      • Analytical
      • Applied
      • Fundamental
      • Quantitative
      • Qualitative
      • Conceptual
      • Empirical
      • Other Types
      • In Descriptive Research , the Researcher has to only report what is happening or what has happened.
      • In Analytical Research , the Researcher has to use the already available facts or information, and analyse them to make a critical evaluation of the subject
      • An attempt to find solution to an immediate problem encountered by a firm, an Industry, a business organization, or the Society is known as Applied Research
      • Gathering knowledge for knowledge’s sake is ‘Pure’ or ‘Basic’ or ‘Fundamental’ Research
      • Quantitative Research involves the measurement of quantity or amount. (ex: Economic & Statistical methods)
      • Qualitative Research is concerned with the aspects related to or involving quality or Kind.(ex: Motivational Research involving behavioural Sciences)
      • The Research related to some abstract idea or theory is known as Conceptual Research. (Ex: Philosophers and Thinkers using this to developing new concepts)
      • Empirical Research relies on the observation or experience with hardly any regard for theory and system.
      • One-time or Longitudinal Research (On the basis time)
      • Laboratory Research or Field-setting or Simulational Research (On the basis of environment)
      • Historical Research
      • Helps Researcher to develop disciplined thinking
      • The Researcher will confidently evaluate and utilize the Research Findings
      • Helps the Research consumer to evaluate Research and make rational decisions
      • The Researcher will be equipped with knowledge of different tools to conduct scientific Research
      • Desire for accuracy of observation & precision of statement
      • An alert mind.
      • Must practice “The art of enduring intellectual hardships”
      • Making statements cautiously
      • According to Hudson Maxim “All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention”
      • 1. Formulating the Research Problem
      • 2. Extensive Literature Survey
      • 3. Developing Hypothesis
      • 4. Preparing the Research Design
      • 5. Determining Sample Design
      • 6. Collecting Data
      • 7. Execution of the Project
      • 8. Analysis of the Data
      • 9. Hypothesis Testing
      • 10. Generalization and Interpretation
      • 11. Preparation of the Report or Presentation of the Results
      • Research Problem is an unanswered question that a researcher might encounter in the context of either a theoretical or practical situation
      • There should be an individual or a group who have some difficulty or problem
      • There should be some objective to be pursued (A person or an organization who wants nothing cannot have a problem)
      • There should be more than one alternative means available to the Researcher.
      • There should be some doubt in the mind of the Researcher about the choice of alternative means
      • X- an individual or an organization (to whom the problem is attributed)
      • Y-the environment where X is situated
      • Z-the uncontrolled variables which control Y
      • A1 & A2 two courses of action
      • B1 & B2 two possible outcomes of the said course (One outcome should be what Researcher Wants)
      • It highlights decisions which include
      • The Name of the Study
      • The Purpose of the Study
      • The Location where the study would be conducted
      • The Nature of Data Required
      • From where the required Data can be collected
      • What time period the study would cover
      • The Type of Sample Design
      • The Techniques of Data Collection
      • The Methods of Data Analysis
      • A magnitude that varies is known as a variable (ex: income, height, weight.. )
      • When changes in one variable depend upon the changes in other variable (s), it is known as dependent variable (ex: If Demand depends on Price, then Demand is a dependent variable, price is independent variable )
      • The independent variables which are not directly related to the purpose of the study but affect the dependent variable are known as Extraneous Variables. ( ex: Relationship between children’s school performance ( dependent variable ) and their Parent’s Income ( Independent Variable ). In this case Intelligence may also influence the school performance ( Extraneous Variable )
      • Exploratory Research Design
      • Descriptive and Diagnostic Research Design
      • Hypothesis-testing Research Design
      • To formulate a Research Problem for an in-depth or more precise investigation
      • To discover new ideas and insights
      • Three methods considered for such Research Design
      • a) a Survey of related Literature
      • b) experience survey
      • c) analysis of insight-stimulating instances
      • Descriptive Research Design is Concerned with describing the characteristics of a particular individual or a group.
      • Diagnostic Research Design is determines the frequency with which a variable occurs or it’s relationship with other.
      • Both Descriptive & Diagnostic Research design have common requirements
      • The Researcher tests the Hypothesis of casual relationship between two or more variables
      • These studies require unbiased attitude of the Researcher
      • It facilitates smooth conduct of the various stages of Research.
      • Makes Research Efficient to yield maximum information with minimum effort, time, expenditure
      • Plays a crucial role in attaining the reliability of the results obtained.
      • Flexible, Suitable, Efficient and Economical
      • Minimizes bias and Maximizes Reliability
      • No Experimental Error
      • Yields Maximum Information
      • The method of exploring and analyzing the life or functioning of a social or economic unit, such as a person, a family, a community, an institution, a firm or an industry is called Case Study Research
      • Through this research the Researcher understands the complex behaviour and situations in specific detail
      • It is a Predictive statement
      • Must be tested by scientific methods
      • A hypothesis is a proposed explanation for an observable phenomenon
      • Example:
      • “ Students who take tuitions perform better than the others who do not receive tuitions”
      • Precise and clear
      • Capable of being put to test
      • Must be stated in simple language
      • Researcher must be able to test it within a stipulated period
      • A Hypothesis should explain what it actually wants to explain.
      • A Hypothesis must be derived from known facts
      • The statistical hypothesis that states that there are no differences between observed and expected data.
      • For example, imagine flipping a coin three times
      • The null Hypothesis is expresses as H 0
      • The alternative hypothesis is the hypothesis used in hypothesis testing that is contrary to the null hypothesis. It is usually taken to be that the observations are the result of a real effect (with some amount of chance variation superposed).
      • An example might be where water quality in a stream has been observed over many years and a test is made of the null hypothesis that there is no change in quality between the first and second halves of the data against the alternative hypothesis that the quality is poorer in the second half of the record.
      • Very important concept
      • If for example, the significance level is taken 5 percent, then it means that 5 % level of significance implies that the researcher is willing to take a risk of 5 % of rejecting the null hypothesis, when (H0) is actually true.
      • Type I Error
      • Researcher rejects H0 when it is true
      • ( Rejection of the Hypothesis when it must have been accepted)
      • Type II Error
      • Researcher accepts H0 when it is not true
      • (Acceptance of the Hypothesis which must have been rejected)
      • The two-tailed test is a statistical test used in inference, in which a given statistical hypothesis , H 0 (null hypothesis)will be rejected when the value of the statistic is either sufficiently small or sufficiently large.
      • Making a formal Statement
      • Selecting a Significance Level
      • Deciding the distribution to Use
      • Selection of a Random Sample & Computing an Appropriate Value
      • Calculation of the Probability
      • Comparing the Probability
      • To begin with a formal Statement of Null Hypothesis (H0) and Alternative Hypothesis (Ha) is
      • Usually 5% or 1 % Significance level is chosen for the Hypothesis Testing
      • The divergence of the Result from expectation (Probability) when Null Hypothesis is True is calculated
      • Probability is compared with Significance Level later on
      • Specify the Level of Significance
      State H0 as Well as Ha Decide the Correct Sampling Distribution Sample a random Sample and workout an appropriate Value Calculate the Probability that Sample Result would diverge as widely as it has from expectations, if H0 were true
      • Sample is a certain portion of the population
      • A Researcher adopts a Technique to select the items of the Sample from the Population and that is called as Sampling Design.
      • Sample design must be done before Data Collection.
      • Type of Interview
      • Sampling Unit
      • Source List
      • Size of Sample
      • Parameters of Interest
      • Budgetary Constraint
      • Sampling Procedure
      • Define the Universe to be studied
      • ( Finite Universe : Population of a City, No. of Workers in a factory)
      • ( Infinite Universe : Stars in the Sky)
      • Sampling Unit :
      • ( Geographical Area : State, District, Village)
      • ( Social Unit : Family, School, Religious Community)
      • Source List is nothing but Sample Frame from which the Sample is to be selected.
      • (For example, in an opinion poll , possible sampling frames include:
      • Electoral register
      • Telephone directory)
      • No. of Units to be chosen from the Universe to form a Sample is Size of the Sample
      • Two Costs control the Selection of a Sampling Procedure
      • Cost of Data Collection
      • Cost of drawing incorrect inference from the selected Data
      • Small Sampling Error
      • Sample Design must fit into the Budget
      • Controllable Bias
      • Results of the Sample Study must be applicable to the Universe, with confidence
      • Non-probability Sampling
      • No probability sampling techniques cannot be used to infer from the sample to the general population.
      • Examples :
      • To sample friends, co-workers, or shoppers at a single mall, are all examples of convenience sampling. The first respondent refers a friend. The friend also refers a friend, etc
      • In quota sampling , the population is first segmented into mutually exclusive sub-groups.Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60.
      • A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined.
      • Example: We want to estimate the total income of adults living in a given street. We visit each household in that street, identify all adults living there, and randomly select one adult from each household.
      • Primary Data
      • Primary Data is a term for data collected on source which has not been subjected to processing or any other manipulation.
      • When Primary Data is Processed it becomes Information
      • Primary Data is the data collected for the first time
      • Secondary Data is the Data that has already been collected and used earlier by somebody or some agency.
      • Example : Statistics about the Population of the country collected for the first time by Govt. of India is Primary Data, but when a researcher uses it for his study the same data becomes Secondary Data
      • Published Sources
      • Examples : Official Publications of State and Central Governments, Research Institutions, Committees and Commissions
      • Unpublished Sources
      • Examples: Records maintained by different offices, Scholars in the Universities
      • Purpose and Scope of Enquiry
      • Availability of Time
      • Availability of Resources
      • The degree of accuracy desired
      • Statistical Tools to be used
      • Method of Data Collection
      • For example if the researcher interested in knowing the nature of price change over a period of time, it would be necessary to to collect data of commodity prices(wholesale or retail prices)
      • The purpose and scope of data collection should be clearly set out at the very beginning
      • Direct Personal Interview
      • Indirect oral interviews
      • Information from correspondents
      • Mailed Questionnaire methods
      • Schedule sent through interviewers
      • Under Indirect Oral Interview method of data collection, the investigator contacts third parties generally called “witnesses” who are capable of supplying necessary information.
      • Schedule is the name usually applied to a set of questions which are asked in a face to face situation with another person.
      • Primary Data is more accurate and authentic.
      • Time, Money and labour is more involved in Primary data Collection
      • But in Statistical enquiries secondary data is used.
      • Primary Data is are collected only if there exists no secondary data.
      • According to Bogardus, a questionnaire is a list of questions sent to a number of persons for their answers and which obtains standardised results that can be tabulated and treated statistically
      • Example1 of Sampling : A housewife testing small quantity of rice to see whether it has been Well cooked
      • Example2 of Sampling : A pathologist testing blood sample of the patient.
      • Number of questions as small as possible.
      • Questions should be clear
      • Questions should be arranged in a logical order
      • Questions should be simple to understand
      • Questions should be easily answerable
      • No personal questions
      • Shut Questions :
      • Simple Alternate Questions ..Yes or No
      • Multiple Choice questions …a)..b)...c)…d)…
      • The questionnaire must be pre-tested on a small scale before using it for the enquiry
      • A covering letter from the organizers of the enquiry should be enclosed along with the questionnaire
      • Absolute Experiment : Example : The impact of fertilizer on the yield of a crop
      • Comparative Experiments : Example: Impact of one fertilizer as compared to the impact of some other fertilizer
      • The Principle of Replication
      • Experiment should be repeated more than once to increase the statistical accuracy
      • The Principle of Randomization
      • The Principle of Local Control
      • It is accurate watching and noting of phenomena as they occur with regard to the cause and effect or mutual relations.
      • Example1 : Watching bonded labour’s life
      • Example2 : Treatment of widows at home
    •