MB0050 Both

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Master of Business Administration

Name Jyotsana DewanganRoll Number 511038208

Course MBA 3 rd Semester Subject Research Methodology

Subject code MB0050Center code 3011

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Assignment Set-1

Question 1: Why should a manger know about research when the job entailsmanaging people, products, events, environments, and the like?

Answer:

Research simply means a search for facts – answers to questions and solutions to problems. Itis a purposive investigation. It is an organized inquiry. It seeks to find explanations tounexplained phenomenon to clarify the doubtful facts and to correct the misconceived facts.Research is the organized and systematic inquiry or investigation which provides informationfor solving a problem or finding answers to a complex issue.

Research in business:

Often, organization members want to know everything about their products, services,programs, etc. Your research plans depend on what information you need to collect in order to

make major decisions about a product, service, program, etc. Research provides the neededinformation that guides managers to make informed decisions to successfully deal withproblems.

The more focused you are about your resources, products, events and environments what youwant to gain by your research, the more effective and efficient you can be in your research, theshorter the time it will take you and ultimately the less it will cost you.

Manager’s role in research programs of a company:

Managing people is only a fraction of a manager's responsibility - they have to manage theoperations of the department, and often have responsibilities towards the profitability of theorganization. Knowledge of research can be very helpful for a good manager.

Question 2:a. How do you evolve research design for exploratory research? Briefly analyze.b. Briefly explain Independent, dependent and extraneous variables in a research

design.

Answer:

a. Research design for exploratory research:

Research simply means a search for facts – answers to questions and solutions toproblems. It is a purposive investigation. It is an organized inquiry. It seeks to findexplanations to unexplained phenomenon to clarify the doubtful facts and to correct themisconceived facts. Although any typology of research is inevitably arbitrary, Researchmay be classified crudely according to its major intent or the methods.

It is also known as formulating research. It is preliminary study of an unfamiliar problemabout which the researcher has little or no knowledge. It is ill-structured and much lessfocused on pre-determined objectives. It usually takes the form of a pilot study. Thepurpose of this research may be to generate new ideas, or to increase the researcher’sfamiliarity with the problem or to make a precise formulation of the problem or to gatherinformation for clarifying concepts or to determine whether it is feasible to attempt the

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study. Katz conceptualizes two levels of exploratory studies. “At the first level is thediscovery of the significant variable in the situations; at the second, the discovery of relationships between variables.”

b. Independent and dependent and extraneous variables in a research design:

The research designer understandably cannot hold all his decisions in his head. Even if hecould, he would have difficulty in understanding how these are inter-related. Therefore, herecords his decisions on paper or record disc by using relevant symbols or concepts. Such asymbolic construction may be called the research design or model. A research design is alogical and systematic plan prepared for directing a research study.

Dependent and Independent variables: A magnitude that varies is known as a variable. The concept may assume differentquantitative values, like height, weight, income, etc. Qualitative variables are notquantifiable in the strictest sense of objectivity. However, the qualitative phenomena mayalso be quantified in terms of the presence or absence of the attribute considered.Phenomena that assume different values quantitatively even in decimal points are known

as „continuous variables . But, all variables need not be continuous. Values that can be expressed only in integer values are called „non-continuous variables . In statistical term, they are also known as „discrete variable . For example, age is a continuous variable; whereas the number of children is a non-continuous variable. When changes in onevariable depends upon the changes in one or more other variables, it is known as adependent or endogenous variable, and the variables that cause the changes in thedependent variable are known as the independent or explanatory or exogenous variables.For example, if demand depends upon price, then demand is a dependent variable, whileprice is the independent variable.

And if, more variables determine demand, like income and prices of substitute commodity,then demand also depends upon them in addition to the own price. Then, demand is adependent variable which is determined by the independent variables like own price,income and price of substitute.

Extraneous variable:

The independent variables which are not directly related to the purpose of the study butaffect the dependent variable are known as extraneous variables. For instance, assumethat a researcher wants to test the hypothesis that there is relationship between children’sschool performance and their self-concepts, in which case the latter is an independentvariable and the former, the dependent variable. In this context, intelligence may alsoinfluence the school performance. However, since it is not directly related to the purpose of the study undertaken by the researcher, it would be known as an extraneous variable. Theinfluence caused by the extraneous variable on the dependent variable is technically calledas an „experimental error . Therefore, a research study should always be framed in such a manner that the dependent variable completely influences the change in the independentvariable and any other extraneous variable or variables.

Question 3:a. Differentiate between ‘Census survey’ and ‘ Sample Survey’b. Analyse multi-stage and sequential sampling.

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Answer:

a. Difference between Census survey and Sample Survey

Census Survey Sample SurveyA census measures absolutely everyone inthe whole country. This obviously meansthat a census survey is a much biggerexercise in nature and procedures

A part of the population is known assample

Census survey also is a very timeconsuming exercise as information needsto be collected from each and everyindividual from the population.

On the other hand, sample survey iseasier as a representative sample is takenfrom the population and the resultsobtained are extrapolated to fit the entirepopulation.

There are times and requirements wheregovernments have to indulge in censussurvey even if it is time consuming andvery expensive as it needs to formulatepolicies and welfare programs for thepopulation. For example, when agovernment has to count heads of thepopulation

Sample surveys cannot count the numberof people in the country but whengovernment is planning on a welfareprogram for cancer patients, it canconduct a sample survey of some of thecancer patients and then extrapolate theresults on the section of the populationthat is undergoing treatment for cancer.

Census survey is more accurate. there is margin for error in sample survey

b.Analyse multi-stage and sequential sampling:

Multi-stage sampling:

In multi-stage sampling method, sampling is carried out in two or more stages. The populationis regarded as being composed of a number of second stage units and so forth. That is, at eachstage, a sampling unit is a cluster of the sampling units of the subsequent stage. First, asample of the first stage sampling units is drawn, then from each of the selected first stagesampling unit, a sample of the second stage sampling units is drawn. The procedure continuesdown to the final sampling units or population elements. Appropriate random sampling methodis adopted at each stage. It is appropriate where the population is scattered over a widergeographical area and no frame or list is available for sampling. It is also useful when a surveyhas to be made within a limited time and cost budget. The major disadvantage is that the

procedure of estimating sampling error and cost advantage is complicated.

Sequential sampling:

Sequential sampling is a non-probability sampling technique wherein the researcher picks asingle or a group of subjects in a given time interval, conducts his study, analyses the resultsthen picks another group of subjects if needed and so on. This sampling technique gives theresearcher limitless chances of fine tuning his research methods and gaining a vital insight intothe study that he is currently pursuing. There is very little effort in the part of the researcherwhen performing this sampling technique. It is not expensive, not time consuming and notworkforce extensive.

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This sampling method is hardly representative of the entire population. Its only hope of approaching representativeness is when the researcher chose to use a very large sample sizesignificant enough to represent a big fraction of the entire population. Due to theaforementioned disadvantages, results from this sampling technique cannot be used to createconclusions and interpretations pertaining to the entire population.

Question 4: List down various measures of central tendency and explain thedifference between them?

Answer:

Measures of Central Tendency:

The term central tendency refers to the "middle" value or perhaps a typical value of the data,and is measured using the mean , median , or mode . Each of these measures is calculateddifferently, and the one that is best to use depends upon the situation.

Analysis of data involves understanding of the characteristics of the data. The following are theimportant characteristics of a statistical data:

Central tendency

Dispersion

Skew ness

Kurtosis

In a data distribution, the individual items may have a tendency to come to a central positionor an average value. For instance, in a mark distribution, the individual students may scoremarks between zero and hundred. In this distribution, many students may score marks, whichare near to the average marks, i.e. 50. Such a tendency of the data to concentrate to the

central position of the distribution is called central tendency. Central tendency of the data ismeasured by statistical averages. Averages are classified into two groups.

1. Mathematical averages2. Positional averages

Statistical Averages

Mathematical averages Positional averages

Arithmetic mean MedianGeometric mean ModeHarmonic mean

Arithmetic mean, geometric mean and harmonic mean are mathematical averages. Median andmode are positional averages. These statistical measures try to understand how individualvalues in a distribution concentrate to a central value like average. If the values of distributionapproximately come near to the average value, we conclude that the distribution has centraltendency.

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Difference between Mean and Median:Mean (Mathematical averages) Median (Positional averages)When the sample size is large and doesnot include outliers, the mean scoreusually provides a better measure of central tendency.

The median may be a better indicator of the most typical value if a set of scoreshas an outlier . An outlier is an extremevalue that differs greatly from othervalues.

The mean is the most commonly-usedmeasure of central tendency. When wetalk about an "average", we usually arereferring to the mean

The median often is used when there are a fewextreme values that could greatly influence themean and distort what might be consideredtypical.

The mean is simply the sum of the valuesdivided by the total number of items in the set

The median is determined by sorting thedata set from lowest to highest values andtaking the data point in the middle of the

sequence

Question 5: Select any topic for research and explain how you will use bothsecondary and primary sources to gather the required information.

Answer:

For performing research on the literacy levels among families, the primary and secondarysources of data can be used very effectively. More specifically the primary sources of datacollection is suggested in this regard. Because personal data or data related to human beingsconsist of:

1. Demographic and socio-economic characteristics of individuals: Age, sex, race, social class,religion, marital status, education, occupation income, family size, location of the household lifestyle etc.2. Behavioral variables: Attitudes, opinions, awareness, knowledge, practice, intentions, etc.3. Organizational data consist of data relating to an organizations origin, ownership, objectives,resources, functions, performance and growth.4. Territorial data are related to geo-physical characteristics, resource endowment, population,occupational pattern infrastructure degree of development, etc. of spatial divisions like villages,cities, talluks, districts, state and the nation.

The data serve as the bases or raw materials for analysis. Without an analysis of factual data,no specific inferences can be drawn on the questions under study. Inferences based onimagination or guess work cannot provide correct answers to research questions. Therelevance, adequacy and reliability of data determine the quality of the findings of a study.

Data form the basis for testing the hypothesis formulated in a study. Data also provide thefacts and figures required for constructing measurement scales and tables, which are analyzedwith statistical techniques. Inferences on the results of statistical analysis and tests of significance provide the answers to research questions. Thus, the scientific process of measurements, analysis, testing and inferences depends on the availability of relevant dataand their accuracy. Hence, the importance of data for any research studies

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The sources of data may be classified into:a. Primary sourcesb. Secondary sources.

Primary Sources of Data:

Primary sources are original sources from which the researcher directly collects data that havenot been previously collected e.g.., collection of data directly by the researcher on brandawareness, brand preference, brand loyalty and other aspects of consumer behaviour from asample of consumers by interviewing them,. Primary data are first-hand information collectedthrough various methods such as observation, interviewing, mailing etc.

Advantage of Primary Data:It is original source of data

It is possible to capture the changes occurring in the course of time.It flexible to the advantage of researcher.Extensive research study is based of primary data

Disadvantage of Primary Data:Primary data is expensive to obtainIt is time consumingIt requires extensive research personnel who are skilled.It is difficult to administer

Methods of Collecting Primary Data:

Primary data are directly collected by the researcher from their original sources. In this case,the researcher can collect the required date precisely according to his research needs, he cancollect them when he wants them and in the form he needs them. But the collection of primarydata is costly and time consuming. Yet, for several types of social science research requireddata are not available from secondary sources and they have to be directly gathered from theprimary sources. In such cases where the available data are in appropriate, inadequate orobsolete, primary data have to be gathered. They include: socioeconomic surveys, socialanthropological studies of rural communities and tribal communities, sociological studies of social problems and social institutions. Marketing research, leadership studies, opinion polls,attitudinal surveys, readership, radio listening and T.V. viewing surveys, knowledge-awarenesspractice (KAP) studies, farm managements studies, business management studies etc. Thereare various methods of data collection. A ‘Method’ is different from a ‘Tool’ while a methodrefers to the way or mode of gathering data, a tool is an instruments used for the method. For

example, a schedule is used for interviewing. The important methods are (a) observation, (b)interviewing,(c)mail survey,(d)experimentation,(e) simulation and (f) projective technique.Each of these methods is discussed in detail in the subsequent sections in the later chapters.

Secondary Sources of Data:

These are sources containing data which have been collected and compiled for anotherpurpose. The secondary sources consists of readily compendia and already compiled statisticalstatements and reports whose data may be used by researchers for their studies e.g., censusreports , annual reports and financial statements of companies, Statistical statement, Reportsof Government Departments, Annual reports of currency and finance published by the ReserveBank of India, Statistical statements relating to Co-operatives and Regional Banks, published

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The use of secondary data enables a researcher to verify the findings bases on primarydata. It readily meets the need for additional empirical support. The researcher needsnot wait the time when additional primary data can be collected.

Disadvantages of Secondary Data:

The use of a secondary data has its own limitations.

The most important limitation is the available data may not meet our specific needs. Thedefinitions adopted by those who collected those data may be different; units of measure may not match; and time periods may also be different.The available data may not be as accurate as desired. To assess their accuracy we needto know how the data were collected.The secondary data are not up-to-date and become obsolete when they appear in print,because of time lag in producing them. For example, population census data arepublished two or three years later after compilation and no new figures will be availablefor another ten years.Finally, information about the whereabouts of sources may not be available to all social

scientists. Even if the location of the source is known, the accessibility depends primarilyon proximity. For example, most of the unpublished official records and compilations arelocated in the capital city, and they are not within the easy reach of researchers basedin far off places.

Evaluation of Secondary Data:

When a researcher wants to use secondary data for his research, he should evaluate thembefore deciding to use them.

1) Data Pertinence:

The first consideration in evaluation is to examine the pertinence of the availablesecondary data to the research problem under study. The following questions should beconsidered.What are the definitions and classifications employed? Are they consistent?What are the measurements of variables used? What is the degree to which theyconform to the requirements of our research?

On the basis of above consideration, the pertinence of the secondary data to the research onhand should be determined, as a researcher who is imaginative and flexible may be able toredefine his research problem so as to make use of otherwise unusable available data.

2) Data Quality:

If the researcher is convinced about the available secondary data for his needs, the next step isto examine the quality of the data. The quality of data refers to their accuracy, reliability andcompleteness. The assurance and reliability of the available secondary data depends on theorganization which collected them and the purpose for which they were collected. What is theauthority and prestige of the organization? Is it well recognized? Is it noted for reliability? It iscapable of collecting reliable data? Does it use trained and well qualified investigators? Theanswers to these questions determine the degree of confidence we can have in the data andtheir accuracy. It is important to go to the original source of the secondary data rather than touse an immediate source which has quoted from the original. Then only, the researcher canreview the cautionary and other comments that were made in the original source.

3) Data Completeness:

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Role of Diagrams:

Recent technological advances have enabled the large-scale adoption of diagrams in a diverserange of areas. Increasingly sophisticated visual representations are emerging and, to enableeffective communication, insight is required into how diagrams are used and when they areappropriate for use. The pervasive, everyday use of diagrams for communicating informationand ideas serves to illustrate the importance of providing a sound understanding of the rolethat diagrams can, and do, play. Research in the field of diagrams aims to improve ourunderstanding of the role of diagrams, sketches and other visualizations in communication,computation, cognition, creative thought, and problem solving. These concerns have triggereda surge of interest in the study of diagrams.

The study of diagrammatic communication as a whole must be pursued as an interdisciplinaryendeavor. Diagrams attract a large number of researchers from virtually all related fields,placing the conference as a major international event in the area.

b) Types and General rules for graphical representation of data:

Graphical representation is done of the data available. This is very important step of statisticalanalysis. We will be discussing the organization of data. The word 'Data' is plural for 'datum';datum means facts. Statistically the term is used for numerical facts such as measures of height, weight and scores on achievement and intelligence tests.

Graphs and diagram leave a lasting impression on the mind and make intelligible and easilyunderstandable the salient features of the data. Forecasting also becomes easier with the helpof graph. Thus it is of interest to study the graphical representation of data.

The graphical representation of data is categorized as basic five types:1) Bar graph2) Pie graph3) Line graph4) Scatter plot5) Histogram

Examples of graphical representation of data:Let us see some examples of graphical representation of data.

1) Bar chart:

A Bar chart (or diagram) is a graphical representation of data using bars (rectangles of samewidth ).

It is one dimensional in which case only the height of the rectangle matters.

year 1931 1941 1951 1961 1971 1981 population of a

place

6000 7600 8900 12000 13500 18000

Solution: scale: Y axis 1 cm = 1000 years

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2) Graphical Representation of Histogram:

A histogram (or rectangular diagram or block diagram) is a graphical representation of afrequency distribution in the form of rectangles one after the other with height proportional tothe frequencies.

It is two dimensional in which case the height as well as width of the rectanglematters.

Que: Represent the following data by means of a Histogram:

Age( inyears)

20-25

25-30

30-35

35-40

40-45

45-50

50-55

Numberof workers

3 4 5 6 5 4 3

3) Frequency Polygon of a Line Graph:

A frequency polygon can be constructed for a grouped frequency distribution, with equal-interval, in two different ways:

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Method I:Represent the class-marks along the x-axis.Represent the frequencies along y-axis.

Join these points, in order, by straight lines.The points at each end is joined to the immediate higher(or lower) class mark at zerofrequency so as to complete the polygon.

Method II:Represent a histogram of the given data.

Join the mid points of the tops of the adjacent rectangles by straight lines.The mid points at each end are joined to the immediate higher (or lower) at zerofrequency so as to complete the polygon.The two classes, one at each end, are to be included.

Construct a frequency polygon for the following data:

Monthly pocket expenses

of a student

0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40

Number of students 10 16 30 42 50 30 16 12

Solution:Here we have

Monthly pocket expenses of astudent(in $)

class- marks Number of students

0-5 2.5 105-10 7.5 1610-15 12.5 3015-20 17.5 4220-25 22.5 5025-30 27.5 3030-35 32.5 1635-40 37.5 12

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4) Cumulative Frequency Curve(ogive):

The Cumulative frequency curve for a grouped frequency distribution is obtained by plotting thepoints and then joining them by a free-hand smooth curve.This is also known as ogive .

Method:Form the cumulative frequency table.Mark the upper class limits along the x-axis.Mark the cumulative frequencies along the y-axis.Plot the points and join them by a free-hand smooth curve.

Draw a cumulative frequency curve for the following data:

Marks 0-4 4-8 8-12 12-16 16-20Number of students

4 6 10 8 4

The cumulative frequency table is as follows: Marks Number of

studentscumulativefrequency

0-4 4 44-8 6 4+6=108-12 10 10+10=2012-16 8 20+8=28

16-20 4 28+4=32Total 32

Joining these points by a free-hand smooth curve, we have the following cumulative frequencycurve:

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5) Pie-chart or Pie-graph:

It is drawn by first drawing a circle of a suitable radius and then dividing the angle of 360degree at its centre in proportion to the figures given under various heads.Solution:

<AOB = 14 x 360 /100 = 50.4<COD = 29 x 360 /100 = 104.4<EOF = 16 x 360 /100 = 57.6<BOC = 16 x 360 /100 = 57.6<DOE = 17 x 360 /100 = 61.2<FOA = 8 x 360 /100 = 28.8Take a circle with centre O and unit radius.

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Assignment Set -2

Question 1: What is questionnaire? Discuss the main points that you will take intoaccount while drafting a questionnaire?

Answer:

A questionnaire is a research instrument consisting of a series of questions and other promptsfor the purpose of gathering information from respondents. Although they are often designedfor statistical analysis of the responses, this is not always the case. The questionnaire wasinvented by Sir Francis Galton.

Questionnaires have advantages over some other types of surveys in that they are cheap, donot require as much effort from the questioner as verbal or telephone surveys, and often havestandardized answers that make it simple to compile data. However, such standardizedanswers may frustrate users. Questionnaires are also sharply limited by the fact that

respondents must be able to read the questions and respond to them. Thus, for somedemographic groups conducting a survey by questionnaire may not be practical.

As a type of survey, questionnaires also have many of the same problems relating to questionconstruction and wording that exist in other types of opinion polls.Questionnaires may be classified as:

Structured/ Standardized Questionnaire:

Structured questionnaires are those in which there are definite, concrete and preordainedquestions with additional questions limited to those necessary to clarify inadequate answers or

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to elicit more detailed responses. The questions are presented with exactly the same wordingand in the same order to all the respondents.

Unstructured Questionnaire: In unstructured questionnaires the respondent is given the opportunity to answer in his ownterms and in his own frame of reference.

Points to take into account while drafting a questionnaire:

Writing an effective questionnaire is not a task for novices. At the very least it requires anunderstanding of four basics. These are:

Considering the differences that exist when writing a questionnaire that respondent’swill fill out themselves as opposed to when a professional interviewer administers thequestionnaire to the respondent.Knowing what questions should be asked early on in the questionnaire,in the middle or toward the end.Understanding how to phrase questions.

Being sensitive to questionnaire length.

There are some basic differences in how the questionnaire should be constructed if it is to befilled out personally by the respondent or if an interviewer is going to administer it. These are:

Self-administered questionnaires should be simple, straightforward and logical. Question2 should follow question 1. Question 3 should follow question 2, and so forth. Further,the going-in assumption with self-administered questionnaires should be thatrespondents will not complete a questionnaire when there are complex skip patterns,when pages are crowded or hard to read or when instructions for completion are overlycomplex.

It has been estimated that as many as 50% of respondents who start a self-administered questionnaire will not complete it because they become irritated andannoyed at the way it is constructed. When writing a self-administered questionnaire,then, every care must be taken to ensure that it is easy to complete in that it almostanswers itself.

Self-administered questionnaires should be written with an eighth grade mentality inmind while interviewer-administered questionnaire can be quite complex. Becauseinterviewers are trained in the flow of the questionnaires they administer and willconduct a number of practice interviews prior to confronting a respondent, developing acomplex questionnaire that is interviewer-administered does not present a problem forthe respondent.

Keep the respondent in one mind-set at a time. If at all possible, complete all yourquestions about one topic before moving on to the next. For example, don’t ask about afavorite place to shop, then about brands used and then go back to additionalquestioning on favorite place to shop.

Save sensitive questions for the end. Again, this might not always be possible, but whenit doesn’t matter, be aware that sensitive questions such as race or income can alienaterespondents and turn them off to the entire interview process. If asked at the end,respondents are more likely to answer as they are wholly invested in the questionnaire.

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Biased question: What do you like about the last airline flight you took? Assumptionhere is that respondent liked something and the question tends to push for a positiveresponse.

Unbiased question. What, if anything, do you like the last airline flight you took? Bysimply using if anything as part of the question phrasing, the respondent is not put onthe spot to find something to like.

When conducting telephone interviews, it’s relatively easy to keep respondents on thephone and answering questions for 15, 20 or 25 minutes if the questionnaire has a goodflow and is thoughtfully written. But try keeping a respondent on the phone for 3minutes with a questionnaire that is the least bit confusing, seems redundant or isinsensitive to sensitive issues.

Question 2: What do you mean by primary data? What are the various methods of collecting primary data?

Answer:

Primary Date is data that has not been previously published, i.e. the data is derived from a newor original research study and collected at the source, e.g., in marketing, it is information thatis obtained directly from first-hand sources by means of surveys, observation orexperimentation.

Data observed or collected directly from first-hand experience. Published data and the datacollected in the past or other parties are called secondary data. Primary data are directlycollected by the researcher from their original sources. In this case, the researcher can collectthe required date precisely according to his research needs, he can collect them when he wants

them and in the form he needs them. But the collection of primary data is costly and timeconsuming. Yet, for several types of social science research required data are not availablefrom secondary sources and they have to be directly gathered from the primary sources.

In such cases where the available data are inappropriate, inadequate or obsolete, primary datahave to be gathered. They include: socio economic surveys, social anthropological studies of rural communities and tribal communities, sociological studies of social problems and socialinstitutions. Marketing research, leadership studies, opinion polls, attitudinal surveys,readership, radio listening and T.V. viewing surveys, knowledge-awareness practice (KAP)studies, farm managements studies, business management studies etc.

Primary data are always collected from the source. It is collected either by the investigatorhimself or through his agents. There are different methods of collecting primary data. Eachmethod has its relative merits and demerits. The investigator has to choose a particularmethod to collect the information. The choice to a large extent depends on the preliminaries todata collection some of the commonly used methods are discussed below.

1) Direct Personal observation:

This is a very general method of collecting primary data. Here the investigator directly contactsthe informants, solicits their cooperation and enumerates the data. The information arecollected by direct personal interviews.

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The novelty of this method is its simplicity. It is neither difficult for the enumerator nor theinformants because both are present at the spot of data collection. This method provides mostaccurate information as the investigator collects them personally. But as the investigator aloneis involved in the process, his personal bias may influence the accuracy of the data. So it isnecessary that the investigator should be honest, unbiased and experienced. In such cases thedata collected may be fairly accurate. However, the method is quite costly and time-consuming. So the method should be used when the scope of enquiry is small.

2) Indirect Oral Interviews:

This is an indirect method of collecting primary data. Here information is not collected directlyfrom the source but by interviewing persons closely related with the problem. This method isapplied to apprehend culprits in case of theft, murder etc. The information relating to one'spersonal life or which the informant hesitates to reveal are better collected by this method.Here the investigator prepares 'a small list of questions relating to the enquiry. The answers(information) are collected by interviewing persons well connected with the incident. Theinvestigator should cross-examine the informants to get correct information.

This method is time saving and involves relatively less cost. The accuracy of the information

largely depends upon the integrity of the investigator. It is desirable that the investigatorshould be experienced and capable enough to inspire and create confidence in the informant tocollect accurate data.

3) Mailed Questionnaire method:

This is a very commonly used method of collecting primary data. Here information is collectedthrough a set of questionnaire. A questionnaire is a document prepared by the investigatorcontaining a set of questions. These questions relate to the problem of enquiry directly orindirectly. Here first the questionnaires are mailed to the informants with a formal request toanswer the question and send them back. For better response the investigator should bear thepostal charges. The questionnaire should carry a polite note explaining the aims and objective

of the enquiry, definition of various terms and concepts used there. Besides this theinvestigator should ensure the secrecy of the information as well as the name of theinformants, if required.

Success of this method greatly depends upon the way in which the questionnaire is drafted. Sothe investigator must be very careful while framing the questions. The questions should be:

Short and clearFew in numberSimple and intelligibleCorroboratory in nature or there should be provision for cross checkImpersonal, non-aggressive typeSimple alternative, multiple-choice or open-end type

a) In the simple alternative question type, the respondent has to choose between alternativessuch as ‘Yes or No’, ‘right or wrong’ etc.For example: Is Adam Smith called father of Statistics? Yes/No

b) In the multiple choice type, the respondent has to answer from any of the givenalternatives.Example: To which sector do you belong?

Primary SectorSecondary SectorTertiary or Service Sector

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c) In the Open-end or free answer questions the respondents are given complete freedom inanswering the questions. The questions are like –

What are the defects of our educational system?The questionnaire method is very economical in terms of time, energy and money. The methodis widely used when the scope of enquiry is large. Data collected by this method are notaffected by the personal bias of the investigator. However the accuracy of the informationdepends on the cooperation and honesty of the informants. This method can be used only if theinformants are cooperative, conscious and educated. This limits the scope of the method.

4) Schedule Method:

In case the informants are largely uneducated and non-responsive data cannot be collected bythe mailed questionnaire method. In such cases, schedule method is used to collect data. Herethe questionnaires are sent through the enumerators to collect information. Enumerators arepersons appointed by the investigator for the purpose. They directly meet the informants withthe questionnaire. They explain the scope and objective of the enquiry to the informants andsolicit their cooperation. The enumerators ask the questions to the informants and record their

answers in the questionnaire and compile them. The success of this method depends on thesincerity and efficiency of the enumerators. So the enumerator should be sweet-tempered,good-natured, trained and well-behaved.

Schedule method is widely used in extensive studies. It gives fairly correct result as theenumerators directly collect the information. The accuracy of the information depends upon thehonesty of the enumerators. They should be unbiased. This method is relatively more costlyand time-consuming than the mailed questionnaire method.

5) From Local Agents:

Sometimes primary data are collected from local agents or correspondents. These agents areappointed by the sponsoring authorities. They are well conversant with the local conditions likelanguage, communication, food habits, traditions etc. Being on the spot and well acquaintedwith the nature of the enquiry they are capable of furnishing reliable information.

The accuracy of the data collected by this method depends on the honesty and sincerity of theagents because they actually collect the information from the spot. Information from a widearea at less cost and time can be collected by this method. The method is generally used bygovernment agencies, newspapers, periodicals etc. to collect data.

Information is like raw materials or inputs in an enquiry. The result of the enquiry basicallydepends on the type of information used. Primary data can be collected by employing any of the above methods. The investigator should make a rational choice of the methods to be usedfor collecting data because collection of data forms the beginning of the statistical enquiry.

Question 3a. Analyse the case study and descriptive approach to research.b. Distinguish between research methods & research Methodology.

Answer:

a) Case Study and descriptive approach to research:

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Descriptive research, also known as statistical research, describes data and characteristicsabout the population or phenomenon being studied. Descriptive research answers the questionswho, what, where, when and how...

Although the data description is factual, accurate and systematic, the research cannot describewhat caused a situation. Thus, Descriptive research cannot be used to create a causalrelationship, where one variable affects another. In other words, descriptive research can besaid to have a low requirement for internal validity.

The description is used for frequencies, averages and other statistical calculations. Often thebest approach, prior to writing descriptive research, is to conduct a survey investigation.Qualitative research often has the aim of description and researchers may follow-up withexaminations of why the observations exist and what the implications of the findings are.

In short descriptive research deals with everything that can be counted and studied. But thereare always restrictions to that. Your research must have an impact to the lives of the peoplearound you e.g. finding the most frequent disease that affects the children of a town. Thereader of the research will know what to do to prevent that disease thus; more people will live

a healthy life.

Descriptive research does not fit neatly into the definition of either quantitative or qualitativeresearch methodologies, but instead it can utilize elements of both, often within the samestudy. The term descriptive research refers to the type of research question, design, and dataanalysis that will be applied to a given topic. Descriptive statistics tell what is, while inferentialstatistics try to determine cause and effect.

A case study is a research method common in social science. It is based on an in-depthinvestigation of a single individual, group, or event. Case studies may be descriptive orexplanatory. The latter type is used to explore causation in order to find underlying principles.They may be prospective, in which criteria are established and cases fitting the criteria areincluded as they become available, or retrospective, in which criteria are established forselecting cases from historical records for inclusion in the study.

Rather than using samples and following a rigid protocol (strict set of rules) to examine limitednumber of variables, case study methods involve an in-depth, longitudinal (over a long periodof time) examination of a single instance or event: a case. They provide a systematic way of looking at events, collecting data, analyzing information, and reporting the results. As a resultthe researcher may gain a sharpened understanding of why the instance happened as it did,and what might become important to look at more extensively in future research. Case studieslend themselves to both generating and testing hypotheses.

Another suggestion is that case study should be defined as a research strategy, an empiricalinquiry that investigates a phenomenon within its real-life context. Case study research meanssingle and multiple case studies, can include quantitative evidence, relies on multiple sources of evidence and benefits from the prior development of theoretical propositions. Case studiesshould not be confused with qualitative research and they can be based on any mix of quantitative and qualitative evidence. Single-subject research provides the statisticalframework for making inferences from quantitative case-study data

b) Distinction between research methods and research Methodology:

Research Methods Research MethodologyResearch methods are the variousprocedures, schemes, algorithms, etc.

Research methodology is a systematicway to solve a problem. It is a science of

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used in research. All the methods used bya researcher during a research study aretermed as research methods. They areessentially planned, scientic and value-neutral. They include theoreticalprocedures, experimental studies,numerical schemes, statistical approaches,etc. Research methods help us collectsamples, data and nd a solution to aproblem. Particularly, scientic researchmethods call for explanations based oncollected facts, measurements andobservations and not on reasoning alone.They ac- cept only those explanationswhich can be veried by experiments.

studying how research is to be carried out.Essentially, the procedures by whichresearchers go about their work of describing, explaining and predictingphenomena are called researchmethodology. It is also dened as thestudy of methods by which knowledge isgained. Its aim is to give the work plan of research.

Question 4: Explain the important concepts in Research design?

Answer:

The research designer understandably cannot hold all his decisions in his head. Even if hecould, he would have difficulty in understanding how these are inter-related. Therefore, herecords his decisions on paper or record disc by using relevant symbols or concepts. Such asymbolic construction may be called the research design or model. A research design is alogical and systematic plan prepared for directing a research study. It specifies the objectivesof the study, the methodology and techniques to be adopted for achieving the objectives. Itconstitutes the blue print for the plan is the overall scheme or program of research. A research

design is the program that guides the investigator in the process of collecting, analysing andinterpreting observations. It provides a systematic plan of procedure for the researcher tofollow elltiz, Jahoda and Destsch and Cook describe, “A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to theresearch purpose with economy in procedure.”

Components of Research Design: It is important to be familiar with the important concepts relating to research design. They are:

1. Dependent and Independent variables:

A magnitude that varies is known as a variable. The concept may assume different quantitativevalues, like height, weight, income, etc. Qualitative variables are not quantifiable in thestrictest sense of objectivity. However, the qualitative phenomena may also be quantified interms of the presence or absence of the attribute considered. Phenomena that assume differentvalues quantitatively even in decimal points are known as “continuous variables. But, allvariables need not be continuous. Values that can be expressed only in integer values arecalled” non-continuous variables. In statistical term, they are also known as „discrete variable.For example, age is a continuous variable; whereas the number of children is a non-continuousvariable. When changes in one variable depends upon the changes in one or more othervariables, it is known as a dependent or endogenous variable, and the variables that cause thechanges in the dependent variable are known as the independent or explanatory or exogenous

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variables. For example, if demand depends upon price, then demand is a dependent variable,while price is the independent variable.

And if, more variables determine demand, like income and prices of substitute commodity, thendemand also depends upon them in addition to the own price. Then, demand is a dependentvariable which is determined by the independent variables like own price, income and price of substitute.

2. Extraneous variable: The independent variables which are not directly related to the purpose of the study but affectthe dependent variable are known as extraneous variables. For instance, assume that aresearcher wants to test the hypothesis that there is relationship between children’s schoolperformance and their self-concepts, in which case the latter is an independent variable andthe former, the dependent variable. In this context, intelligence may also influence the schoolperformance. However, since it is not directly related to the purpose of the study undertakenby the researcher, it would be known as an extraneous variable. The influence caused by theextraneous variable on the dependent variable is technically called as an „experimental errorsTherefore, a research study should always be framed in such a manner that the dependent

variable completely influences the change in the independent variable and any otherextraneous variable or variables. 3. Control:

One of the most important features of a good research design is to minimize the effect of extraneous variable. Technically, the term control is used when a researcher designs the studyin such a manner that it minimizes the effects of extraneous independent variables. The termcontrol is used in experimental research to reflect the restrain in experimental conditions.

4. Confounded relationship:

The relationship between dependent and independent variables is said to be confounded by anextraneous variable, when the dependent variable is not free from its effects.

Research hypothesis:

When a prediction or a hypothesized relationship is tested by adopting scientificmethods, it is known as research hypothesis. The research hypothesis is a predictivestatement which relates a dependent variable and an independent variable. Generally, aresearch hypothesis must consist of at least one dependent variable and oneindependent variable. Whereas, the relationships that are assumed but not be testedare predictive statements that are not to be objectively verified are not classified asresearch hypothesis.

Experimental and control groups:

When a group is exposed to usual conditions in an experimental hypothesis-testingresearch, it is known as „control group. On the other hand, when the group is exposedto certain new or special condition, it is known as an „experimental group. In the afore-mentioned example, the Group A can be called a control group and the Group B anexperimental one. If both the groups A and B are exposed to some special feature, thenboth the groups may be called as „experimental groups. A research design may includeonly the experimental group or the both experimental and control groups together.

Treatments:

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Treatments are referred to the different conditions to which the experimental andcontrol groups are subject to. In the example considered, the two treatments are theparents with regular earnings and those with no regular earnings. Likewise, if a researchstudy attempts to examine through an experiment regarding the comparative impacts of three different types of fertilizers on the yield of rice crop, then the three types of fertilizers would be treated as the three treatments.

Experiment:

An experiment refers to the process of verifying the truth of a statistical hypothesisrelating to a given research problem. For instance, experiment may be conducted toexamine the yield of a certain new variety of rice crop developed. Further, Experimentsmay be categorized into two types namely, absolute experiment and comparativeexperiment. If a researcher wishes to determine the impact of a chemical fertilizer onthe yield of a particular variety of rice crop, then it is known as absolute experiment.Meanwhile, if the researcher wishes to determine the impact of chemical fertilizer ascompared to the impact of bio-fertilizer, then the experiment is known as a comparativeexperiment.

Experiment unit:

Experimental units refer to the predetermined plots, characteristics or the blocks, towhich the different treatments are applied. It is worth mentioning here that suchexperimental units must be selected with great caution.

Question 5: What are the differences between observation and interviewing asmethods of data collection? Give two specific examples of situations where eitherobservation or interviewing would be more appropriate.

Answer:

Observation vs. interviewing as Methods of Data Collection:

Collection of data is the most crucial part of any research project as the success or failure of the project is dependent upon the accuracy of the data. Use of wrong methods of datacollection or any inaccuracy in collecting data can have significant impact on the results of astudy and may lead to results that are not valid. There are many techniques of data collectionalong a continuum and observation and interviewing are two of the popular methods on thiscontinuum that has quantitative methods at one end while qualitative methods at the otherend. Though there are many similarities in these two methods and they serve the same basicpurpose, there are differences that will be highlighted in this article.

Observation:

Observation, as the name implies refers to situations where participants are observed from asafe distance and their activities are recorded minutely. It is a time consuming method of datacollection as you may not get the desired conditions that are required for your research andyou may have to wait till participants are in the situation you want them to be in. Classicexamples of observation are wild life researchers who wait for the animals of birds to be in anatural habitat and behave in situations that they want to focus upon. As a method of datacollection, observation has limitations but produces accurate results as participants areunaware of being closely inspected and behave naturally.

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Some interviews may be very formal, while others will feel more like an informal chatabout you and your interests. Be aware that you are still being assessed, howeverinformal the discussion may seem.

Portfolio based interviews:

If the role is within the arts, media or communications industries, you may be asked tobring a portfolio of your work to the interview, and to have an in-depth discussion aboutthe pieces you have chosen to include.

Senior/case study interviews:These ranges from straightforward scenario questions (e.g. µWhat would you do in asituation where to the detailed analysis of a hypothetical business problem. You will beevaluated on your analysis of the problem, how you identify the key issues, how youpursue a particular line of thinking and whether you can develop and present anappropriate framework for organising your thoughts.

Specific types of interview

The Screening Interview:

Companies use screening tools to ensure that candidates meet minimum qualificationrequirements. Computer programs are among the tools used to weed out unqualifiedcandidates. (This is why you need a digital resume that is screening-friendly. See our resumecentre for help.) Sometimes human professionals are the gatekeepers. Screening interviewersoften have honed skills to determine whether there is anything that might disqualify you forthe position. Remember they do not need to know whether you are the best fit for the position,only whether you are not a match. For this reason, screeners tend to dig for dirt. Screeners willhone in on gaps in your employment history or pieces of information that look inconsistent.They also will want to know from the outset whether you will be too expensive for thecompany.

Some tips for maintaining confidence during screening interviews:

Highlight your accomplishments and qualifications.

Get into the straightforward groove. Personality is not as important to the screener asverifying your qualifications. Answer questions directly and succinctly. Saveyour winning personality for the person making hiring decisions!

Be tactful about addressing income requirements. Give a range, and try to avoid givingspecifics by replying, "I would be willing to consider your best offer."

If the interview is conducted by phone, it is helpful to have note cards with your vitalinformation sitting next to the phone. That way, whether the interviewer catches yousleeping or vacuuming the floor, you will be able to switch gears quickly

The Informational Interview:

On the opposite end of the stress spectrum from screening interviews is the informationalinterview. A meeting that you initiate, the informational interview is underutilized by job-seekers who might otherwise consider themselves savvy to the merits of networking.Jobseekers ostensibly secure informational meetings in order to seek the advice of someone intheir current or desired field as well as to gain further references to people who can lend

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insight. Employers that like to stay apprised of available talent even when they do not havecurrent job openings, are often open to informational interviews, especially if they like to sharetheir knowledge, feel flattered by your interest, or esteem the mutual friend that connected youto them. During an informational interview, the jobseeker and employer exchange informationand get to know one another better without reference to specific job opening.

This takes off some of the performance pressure, but be intentional nonetheless:

Come prepared with thoughtful questions about the field and the company.

Gain references to other people and make sure that the interviewer would becomfortable if you contact other people and use his or her name.

Give the interviewer your card, contact information and resume.· Write a thank you noteto the interviewer.

The Directive Style:

In this style of interview, the interviewer has a clear agenda that he or she follows

unflinchingly. Sometimes companies use this rigid format to ensure parity between interviews;when interviewers ask each candidate the same series of questions, they can more readilycompare the results. Directive interviewers rely upon their own questions and methods to teasefrom you what they wish to know. You might feel like you are being steam-rolled, or you mightfind the conversation develops naturally. Their style does not necessarily mean that they havedominance issues, although you should keep an eye open for these if the interviewer would beyour supervisor. Either way, remember:· Flex with the interviewer, following his or her lead.·Do not relinquish complete control of the interview. If the interviewer does not ask you forinformation that you think is important to proving your superiority as a candidate, politelyinterject it.

The Meandering Style:

This interview type, usually used by inexperienced interviewers, relies on you to lead thediscussion. It might begin with a statement like "tell me about yourself," which you can use toyour advantage. The interviewer might ask you another broad, open-ended question beforefalling into silence. This interview style allows you tactfully to guide the discussion in a way thatbest serves you. The following strategies, which are helpful for any interview, are particularlyimportant when interviewers use a non-directive approach:

Come to the interview prepared with highlights and anecdotes of your skills, qualitiesand experiences. Do not rely on the interviewer to spark your memory-jot down somenotes that you can reference throughout the interview.

Remain alert to the interviewer. Even if you feel like you can take the driver's seat andgo in any direction you wish, remain respectful of the interviewer's role. If he or shebecomes more directive during the interview, adjust.

Ask well-placed questions. Although the open format allows you significantly to shapethe interview, running with your own agenda and dominating the conversation meansthat you run the risk of missing important information about the company and its needs.

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Question 6: Strictly speaking, would case studies be considered as scientificresearch? Why or why not?

Answer:

Case studies are a tool for discussing scientific integrity. Although one of the most frequentlyused tools for encouraging discussion, cases are only one of many possible tools. Many of theprinciples discussed below for discussing case studies can be generalized to other approachesto encouraging discussion about research ethics.

Cases are designed to confront readers with specific real-life problems that do not lendthemselves to easy answers. Case discussion demands critical and analytical skills and, whenimplemented in small groups, also fosters collaboration (Pimple, 2002). By providing a focus fordiscussion, cases help trainees to define or refine their own standards, to appreciate alternativeapproaches to identifying and resolving ethical problems, and to develop skills for analyzingand dealing with hard problems on their own. The effective use of case studies is comprised of many factors, including:

appropriate selection of case(s) (topic, relevance, length, complexity)

method of case presentation (verbal, printed, before or during discussion)format for case discussion (Email or Internet-based, small group, large group)leadership of case discussion (choice of discussion leader, roles and responsibilities fordiscussion leader)outcomes for case discussion (answers to specific questions, answers to generalquestions, written or verbal summaries)

Research methods don't seem so intimidating when you're familiar with the terminology. This isimportant whether you're conducting evaluation or merely reading articles about other studiesto incorporate in your program. To help with understanding, here are some basic definitionsused.

Variable: Characteristics by which people or things can be described. Must have morethan one level; in other words, to be able to change over time for the sameperson/object, or from person to person, or object to object. Some variables, calledattributes, cannot be manipulated by the researcher (e.g., socioeconomic status, IQscore, race, gender, etc.). Some variables can be manipulated but are not in a particularstudy. This occurs when subjects self-select the level of the independent variable, or thelevel is naturally occurring (as with ex post facto research).

Manipulation: Random assignment of subjects to levels of the independent variable(treatment groups).

Independent variable: The treatment, factor, or presumed cause that will produce achange in the dependent variable. This is what the experimenter tries to manipulate. It

is denoted as "X" on the horizontal axis of a graph.

Dependent variable: The presumed effect or consequence resulting from changes inthe independent variable. This is the observation made and is denoted by "Y" on thevertical axis of a graph. The score of "Y" depends on the score of "X."

Population: The complete set of subjects that can be studied: people, objects, animals,plants, etc.

Sample: A subset of subjects that can be studied to make the research project moremanageable. There are a variety of ways samples can be taken. If a large enough

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random samples are taken, the results can be statistically similar to taking a census of an entire population--with reduced effort and cost.

Case Study:

A case study is conducted for similar purpose as the above but is usually done with a smallersample size for more in-depth study. A case study often involves direct observation orinterviews with single subjects or single small social units such as a family, club, schoolclassroom, etc. This is typically considered qualitative research.

Purpose: Explain or Predict

Type of Research to Use: Relational Study

In a relational study you start with a research hypothesis, that is, is what you're trying to"prove."

Examples of research hypotheses for a relational study:

The older the person, the more health problems he or she encounters.4-H members attending 4-H summer camp stay enrolled in 4-H longer.The greater the number of money management classes attended, the greater theamount of annual savings achieved.

Types of relational studies include correlational studies and ex post facto studies.

Correlational Study:

A correlational study compares two or more different characteristics from the same group of people and explains how two characteristics vary together and how well one can be predictedfrom knowledge of the other.

A concurrent correlational study draws a relationship between characteristics at the same pointin time. For example, a student's grade point average is related to his or her class rank.

A predictive correlational study could predict a later set of data from an earlier set. Forexample, a student's grade point average might predict the same student's grade pointaverage during senior year. A predictive correlational study could also use one characteristic topredict what another characteristic will be at another time. For example, a student's SAT scoreis designed to predict college freshman grade point average.

Ex Post Facto (After the Fact) Study:

An ex post facto study is used when experimental research is not possible, such as when

people have self-selected levels of an independent variable or when a treatment is naturallyoccurring and the researcher could not "control" the degree of its use. The researcher starts byspecifying a dependent variable and then tries to identify possible reasons for its occurrence aswell as alternative (rival) explanations such confounding (intervening, contaminating, orextraneous) variables are "controlled" using statistics.

This type of study is very common and useful when using human subjects in real-worldsituations and the investigator comes in "after the fact." For example, it might be observed thatstudents from one town have higher grades than students from a different town attending thesame high school. Would just "being from a certain town" explain the differences? In an ex postfacto study, specific reasons for the differences would be explored, such as differences inincome, ethnicity, parent support, etc. It is important to recognize that, in a relational study,

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"cause and effect" cannot be claimed. All that can be claimed is that that there is a relationshipbetween the variables.

For that matter, variables that are completely unrelated could, in fact, vary together due tonothing more than coincidence. That is why the researcher needs to establish a plausiblereason (research hypothesis) for why there might be a relationship between two variablesbefore conducting a study. For instance, it might be found that all football teams with blueuniforms won last week. There is no likely reason why the uniform color had any relationship tothe games' outcomes, and it certainly was not the cause for victory. Similarly, you must becareful about claiming that your Extension program was the "cause" of possible results.

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