mb0034(research methodology)

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Research Methodology (MB0034) Assignment: Set -1

MBA III SEM

MB0034

RESEARCH METHODOLOGY

SET -1

ASSIGNMENT

Q 1. Give examples of specific situations that would call

for the following types of research, explaining why a)Exploratory research b) Descriptive research c) Diagnosticresearch d) Evaluation research.

Ans.: Research may be classified crudely according to its major intent or themethods. According to the intent, research may be classified as:Basic (aka fundamental or pure) research is driven by a scientist's curiosityor interest in a scientific question. The main motivation is to expand man'sknowledge, not to create or invent something. There is no obviouscommercial value to the discoveries that result from basic research.

For example, basic science investigations probe for answers to questionssuch as:

How did the universe begin?

What are protons, neutrons, and electrons composed of?

How do slime molds reproduce?

What is the specific genetic code of the fruit fly?

Most scientists believe that a basic, fundamental understanding of allbranches of science is needed in order for progress to take place. In otherwords, basic research lays down the foundation for the applied science thatfollows. If basic work is done first, then applied spin-offs often eventuallyresult from this research. As Dr. George Smoot of LBNL says, "People cannotforesee the future well enough to predict what's going to develop from basicresearch. If we only did applied research, we would still be making betterspears."

Applied research is designed to solve practical problems of the modernworld, rather than to acquire knowledge for knowledge's sake. One might say

that the goal of the applied scientist is to improve the human condition.

For example, applied researchers may investigate ways to:

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Improve agricultural crop production

Treat or cure a specific disease

Improve the energy efficiency of homes, offices, or modes of transportation

Some scientists feel that the time has come for a shift in emphasis awayfrom purely basic research and toward applied science. This trend, they feel,is necessitated by the problems resulting from global overpopulation,pollution, and the overuse of the earth's natural resources.

Exploratory research provides insights into and comprehension of an issueor situation. It should draw definitive conclusions only with extreme caution.Exploratory research is a type of research conducted because a problem hasnot been clearly defined. Exploratory research helps determine the bestresearch design, data collection method and selection of subjects. Given itsfundamental nature, exploratory research often concludes that a perceivedproblem does not actually exist.

Exploratory research often relies on secondary research such as reviewingavailable literature and/or data, or qualitative approaches such as informaldiscussions with consumers, employees, management or competitors, andmore formal approaches through in-depth interviews, focus groups,projective methods, case studies or pilot studies. The Internet allows forresearch methods that are more interactive in nature: E.g., RSS feeds

efficiently supply researchers with up-to-date information; major searchengine search results may be sent by email to researchers by services suchas Google Alerts; comprehensive search results are tracked over lengthyperiods of time by services such as Google Trends; and Web sites may becreated to attract worldwide feedback on any subject.

The results of exploratory research are not usually useful for decision-makingby themselves, but they can provide significant insight into a given situation.Although the results of qualitative research can give some indication as tothe "why", "how" and "when" something occurs, it cannot tell us "how often"or "how many."Exploratory research is not typically generalizable to the population at large.A defining characteristic of causal research is the random assignment of participants to the conditions of the experiment; e.g., an Experimental and aControl Condition... Such assignment results in the groups being comparableat the beginning of the experiment. Any difference between the groups atthe end of the experiment is attributable to the manipulated variable.Observational research typically looks for difference among "in-tact" definedgroups. A common example compares smokers and non-smokers with regardto health problems. Causal conclusions can't be drawn from such a studybecause of other possible differences between the groups; e.g., smokersmay drink more alcohol than non-smokers. Other unknown differences could

exist as well. Hence, we may see a relation between smoking and health buta conclusion that smoking is a cause would not be warranted in thissituation. (Cp)

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Descriptive research , also known as statistical research, describes dataand characteristics about the population or phenomenon being studied.Descriptive research answers the questions who, what, where, when andhow.Although the data description is factual, accurate and systematic, theresearch cannot describe what caused a situation. Thus, descriptive researchcannot be used to create a causal relationship, where one variable affectsanother. In other words, descriptive research can be said to have a lowrequirement for internal validity.

The description is used for frequencies, averages and other statisticalcalculations. Often the best approach, prior to writing descriptive research, isto conduct a survey investigation. Qualitative research often has the aim of description and researchers may follow-up with examinations of why theobservations exist and what the implications of the findings are.In short descriptive research deals with everything that can be counted andstudied. But there are always restrictions to that. Your research must havean impact to the life of the people around you. For example, finding the mostfrequent disease that affects the children of a town. The reader of theresearch will know what to do to prevent that disease thus; more people willlive a healthy life.

Diagnostic study : it is similar to descriptive study but with different focus.It is directed towards discovering what is happening and what can be doneabout. It aims at identifying the causes of a problem and the possiblesolutions for it. It may also be concerned with discovering and testingwhether certain variables are associated. This type of research requires prior

knowledge of the problem, its thorough formulation, clear-cut definition of the given population, adequate methods for collecting accurate information,precise measurement of variables, statistical analysis and test of significance.

Evaluation Studies : it is a type of applied research. It is made for assessingthe effectiveness of social or economic programmes implemented or forassessing the impact of development of the project area. It is thus directedto assess or appraise the quality and quantity of an activity and itsperformance and to specify its attributes and conditions required for itssuccess. It is concerned with causal relationships and is more actively guidedby hypothesis. It is concerned also with change over time.

Action research is a reflective process of progressive problem solving ledby individuals working with others in teams or as part of a "community of practice" to improve the way they address issues and solve problems. Actionresearch can also be undertaken by larger organizations or institutions,assisted or guided by professional researchers, with the aim of improvingtheir strategies, practices, and knowledge of the environments within whichthey practice. As designers and stakeholders, researchers work with othersto propose a new course of action to help their community improve its work

practices (Center for Collaborative Action Research). Kurt Lewin, then aprofessor at MIT, first coined the term action research in about 1944, and itappears in his 1946 paper Action Research and Minority Problems. In thatpaper, he described action research as a comparative research on the

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conditions and effects of various forms of social action and research leadingto social action that uses a spiral of steps, each of which is composed of acircle of planning, action, and fact-finding about the result of the action.Action research is an interactive inquiry process that balances problemsolving actions implemented in a collaborative context with data-drivencollaborative analysis or research to understand underlying causes enablingfuture predictions about personal and organizational change (Reason &Bradbury, 2001). After six decades of action research development, manymethodologies have evolved that adjust the balance to focus more on theactions taken or more on the research that results from the reflectiveunderstanding of the actions. This tension exists between

Those that are more driven by the researchers agenda to thosemore driven by participants;

Those that are motivated primarily by instrumental goalattainment to those motivated primarily by the aim of personal,organizational, or societal transformation; and1st-, to 2nd-, to 3rd-person research, that is, my research on myown action, aimed primarily at personal change; our research onour group (family/team), aimed primarily at improving the group;and scholarly research aimed primarily at theoreticalgeneralization and/or large scale change.

Action research challenges traditional social science, by moving beyondreflective knowledge created by outside experts sampling variables to anactive moment-to-moment theorizing, data collecting, and inquiringoccurring in the midst of emergent structure. Knowledge is always gainedthrough action and for action. From this starting point, to question thevalidity of social knowledge is to question, not how to develop a reflectivescience about action, but how to develop genuinely well-informed action how to conduct an action science (Tolbert 2001).

Q 2. In the context of hypothesis testing, briefly explain thedifference between a) Null and alternative hypothesis b)Type 1 and type 2 error c) Two tailed and one tailed test d)Parametric and non-parametric tests.

Ans.: Some basic concepts in the context of testing of hypotheses are explainedbelow 1) Null Hypotheses and Alternative Hypotheses : In the context of statisticalanalysis, we often talk about null and alternative hypotheses. If we are tocompare the superiority of method A with that of method B and we proceed onthe assumption that both methods are equally good, then this assumption istermed as a null hypothesis. On the other hand, if we think that method A issuperior, then it is known as an alternative hypothesis.

These are symbolically represented as:

Null hypothesis = H0 and Alternative hypothesis = Ha

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Suppose we want to test the hypothesis that the population mean is equal to thehypothesized mean ( H0) = 100. Then we would say that the null hypothesis isthat the population mean is equal to the hypothesized mean 100 andsymbolically we can express it as: H0: = H0=100

If our sample results do not support this null hypothesis, we should concludethat something else is true. What we conclude rejecting the null hypothesisis known as an alternative hypothesis. If we accept H0, then we are rejectingHa and if we reject H0, then we are accepting Ha. For H0: = H0=100, wemay consider three possible alternative hypotheses as follows:

AlternativeHypotheses

To be read as follows

Ha: H0 (The alternative hypothesis is that the population mean is notequal to 100 i.e., it may be more or less 100)

Ha: > H0 (The alternative hypothesis is that the population mean isgreater than 100)

Ha: < H0 (The alternative hypothesis is that the population mean is lessthan 100)

The null hypotheses and the alternative hypotheses are chosen before thesample is drawn (the researcher must avoid the error of deriving hypothesesfrom the data he collects and testing the hypotheses from the same data). In thechoice of null hypothesis, the following considerations are usually kept in view:

a. The alternative hypothesis is usually the one, which is to be proved, and thenull hypothesis is the one that is to be disproved. Thus a null hypothesisrepresents the hypothesis we are trying to reject, while the alternativehypothesis represents all other possibilities.

b. If the rejection of a certain hypothesis when it is actually true involves greatrisk, it is taken as null hypothesis, because then the probability of rejecting itwhen it is true is (the level of significance) which is chosen very small.

c. The null hypothesis should always be a specific hypothesis i.e., it should notstate an approximate value.

Generally, in hypothesis testing, we proceed on the basis of the null hypothesis,keeping the alternative hypothesis in view. Why so? The answer is that on theassumption that the null hypothesis is true, one can assign the probabilities todifferent possible sample results, but this cannot be done if we proceed withalternative hypotheses. Hence the use of null hypotheses (at times also knownas statistical hypotheses) is quite frequent.

2) The Level of Significance: This is a very important concept in the contextof hypothesis testing. It is always some percentage (usually 5%), which shouldbe chosen with great care, thought and reason. In case we take the significance

level at 5%, then this implies that H0 will be rejected when the sampling result(i.e., observed evidence) has a less than 0.05 probability of occurring if H0 istrue. In other words, the 5% level of significance means that the researcher iswilling to take as much as 5% risk rejecting the null hypothesis when it (H0)Roll No: 540911501 Page 6 of 22


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happens to be true. Thus the significance level is the maximum value of theprobability of rejecting H0 when it is true and is usually determined in advancebefore testing the hypothesis.3) Decision Rule or Test of Hypotheses: Given a hypothesis Ha and analternative hypothesis H0, we make a rule, which is known as a decision rule,according to which we accept H0 (i.e., reject Ha) or reject H0 (i.e., accept Ha).For instance, if H0 is that a certain lot is good (there are very few defectiveitems in it), against Ha, that the lot is not good (there are many defective itemsin it), then we must decide the number of items to be tested and the criterion foraccepting or rejecting the hypothesis. We might test 10 items in the lot and planour decision saying that if there are none or only 1 defective item among the 10,we will accept H0; otherwise we will reject H0 (or accept Ha). This sort of basis isknown as a decision rule.

4) Type I & II Errors: In the context of testing of hypotheses, there arebasically two types of errors that we can make. We may reject H0 when H0 istrue and we may accept H0 when it is not true. The former is known as Type Iand the latter is known as Type II. In other words, Type I error means rejection of hypotheses, which should have been accepted, and Type II error meansaccepting of hypotheses, which should have been rejected. Type I error isdenoted by (alpha), also called as level of significance of test; and Type II erroris denoted by (beta).

Decision

Accept H0 Reject H0H0(true)

Correct decision Type I error (error)

Ho(false)

Type II error (error)

Correct decision

The probability of Type I error is usually determined in advance and isunderstood as the level of significance of testing the hypotheses. If type I error isfixed at 5%, it means there are about 5 chances in 100 that we will reject H0when H0 is true. We can control type I error just by fixing it at a lower level. Forinstance, if we fix it at 1%, we will say that the maximum probability of

committing type I error would only be 0.01.But with a fixed sample size n, when we try to reduce type I error, the probabilityof committing type II error increases. Both types of errors cannot be reducedsimultaneously, since there is a trade-off in business situations. Decision makersdecide the appropriate level of type I error by examining the costs of penaltiesattached to both types of errors. If type I error involves time and trouble of reworking a batch of chemicals that should have been accepted, whereas type IIerror means taking a chance that an entire group of users of this chemicalscompound will be poisoned, then in such a situation one should prefer a type Ierror to a type II error. As a result, one must set a very high level for type I errorin ones testing techniques of a given hypothesis. Hence, in testing of hypotheses, one must make all possible efforts to strike an adequate balancebetween Type I & Type II error.

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1 5) Two Tailed Test & One Tailed Test: In the context of hypothesis testing,these two terms are quite important and must be clearly understood. A two-tailed test rejects the null hypothesis if, say, the sample mean is significantlyhigher or lower than the hypothesized value of the mean of the population. Sucha test is inappropriate when we have H0: = H0 and Ha: H0 which may> H0 or


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they will buy, and let friends and family know where they got it. Making themhappy makes the money.

Casual relationship Marketing was first defined as a form of marketing developed from direct response marketing campaigns, which emphasizescustomer retention and satisfaction, rather than a dominant focus on salestransactions.

As a practice, Relationship Marketing differs from other forms of marketing inthat it recognizes the long term value of customer relationships and extendscommunication beyond intrusive advertising and sales promotional messages.

With the growth of the internet and mobile platforms, Relationship Marketing hascontinued to evolve and move forward as technology opens more collaborativeand social communication channels. This includes tools for managingrelationships with customers that goes beyond simple demographic andcustomer service data. Relationship Marketing extends to include InboundMarketing efforts (a combination of search optimization and Strategic Content),PR, Social Media and Application Development.

Just like Customer relationship management(CRM), Relationship Marketing is abroadly recognized, widely-implemented strategy for managing and nurturing acompanys interactions with clients and sales prospects. It also involves usingtechnology to, organize, synchronize business processes (principally sales andmarketing activities) and most importantly, automate those marketing and

communication activities on concrete marketing sequences that could run inautopilot (also known as marketing sequences). The overall goals are to find,attract, and win new clients, nurture and retain those the company already has,entice former clients back into the fold, and reduce the costs of marketing andclient service. [1] Once simply a label for a category of software tools, today, itgenerally denotes a company-wide business strategy embracing all client-facingdepartments and even beyond. When an implementation is effective, people,processes, and technology work in synergy to increase profitability, and reduceoperational costs

Reasons for a correlation between two variables: Chance association, (therelationship is due to chance) or causative association (one variable causes theother).

The information given by a correlation coefficient is not enough to define thedependence structure between random variables. The correlation coefficientcompletely defines the dependence structure only in very particular cases, forexample when the distribution is a multivariate normal distribution . (Seediagram above.) In the case of elliptic distributions it characterizes the(hyper-)ellipses of equal density, however, it does not completely characterizethe dependence structure (for example, a multivariate t-distribution's degrees of freedom determine the level of tail dependence).

Distance correlation and Brownian covariance / Brownian correlation [8] [9] wereintroduced to address the deficiency of Pearson's correlation that it can be zero

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http://en.wikipedia.org/wiki/Marketinghttp://en.wikipedia.org/wiki/Multivariate_normal_distributionhttp://en.wikipedia.org/wiki/Distance_correlationhttp://en.wikipedia.org/wiki/Brownian_covariancehttp://en.wikipedia.org/wiki/#cite_note-7http://en.wikipedia.org/wiki/#cite_note-8http://en.wikipedia.org/wiki/Marketinghttp://en.wikipedia.org/wiki/Multivariate_normal_distributionhttp://en.wikipedia.org/wiki/Distance_correlationhttp://en.wikipedia.org/wiki/Brownian_covariancehttp://en.wikipedia.org/wiki/#cite_note-7http://en.wikipedia.org/wiki/#cite_note-8


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for dependent random variables; zero distance correlation and zero Browniancorrelation imply independence.

The correlation ratio is able to detect almost any functional dependency, or theentropy -based mutual information /total correlation which is capable of detectingeven more general dependencies. The latter are sometimes referred to as multi-moment correlation measures, in comparison to those that consider only 2ndmoment (pair wise or quadratic) dependence.

The polychoric correlation is another correlation applied to ordinal data that aimsto estimate the correlation between theorized latent variables.

One way to capture a more complete view of dependence structure is toconsider a copula between them.

Q 4. Briefly explain any two factors that affect the choice of asampling technique. What are the characteristics of a goodsample?

Ans.: The difference between non-probability and probability sampling is thatnon-probability sampling does not involve random selection and probabilitysampling does. Does that mean that non-probability samples aren'trepresentative of the population? Not necessarily. But it does mean that non-

probability samples cannot depend upon the rationale of probability theory. Atleast with a probabilistic sample, we know the odds or probability that we haverepresented the population well. We are able to estimate confidence intervals forthe statistic. With non-probability samples, we may or may not represent thepopulation well, and it will often be hard for us to know how well we've done so.In general, researchers prefer probabilistic or random sampling methods overnon probabilistic ones, and consider them to be more accurate and rigorous.However, in applied social research there may be circumstances where it is notfeasible, practical or theoretically sensible to do random sampling. Here, weconsider a wide range of non-probabilistic alternatives.

We can divide non-probability sampling methods into two broad types: Accidental or purposive .

Most sampling methods are purposive in nature because we usuallyapproach the sampling problem with a specific plan in mind. The most importantdistinctions among these types of sampling methods are the ones between thedifferent types of purposive sampling approaches.

Accidental, Haphazard or Convenience Sampling

One of the most common methods of sampling goes under the varioustitles listed here. I would include in this category the traditional "man on thestreet" (of course, now it's probably the "person on the street") interviewsconducted frequently by television news programs to get a quick (although non

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representative) reading of public opinion. I would also argue that the typical useof college students in much psychological research is primarily a matter of convenience. (You don't really believe that psychologists use college studentsbecause they believe they're representative of the population at large, do you?).In clinical practice, we might use clients who are available to us as our sample.In many research contexts, we sample simply by asking for volunteers. Clearly,the problem with all of these types of samples is that we have no evidence thatthey are representative of the populations we're interested in generalizing to --and in many cases we would clearly suspect that they are not.

Purposive Sampling

In purposive sampling, we sample with a purpose in mind. We usuallywould have one or more specific predefined groups we are seeking. For instance,have you ever run into people in a mall or on the street who are carrying aclipboard and who are stopping various people and asking if they could interviewthem? Most likely they are conducting a purposive sample (and most likely theyare engaged in market research). They might be looking for Caucasian femalesbetween 30-40 years old. They size up the people passing by and anyone wholooks to be in that category they stop to ask if they will participate. One of thefirst things they're likely to do is verify that the respondent does in fact meet thecriteria for being in the sample. Purposive sampling can be very useful forsituations where you need to reach a targeted sample quickly and wheresampling for proportionality is not the primary concern. With a purposivesample, you are likely to get the opinions of your target population, but you arealso likely to overweight subgroups in your population that are more readily

accessible.All of the methods that follow can be considered subcategories of purposive sampling methods. We might sample for specific groups or types of people as in modal instance, expert, or quota sampling. We might sample fordiversity as in heterogeneity sampling. Or, we might capitalize on informal socialnetworks to identify specific respondents who are hard to locate otherwise, as insnowball sampling. In all of these methods we know what we want -- we aresampling with a purpose.

Modal Instance SamplingIn statistics, the mode is the most frequently occurring value in a distribution. Insampling, when we do a modal instance sample, we are sampling the mostfrequent case, or the "typical" case. In a lot of informal public opinion polls, forinstance, they interview a "typical" voter. There are a number of problems withthis sampling approach. First, how do we know what the "typical" or "modal"case is? We could say that the modal voter is a person who is of average age,educational level, and income in the population. But, it's not clear that using theaverages of these is the fairest (consider the skewed distribution of income, forinstance). And, how do you know that those three variables -- age, education,income -- are the only or even the most relevant for classifying the typical voter?What if religion or ethnicity is an important discriminator? Clearly, modal

instance sampling is only sensible for informal sampling contexts.

Expert Sampling

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Expert sampling involves the assembling of a sample of persons with known ordemonstrable experience and expertise in some area. Often, we convene such asample under the auspices of a "panel of experts." There are actually tworeasons you might do expert sampling. First, because it would be the best wayto elicit the views of persons who have specific expertise. In this case, expertsampling is essentially just a specific sub case of purposive sampling. But theother reason you might use expert sampling is to provide evidence for thevalidity of another sampling approach you've chosen. For instance, let's say youdo modal instance sampling and are concerned that the criteria you used fordefining the modal instance are subject to criticism. You might convene anexpert panel consisting of persons with acknowledged experience and insightinto that field or topic and ask them to examine your modal definitions andcomment on their appropriateness and validity. The advantage of doing this isthat you aren't out on your own trying to defend your decisions -- you have someacknowledged experts to back you. The disadvantage is that even the expertscan be, and often are, wrong.

Quota SamplingIn quota sampling, you select people non-randomly according to some fixedquota. There are two types of quota sampling: proportional and non

proportional . In proportional quota sampling you want to represent the majorcharacteristics of the population by sampling a proportional amount of each. Forinstance, if you know the population has 40% women and 60% men, and thatyou want a total sample size of 100, you will continue sampling until you getthose percentages and then you will stop. So, if you've already got the 40women for your sample, but not the sixty men, you will continue to sample men

but even if legitimate women respondents come along, you will not sample thembecause you have already "met your quota." The problem here (as in muchpurposive sampling) is that you have to decide the specific characteristics onwhich you will base the quota. Will it be by gender, age, education race, religion,etc.?Non-proportional quota sampling is a bit less restrictive. In this method, youspecify the minimum number of sampled units you want in each category. Here,you're not concerned with having numbers that match the proportions in thepopulation. Instead, you simply want to have enough to assure that you will beable to talk about even small groups in the population. This method is the non-probabilistic analogue of stratified random sampling in that it is typically used toassure that smaller groups are adequately represented in your sample.

Heterogeneity SamplingWe sample for heterogeneity when we want to include all opinions or views, andwe aren't concerned about representing these views proportionately. Anotherterm for this is sampling for diversity . In many brainstorming or nominal groupprocesses (including concept mapping), we would use some form of heterogeneity sampling because our primary interest is in getting broadspectrum of ideas, not identifying the "average" or "modal instance" ones. Ineffect, what we would like to be sampling is not people, but ideas. We imagine

that there is a universe of all possible ideas relevant to some topic and that wewant to sample this population, not the population of people who have the ideas.Clearly, in order to get all of the ideas, and especially the "outlier" or unusualones, we have to include a broad and diverse range of participants.Roll No: 540911501 Page 12 of 22


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Heterogeneity sampling is, in this sense, almost the opposite of modal instancesampling.

Snowball SamplingIn snowball sampling, you begin by identifying someone who meets the criteriafor inclusion in your study. You then ask them to recommend others who theymay know who also meet the criteria. Although this method would hardly lead torepresentative samples, there are times when it may be the best methodavailable. Snowball sampling is especially useful when you are trying to reachpopulations that are inaccessible or hard to find. For instance, if you are studyingthe homeless, you are not likely to be able to find good lists of homeless peoplewithin a specific geographical area. However, if you go to that area and identifyone or two, you may find that they know very well whom the other homelesspeople in their vicinity are and how you can find them.

Characteristics of good Sample: The decision process is a complicated one. The researcher has to first identify the limiting factor or factors and must judiciously balance the conflicting factors. The various criteria governing thechoice of the sampling technique are:

1 1. Purpose of the Survey : What does the researcher aim at? If heintends to generalize the findings based on the sample survey to thepopulation, then an appropriate probability sampling method must beselected. The choice of a particular type of probability samplingdepends on the geographical area of the survey and the size and thenature of the population under study.

2 2. Measurability : The application of statistical inference theory requirescomputation of the sampling error from the sample itself. Onlyprobability samples allow such computation. Hence, where the researchobjective requires statistical inference, the sample should be drawn byapplying simple random sampling method or stratified randomsampling method, depending on whether the population is homogenousor heterogeneous.

3 3. Degree of Precision : Should the results of the survey be very precise,or could even rough results serve the purpose? The desired level of precision is one of the criteria for sampling method selection. Where ahigh degree of precision of results is desired, probability samplingshould be used. Where even crude results would serve the purpose(E.g., marketing surveys, readership surveys etc), any convenient non-random sampling like quota sampling would be enough.

45 4. Information about Population : How much information is available

about the population to be studied? Where no list of population and noinformation about its nature are available, it is difficult to apply aprobability sampling method. Then an exploratory study with non-probability sampling may be done to gain a better idea of the

population. After gaining sufficient knowledge about the populationthrough the exploratory study, an appropriate probability samplingdesign may be adopted.

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6 5. The Nature of the Population : In terms of the variables to bestudied, is the population homogenous or heterogeneous? In the caseof a homogenous population, even simple random sampling will give arepresentative sample. If the population is heterogeneous, stratifiedrandom sampling is appropriate.

7 6. Geographical Area of the Study and the Size of the Population :If the area covered by a survey is very large and the size of thepopulation is quite large, multi-stage cluster sampling would beappropriate. But if the area and the size of the population are small,single stage probability sampling methods could be used.

8 7. Financial Resources : If the available finance is limited, it maybecome necessary to choose a less costly sampling plan like multistagecluster sampling, or even quota sampling as a compromise. However, if the objectives of the study and the desired level of precision cannot beattained within the stipulated budget, there is no alternative but to giveup the proposed survey. Where the finance is not a constraint, aresearcher can choose the most appropriate method of sampling thatfits the research objective and the nature of population.

9 8. Time Limitation : The time limit within which the research projectshould be completed restricts the choice of a sampling method. Then,as a compromise, it may become necessary to choose less timeconsuming methods like simple random sampling, instead of stratifiedsampling/sampling with probability proportional to size; or multi-stage

cluster sampling, instead of single-stage sampling of elements. Of course, the precision has to be sacrificed to some extent.10 9. Economy : It should be another criterion in choosing the sampling

method. It means achieving the desired level of precision at minimumcost. A sample is economical if the precision per unit cost is high, or thecost per unit of variance is low. The above criteria frequently conflictwith each other and the researcher must balance and blend them toobtain a good sampling plan. The chosen plan thus represents anadaptation of the sampling theory to the available facilities andresources. That is, it represents a compromise between idealism andfeasibility. One should use simple workable methods, instead of undulyelaborate and complicated techniques.

Q 5. Select any topic for research and explain how you willuse both secondary and primary sources to gather therequired information.

Ans.: Primary Sources of Data

Primary sources are original sources from which the researcher directly collectsdata that has not been previously collected, e.g., collection of data directly bythe researcher on brand awareness, brand preference, and brand loyalty and

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other aspects of consumer behavior, from a sample of consumers byinterviewing them. Primary data is first hand information collected throughvarious methods such as surveys, experiments and observation, for thepurposes of the project immediately at hand.

The advantages of primary data are It is unique to a particular research studyIt is recent information, unlike published information that is alreadyavailable

The disadvantages are It is expensive to collect, compared to gathering information fromavailable sourcesData collection is a time consuming process

It requires trained interviewers and investigators

2 Secondary Sources of Data

These are sources containing data, which has been collected and compiled foranother purpose. Secondary sources may be internal sources, such as annualreports, financial statements, sales reports, inventory records, minutes of meetings and other information that is available within the firm, in the form of amarketing information system. They may also be external sources, such asgovernment agencies (e.g. census reports, reports of government departments),published sources (annual reports of currency and finance published by theReserve Bank of India, publications of international organizations such as theUN, World Bank and International Monetary Fund, trade and financial journals,etc.), trade associations (e.g. Chambers of Commerce) and commercial services(outside suppliers of information).

Methods of Data Collection: The researcher directly collects primary data from its original sources. In thiscase, the researcher can collect the required data precisely according to hisresearch needs and he can collect them when he wants and in the form that heneeds it. But the collection of primary data is costly and time consuming. Yet, for

several types of social science research, required data is not available fromsecondary sources and it has to be directly gathered from the primary sources.Primary data has to be gathered in cases where the available data isinappropriate, inadequate or obsolete. It includes: socio economic surveys, socialanthropological studies of rural communities and tribal communities, sociologicalstudies of social problems and social institutions, marketing research, leadershipstudies, opinion polls, attitudinal surveys, radio listening and T.V. viewingsurveys, knowledge-awareness practice (KAP) studies, farm managementstudies, business management studies etc.

There are various methods of primary data collection, including surveys, auditsand panels, observation and experiments.

1 Survey Research

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A survey is a fact-finding study. It is a method of research involving collection of data directly from a population or a sample at a particular time. A survey hascertain characteristics:

It is always conducted in a natural setting. It is a field study.It seeks responses directly from the respondents.

It can cover a very large population.It may include an extensive study or an intensive studyIt covers a definite geographical area.

A survey involves the following steps -Selection of a problem and its formulationPreparation of the research designOperation concepts and construction of measuring indexes and scalesSamplingConstruction of tools for data collectionField work and collection of dataProcessing of data and tabulationAnalysis of data

Reporting

There are four basic survey methods, which include:Personal interview

Telephone interviewMail survey andFax survey

2. Personal InterviewPersonal interviewing is one of the prominent methods of data collection. It maybe defined as a two-way systematic conversation between an investigator andan informant, initiated for obtaining information relevant to a specific study. Itinvolves not only conversation, but also learning from the respondents gestures,facial expressions and pauses, and his environment.Interviewing may be used either as a main method or as a supplementary one instudies of persons. Interviewing is the only suitable method for gatheringinformation from illiterate or less educated respondents. It is useful for collecting

a wide range of data, from factual demographic data to highly personal andintimate information relating to a persons opinions, attitudes, values, beliefs,experiences and future intentions. Interviewing is appropriate when qualitativeinformation is required, or probing is necessary to draw out the respondent fully.Where the area covered for the survey is compact, or when a sufficient numberof qualified interviewers are available, personal interview is feasible.Interview is often superior to other data-gathering methods. People are usuallymore willing to talk than to write. Once rapport is established, even confidentialinformation may be obtained. It permits probing into the context and reasons foranswers to questions.Interview can add flesh to statistical information. It enables the investigator tograsp the behavioral context of the data furnished by the respondents. It permitsthe investigator to seek clarifications and brings to the forefront those questions,

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which for some reason or the other the respondents do not want to answer.Interviewing as a method of data collection has certain characteristics. They are:

The participants the interviewer and the respondent arestrangers; hence, the investigator has to get himself/herself introduced to therespondent in an appropriate manner.

The relationship between the participants is a transitory one. Ithas a fixed beginning and termination points. The interview proper is a fleeting,momentary experience for them.

The interview is not a mere casual conversational exchange,but a conversation with a specific purpose, viz., obtaining information relevant toa study.

The interview is a mode of obtaining verbal answers toquestions put verbally.

The interaction between the interviewer and the respondentneed not necessarily be on a face-to-face basis, because the interview can alsobe conducted over the telephone.

Although the interview is usually a conversation between twopersons, it need not be limited to a single respondent. It can also be conductedwith a group of persons, such as family members, or a group of children, or agroup of customers, depending on the requirements of the study.

The interview is an interactive process. The interactionbetween the interviewer and the respondent depends upon how they perceiveeach other.

The respondent reacts to the interviewers appearance,behavior, gestures, facial expression and intonation, his perception of the thrustof the questions and his own personal needs. As far as possible, the interviewershould try to be closer to the social-economic level of the respondents.

The investigator records information furnished by therespondent in the interview. This poses a problem of seeing that recording doesnot interfere with the tempo of conversation.

Interviewing is not a standardized process like that of achemical technician; it is rather a flexible, psychological process.

3 Telephone Interviewing Telephone interviewing is a non-personalmethod of data collection. It may be used as a major method or as asupplementary method. It will be useful in the following situations:

1. When the universe is composed of those persons whose names are listedin telephone directories, e.g. business houses, business executives,doctors and other professionals

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2. When the study requires responses to five or six simple questions, e.g. aradio or television program survey.

3. When the survey must be conducted in a very short period of time,provided the units of study are listed in the telephone directory.

4. When the subject is interesting or important to respondents, e.g. a surveyrelating to trade conducted by a trade association or a chamber of commerce, a survey relating to a profession conducted by the concernedprofessional association.

5. When the respondents are widely scattered and when there are many callbacks to make.

4 Group Interviews A group interview may be defined as a method of collecting primary data in which a number of individuals with a commoninterest interact with each other. In a personal interview, the flow of information is multi dimensional. The group may consist of about six to eightindividuals with a common interest. The interviewer acts as the discussionleader. Free discussion is encouraged on some aspect of the subject understudy. The discussion leader stimulates the group members to interact witheach other. The desired information may be obtained through self-administered questionnaire or interview, with the discussion serving as aguide to ensure consideration of the areas of concern. In particular, theinterviewers look for evidence of common elements of attitudes, beliefs,intentions and opinions among individuals in the group. At the same time, he

must be aware that a single comment by a member can provide importantinsight. Samples for group interviews can be obtained through schools, clubsand other organized groups.

5 Mail Survey The mail survey is another method of collecting primarydata. This method involves sending questionnaires to the respondents with arequest to complete them and return them by post. This can be used in thecase of educated respondents only. The mail questionnaires should besimple so that the respondents can easily understand the questions andanswer them. It should preferably contain mostly closed-ended and multiplechoice questions, so that it could be completed within a few minutes. Thedistinctive feature of the mail survey is that the questionnaire is self-administered by the respondents themselves and the responses arerecorded by them and not by the investigator, as in the case of personalinterview method. It does not involve face-to-face conversation between theinvestigator and the respondent. Communication is carried out only in writingand this requires more cooperation from the respondents than verbalcommunication. The researcher should prepare a mailing list of the selectedrespondents, by collecting the addresses from the telephone directory of theassociation or organization to which they belong. The following proceduresshould be followed - a covering letter should accompany a copy of the

questionnaire. It must explain to the respondent the purpose of the studyand the importance of his cooperation to the success of the project. Anonymity must be assured. The sponsors identity may be revealed. However, when such information may bias the result, it is not desirable to

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reveal it. In this case, a disguised organization name may be used. A self-addressed stamped envelope should be enclosed in the covering letter.

1 After a few days from the date of mailing the questionnaires to the respondents, the researcher can expect the return of completed ones fromthem. The progress in return may be watched and at the appropriate stage,follow-up efforts can be made.

The response rate in mail surveys is generally very low in developing countrieslike India. Certain techniques have to be adopted to increase the response rate.

They are:

1 1. Quality printing: The questionnaire may be neatly printed on qualitylight colored paper, so as to attract the attention of the respondent.

23 2. Covering letter: The covering letter should be couched in a pleasant

style, so as to attract and hold the interest of the respondent. It mustanticipate objections and answer them briefly. It is desirable to addressthe respondent by name.

45 3. Advance information: Advance information can be provided to potential

respondents by a telephone call, or advance notice in the newsletter of theconcerned organization, or by a letter. Such preliminary contact withpotential respondents is more successful than follow-up efforts.

6

7 4. Incentives: Money, stamps for collection and other incentives are alsoused to induce respondents to complete and return the mail questionnaire.

8 5. Follow-up-contacts: In the case of respondents belonging to anorganization, they may be approached through someone in thatorganization known as the researcher.

910 6. Larger sample size: A larger sample may be drawn than the estimated

sample size. For example, if the required sample size is 1000, a sample of 1500 may be drawn. This may help the researcher to secure an effectivesample size closer to the required size.

Q 6. Case Study: You are engaged to carry out a marketsurvey on behalf of a leading Newspaper that is keen toincrease its circulation in Bangalore City, in order toascertain reader habits and interests. Develop a title for thestudy; define the research problem and the objectives orquestions to be answered by the study.

Ans.: Title: Newspaper reading choices

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Research problem: A research problem is the situation that causes theresearcher to feel apprehensive, confused and ill at ease. It is the demarcationof a problem area within a certain context involving the WHO or WHAT, theWHERE, the WHEN and the WHY of the problem situation.

There are many problem situations that may give rise to research. Threesources usually contribute to problem identification. Own experience or theexperience of others may be a source of problem supply. A second source couldbe scientific literature. You may read about certain findings and notice that acertain field was not covered. This could lead to a research problem. Theoriescould be a third source. Shortcomings in theories could be researched.

Research can thus be aimed at clarifying or substantiating an existing theory, atclarifying contradictory findings, at correcting a faulty methodology, atcorrecting the inadequate or unsuitable use of statistical techniques, atreconciling conflicting opinions, or at solving existing practical problems

Types of questions to be asked :For more than 35 years, the news aboutnewspapers and young readers has been mostly bad for the newspaper industry.Long before any competition from cable television or Nintendo, Americannewspaper publishers were worrying about declining readership among theyoung.

As early as 1960, at least 20 years prior to Music Television (MTV) or theInternet, media research scholars1 began to focus their studies on young adultreaders' decreasing interest in newspaper content. The concern over a declining

youth market preceded and perhaps foreshadowed today's fretting over marketpenetration. Even where circulation has grown or stayed stable, there is risingconcern over penetration, defined as the percentage of occupied households in ageographic market that are served by a newspaper.2 Simply put, populationgrowth is occurring more rapidly than newspaper readership in mostcommunities.

This study looks at trends in newspaper readership among the 18-to-34 agegroup and examines some of the choices young adults make when readingnewspapers.

One of the underlying concerns behind the decline in youth newspaper readingis the question of how young people view the newspaper. A number of studiesexplored how young readers evaluate and use newspaper content.

Comparing reader content preferences over a 10-year period, Gerald Stone and Timothy Boudreau found differences between readers ages 18-34 and those 35-plus.16 Younger readers showed increased interest in national news, weather,sports, and classified advertisements over the decade between 1984 and 1994,while older readers ranked weather, editorials, and food advertisements higher.Interest in international news and letters to the editor was less among younger

readers, while older readers showed less interest in reports of births, obituaries,and marriages.

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David Atkin explored the influence of telecommunication technology onnewspaper readership among students in undergraduate media courses.17 Hereported that computer-related technologies, including electronic mail andcomputer networks, were unrelated to newspaper readership. The study foundthat newspaper subscribers preferred print formats over electronic. In a study of younger, school-age children, Brian Brooks and James Kropp found thatelectronic newspapers could persuade children to become news consumers, butthat young readers would choose an electronic newspaper over a printed one.18

In an exploration of leisure reading among college students, Leo Jeffres andAtkin assessed dimensions of interest in newspapers, magazines, and books,19exploring the influence of media use, non-media leisure, and academic major onnewspaper content preferences. The study discovered that overall newspaperreadership was positively related to students' focus on entertainment, job /travel information, and public affairs. However, the students' preference forreading as a leisure-time activity was related only to a public affairs focus.Content preferences for newspapers and other print media were related. Theresearchers found no significant differences in readership among variousacademic majors, or by gender, though there was a slight correlation betweenage and the public affairs readership index, with older readers more interestedin news about public affairs.

Methodology

Sample

Participants in this study (N=267) were students enrolled in 100- and 200-levelEnglish courses at a midwestern public university. Courses that comprise theframework for this sample were selected because they could fulfill basic studiesrequirements for all majors. A basic studies course is one that is listed within thecore curriculum required for all students. The researcher obtained permissionfrom seven professors to distribute questionnaires in the eight classes duringregularly scheduled class periods. The students' participation was voluntary; twostudents declined. The goal of this sampling procedure was to reach a cross-section of students representing various fields of study. In all, 53 majors wererepresented.

Of the 267 students who participated in the study, 65 (24.3 percent) were maleand 177 (66.3 percent) were female. A total of 25 participants chose not todivulge their genders. Ages ranged from 17 to 56, with a mean age of 23.6years. This mean does not include the 32 respondents who declined to give theirages. A total of 157 participants (58.8 percent) said they were of the Caucasianrace, 59 (22.1 percent) African American, 10 (3.8 percent) Asian, five (1.9percent) African/Native American, two (.8 percent) Hispanic, two (.8 percent)Native American, and one (.4 percent) Arabic. Most (214) of the students wereenrolled full time, whereas a few (28) were part-time students. The class rankbreakdown was: freshmen, 45 (16.9 percent); sophomores, 15 (5.6 percent);

juniors, 33 (12.4 percent); seniors, 133 (49.8 percent); and graduate students,16 (6 percent).

Procedure

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After two pre-tests and revisions, questionnaires were distributed and collectedby the investigator. In each of the eight classes, the researcher introducedherself to the students as a journalism professor who was conducting a study onstudents' use of newspapers and other media. Each questionnaire included acover letter with the researcher's name, address, and phone number. Theresearcher provided pencils and was available to answer questions if anyoneneeded further assistance. The average time spent on the questionnaires was 20minutes, with some individual students taking as long as an hour. Approximatelysix students asked to take the questionnaires home to finish. They returned thequestionnaires to the researcher's mailbox within a couple of day.

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mb0034(research methodology)

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