MB0050 Research Methodology Fall 10

RESEARCH METHODOLOGY MB 0050

Name: Rajesh Kumar Roll number: 520932980 Learning centre: 03036 Subject: MB 0050-

RESEARCH METHODOLOGY

Assignment No.: Set 1 Date of submission at learning centre:

MB0050-Research Methodology

ASSIGNMENTS Subject code: MB0050 (4 credits) Marks 60 SUBJECT NAME: RESEARCH METHODOLOGY Note: Each Question Question carries carries 10 marks Q1. Give Give exampl examples es of specif specific ic situat situation ionss that that would would call call for for the the follo followin wing g types types of rese resear arch ch,, expl explai aini ning ng why why – a) Expl Explor orat ator ory y rese resear arch ch b) Desc Descri ript ptiv ivee rese resear arch ch c) Diagnostic research d) Evaluation research. Ans: a) Exploratory research- It is also known as formulative research. It is preliminary study of an unfamiliar problem about which the r esearcher has little or no knowledge. It is illstructured and much less focused on pre-determined objectives. It usually takes the form of a pilot study. The purpose of this research may be to generate new ideas, or to increase the researcher’s familiarity with the problem or to make a precise formulation of the problem or to gather information for clarifying concepts or to determine whether it is feasible to attempt the study. Katz conceptualizes two levels of exploratory studies. “At the first level is the discov discovery ery of the signif significa icant nt variab variable le in the situat situation ions; s; at the second second,, the discov discovery ery of relationships between variables.”

It is a type of research of research conducted for a problem that has not been clearly defined. Exploratory research helps determine the best research design, data collection collection method and selection of subj subjec ects ts.. It shou should ld draw draw defi defini niti tive ve conc conclu lusi sion onss only only with with extre extreme me caut cautio ion. n. Give Given n its its fundamental nature, exploratory research often concludes that a perceived problem does not actually exist. Exploratory research often relies on secondary research such as reviewing available literature and/or and/or data, data, or qualit qualitati ative ve approa approache chess such such as inform informal al discus discussio sions ns with with consum consumers ers,, employ employees ees,, manage managemen mentt or compet competito itors, rs, and more more formal formal approa approache chess throug through h in-dep in-depth th interviews, focus groups groups,, projective methods, case studies studies or or pilot pilot studies studies.. The Internet allows for research methods that are more interactive in nature. For example, RSS feeds efficiently supply researchers with up-to-date information; major search major search engine search results may be sent by email to researchers by services such as Google Alerts; Alerts; comprehensive search results are tracked over lengthy periods of time by services such as Google Trends; Trends; and websites may be created to attract worldwide feedback on any subject. The results of exploratory research are not usually useful for decision-making by themselves, but but they they can provid providee signif significa icant nt insigh insightt into into a given given situat situation ion.. Althou Although gh the results results of qualitative research can give some indication as to the "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.

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b) Descriptive research- It is a fact-finding fact-finding investigation investigation with adequate adequate interpretation. interpretation. It is the simplest type of research. It is more specific than an exploratory research. It aims at identifyin identifying g the various characteristics characteristics of a community community or institutio institution n or problem problem under study and also aims at a classification of the range of elements comprising the subject matter of study. It contributes to the development of a young science and useful in verifying focal concepts through empirical observation. It can highlight important methodological aspects of data collection and interpretation. The information obtained may be useful for prediction about about areas areas of social social life life outsid outsidee the boundarie boundariess of the research. research. They are valuab valuable le in providing facts needed for planning social action program.

It also known as statistical research , describes data and characteristics about the population the population or phenomenon being studied. Descriptive research answers the questions who, what , where, when and how... Although the data description is factual, accurate and systematic, the research cannot describe what what caused caused a situat situation ion.. Thus, Thus, Descripti Descriptive ve researc research h cannot cannot be used used to create create a causal another. In other words, descriptive descriptive research can be relationship , where one variable affects another. said to have a low requirement for internal for internal validity. validity. The description is used for frequencies, averages and other statistical calculations. Often the best approach, prior to writing descriptive research, is to conduct a survey investigation. Qualitative Qualitative research research often has the aim of description and researchers may follow-up with examinations 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 there are always restrictions to that. Your research must have an impact to the lives of the people around you. For example, finding the most frequent disease that affects the children of a town. The reader of the research will know what to do to prevent that disease thus, more people will live a healthy life. c) Diagnosti Diagnosticc research research-- It is similar to descriptive study but with a different focus. It is directed directed towards towards discoverin discovering g what is happening, happening, why it is happening happening and what can be done about. It aims at identifying the causes of a problem and the possible solutions for it. It may also be concerned with discovering and testing whether 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. d) Evaluatio Evaluation n research research-- It is a type type of appl applie ied d rese resear arch ch.. It is made made for for asse assess ssin ing g the the effectiveness of social or economic programmes implemented or for assessing the impact of developmental projects on the development of the project area. It is thus directed to assess or appraise the quality and quantity of an activity and its performance, and to specify its attributes and conditions required for its success. It is concerned with causal relationships and is more actively guided by hypothesis. It is concerned also with change over time. Q2.In the context of hypothesis testing, briefly explain the difference between a) Null and alternative hypothesis b) Type 1 and type 2 errors c) Two tailed and one tailed test d) Parametric and non parametric tests.

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Ans: a) Null and alternative hypothesis - In the context of statistical analysis, we often talk null and alternative hypothesis. If we are to compare method A with method B about its superiority and if we proceed on the assumption that both methods are equally good, then this assumption is termed as null hypothesis. As against this, we may think that the method A is superior, it is alternative hypothesis. Symbolically presented as:

Null hypothesis = H0 and Alternative hypothesis = Ha Suppose we want to test the hypothesis that the population mean is equal to the hypothesis mean (µ H0) = 100. Then we would say that the null hypotheses are that the population mean is equal to the hypothesized mean 100 and symbolical we can express as: H0: µ= µ H0=100

If our our samp sample le resul results ts do not not supp suppor ortt thes thesee null null hypo hypoth thes eses es,, we shou should ld conc conclu lude de that that some someth thin ing g else else is true true.. What What we conc conclu lude de reje rejecti cting ng the the null null hypo hypoth thes esis is is know known n as alternative hypothesis. If we accept H0, then we are rejecting Ha and if we reject H0, then we are are accep accepti ting ng Ha. Ha. For For H0: H0: µ= µ H0=1 H0=100 00,, we may may cons consid ider er thre threee poss possib ible le alter alterna nati tive ve hypotheses as follows: b) Type 1 and type 2 errors - In the context of testing of hypothesis there are basically two types of errors that researchers make. We may reject H0 when H0 is true & we may accept H0 when it is not true. The former is known as Type I & the later is known as Type II. In othe otherr word words, s, Type Type I erro errorr mean mean reje rejecti ction on of hypo hypoth thes esis is whic which h shou should ld have have been been accepte accepted d & Type Type II error error means means accept accepting ing of hypoth hypothesi esiss which which should should have have been been rejected. Type I error is donated by á (alpha), also called as level of significance of test; and Type II error is donated by (beta).

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The probability of Type I error is usually determined in advance and is understood as the level of significance of testing the hypothesis. If type I error is fixed at 5%, it means there are about chances in 100 that we will reject H0 when H0 is true. We can control type I error just by fixing it at a lower level. For instance, 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 probability of committing committing type II error increases. increases. Both types of errors can not be reduced reduced simultaneo simultaneously usly.. There is a tradeoff in business situations, decision-makers decide the appropriate level of type I error by examining the costs of penalties attached to both types of errors. If type I error involves time & trouble of reworking a batch of chemicals that should have been accepted, where as type II error means taking a chance that an entire group of users of this chemicals compound will be poisoned, then in such a situation one should prefer a type I error to a type II error means taking a chance that an entire group of users of this chemicals compound will be poisoned, then in such a situation one should prefer a type II error. As a result one must set very high level for type I error in one’s testing techniques of a given hypothesis. Hence, in testing of hypothesis, one must make all possible effort to strike an adequate balance between Type I & Type II error. c) Two tailed tailed and 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 significantly higher or lower than the hypnotized value of the mean of the population. Such a test inappropriate when we have If

significance level is % and the two-tailed test to be applied, the probability of the rejection area will be 0.05 (equally split on both tails of curve as 0.025) and that of the acceptance region will be 0.95. If we take µ = 100 and if our sample mean deviates significantly from µ, in that case we shall accept the null hypothesis. But there are situations when only one-tailed test is considered appropriate. A one-tailed test would be used when we are to test, say, whether the population mean in either lower than or higher than some hypothesized value. d) Parametric and non parametric tests - The hypothesis testing determines the validity of the assumption (technically described as null hypothesis) with a view to choose between the conflicting hypotheses about the value of the population hypothesis about the value of the population of a population parameter. Hypothesis testing helps to secede on the basis of a samp sample le data data,, wheth whether er a hypo hypoth thes esis is abou aboutt the the popu popula lati tion on is like likely ly to be true true or fals false. e. Statisticians have developed several tests of hypothesis (also known as tests of significance) for the purpose of testing of hypothesis which can be classified as: • •

Parametric tests or standard tests of hypothesis ; Non Parametric test or distribution – free test of the hypothesis.

Parametric tests usually assume certain properties of the parent population from which we draw samples. Assumption like observations come from a normal population, sample size is large, assumptions about the population parameters like mean, variants etc must hold good before parametric test can be used. But there are situation when the researcher cannot or does

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not want to make assumptions. In such situations we use statistical methods for testing hypothesis which are called non parametric tests because such tests do not depend on any assumption about the parameters of parent population. Besides, most non-parametric test assum assumes es only only nomina nominall or origin original al data, data, where where as parame parametric tric test test requir requiree measur measureme ement nt equivalent to at least an interval scale. As a result non-parametric test needs more observation than a parametric test to achieve the same size of Type I & Type II error. Q 3. Explain the difference between a causal relationship and correlation, with an example of each. What are the possible reasons for a correlation between two variables? Ans: Economic and business variables are related. For instance, demand and supply of a commodity is related to its price. Demand for a commodity increases as price falls. Demand for a commodity decreases as its price rises. We say demand and price are inversely related or negatively correlated. But sellers supply more of a commodity when its price rises. Supply of the commodity decreases when its price falls. We say supply and price are directly related or positi positivel vely y co-rela co-related ted.. Thus, Thus, correla correlatio tion n indicat indicates es the relatio relationsh nship ip betwee between n two such such variables variables in which changes changes in the value of one variable is accompanies accompanies with a change change in the value of other variable.

According to L.R. Connor, “if two or more quantities vary in sympathy so that movements in the one tend to be accompanied by corresponding movements in the other(s) they are said to be correlated”. W.I. King defined “Correlation means that between two series or groups of data, there exists some casual connection”. The definitions make it clear that the term correlation refers to the study of relationship betw betwee een n two two or more more vari variab able les. s. Corre Correla lati tion on is a stat statis isti tical cal devi device ce,, whic which h stud studie iess the the relationship between two variables. If two variables are said to be correlated, change in the value of one variable result in a corresponding change in the value of other variable. Heights and weights of a group of people, age of husbands and wives etc., are examples of bi-variant data that change together. Correlation and Causation Although, the term correlation is used in the sense of mutual dependence of two or more variable, it is not always necessary that they have cause and effect relation. Even a high degree of correlation between two variables does not necessarily necessarily indicate a cause and effect relationship between them. Reasons for a correlation correlation between two variables: Correlation between two variables can be due to following reasons:-

1. Cause and effect relationship relationship:: Heat and temperature temperature are cause and effect variable. Heat is the cause of temperature. Higher the heat, higher will be the temperature. 2. Both the correlated variables are being affected by a third variable. For instance, price of rice and price of sugar are affected by rainfall. Here there may not be any cause and effect relation between price of rice and price of sugar.

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3. Related variable may be mutually affecting each other so that none of them is either a cause or an effect. Demand may be the result of price. There are cases when price rise due to increased demand. 4. The correlation may be due to chance. For instance, a small sample may show correlation between between wages and productivity. productivity. That is, higher wage leading leading to lower productiv productivity. ity. In real life it need not be true. Such correlation is due to chance. 5. There might be a situation of nonsense or spurious correlation between two variables. For instance, relationship between number of divorces and television exports may be correlated. There cannot be any relationship between divorce and exports of television. The above points make it clear that correlation is only a statistical relationship and it does not necessarily signify a cause and effect relationship between the variables. Q 4. Briefly explain any two factors that affect the choice of a sampling technique. What are the characteristics of a good sample? Ans: A part of the population is known as sample. The method consisting of the selecting for study, a portion of the ‘universe’ with a view to draw conclusions about the ‘universe’ or ‘population’ is known as sampling. A statistical sample ideally purports to be a miniature model or replica of the collectivity or the population constituted of all the items that the study should principally encompass, that is, the items which potentially hold promise of affording information relevant to the purpose of a given research.

Sampling helps in time and cost saving. It also helps in checking their accuracy. But on the other hand it demands exercise of great care caution; otherwise the results obtained may be incorrect or misleading. Sampling Procedure- The decision process of sampling is complicated one. The researcher has to first identity the limiting factor or factors and must judiciously balance the conflicting factors. The two among various criteria governing the choice of the sampling technique:

intends to generalize (1) Purpose of of th the Su Survey: What does the researcher aim at? If he intends the findings based on the sample survey to the population, then an appropriate probability sampling method must be selected. The choice of a particular type of probability sampling depends on the geographical area of the survey and the size and the nature of the population under study. (2) Measurability: The application of statistical inference theory requires computation of the sampli sampling ng error error from from the sample sample itself. itself. Probab Probabili ility ty sample sampless allow allow such such comput computati ation. on. Hence, where the research objective requires statistical inference, the sample should be drawn by applyi applying ng simple simple random random sampli sampling ng method method or strati stratified fied random random sampli sampling ng method method,, depending on whether the population is homogenous or heterogeneous. Factors that affect choice of sample The size of the population : If the population to be studied is quite large, sampling is warranted. However, the size is a relative matter. Whether a population is large or small depends upon the nature of the study, the purpose for which it is undertaken, and the time and other resources available for it. •

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Amount of funds budgeted for the study : Sampling is opted when the amount of money budgeted is smaller than the anticipated cost of census survey. Facilities: The extent of facilities available – staff, access to computer facility and accessibility to population elements – in another factor to be considered in deciding to samp sample le or not. not. When When the the avai availa labil bilit ity y of thes thesee facil facilit ities ies is limi limited ted,, samp sampli ling ng is preferable. Time: The time limit within the study should be completed in another important factor to be considered in deciding the question of sample survey. This, in fact, is a primary reason for using sampling by academic and marketing researchers.

Characteristics Characteristics of a Good Sample The characteristics of a good sample are described below: Representative Representative ness: a sample must be representative of the population. Probability sampling technique yield representative sample. Accuracy: accuracy is defined as the degree to which bias is absent from the sample. An accurate sample is the one which exactly represents the population. Precision: the sample must yield precise estimate. Precision is measured by standard error. Size: a good sample must be adequate in size in order to be reliable. •

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Q 5. Select any topic for research and explain how you will use both secondary and primary sources to gather the required information.

performin ming g researc research h on the literac literacy y levels levels among among famili families, es, the primar primary y and Ans: For perfor secondary sources of data can be used very effectively. More specifically the primary sources of data collection is suggested in this regard. Because personal data or data related to human beings consist of: 1.

2.

3.

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Demographic and socio-economic characteristics of individuals: Age, sex, race, social class, religion, religion, marital marital status, status, education, occupation occupation income, income, family size, location of the household life style etc. Behavioral variables: Attitudes, opinions, awareness, knowledge, practice, intentions, etc. Organizational data consist of data relating to an organizations origin, ownership, objectives, resources, functions, performance and growth. Territ Territori orial al data data are related related to geo-ph geo-physi ysical cal charac characteri teristi stics, cs, resour resource ce endowm endowment ent,, 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 on imagin imaginatio ation n or guess guess work work cannot cannot provid providee correct correct answer answerss to researc research h questi questions ons.. The relevance, 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 the facts and figures required for constructing measurement scales and tables, which are analyzed with with statis statistic tical al techniq techniques ues.. Inferen Inferences ces on the result resultss of statis statistica ticall analys analysis is and tests tests of signif significa icance nce provid providee the answers answers to researc research h questi questions ons.. Thus, Thus, the scient scientific ific proces processs of measurements, analysis, testing and inferences depends on the availability of relevant data and 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 sources and (b) secondary sources. Primary Sources of Data

Primary sources are original sources from which the researcher directly collects data that have not been previously collected e.g.., collection of data directly by the researcher on brand awareness, brand preference, brand loyalty and other aspects of consumer behavior from a sample of consumers by interviewing them,. Primary data are first hand information collected through 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 obtain • It is time consuming • It 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 required date precisely precisely according to his research 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 time consuming. Yet, for several types of social science research required data are not available from 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 data have to be gathered. They include: socio economic surveys, social anthropological studies of rural communities and tribal communities, sociological studies of social problems and social instit instituti utions ons.. Marketi Marketing ng researc research, h, leader leadershi ship p studie studies, s, opinio opinion n polls, polls, attitud attitudina inall survey surveys, s, readership, radio listening and T.V. viewing surveys, knowledge-awareness practice (KAP) studies, farm managements studies, business management studies etc. There are various methods of data collection. A ‘Method’ is different from a ‘Tool’ while a method refers 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

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These These are sources sources containi containing ng data data which which have have been been collect collected ed and compiled compiled for anothe another r purpo purpose. se. The second secondary ary sourc sources es consis consists ts of readily readily compen compendia dia and alread already y compil compiled ed statistical statements and reports whose data may be used by researchers for their studies e.g., census reports, annual reports and financial statements of companies, Statistical statement, Reports of Government Departments, Annual reports of currency and finance published by the Reserve Bank of India, Statistical statements relating to Co-operatives and Regional Banks, published by the NABARD, Reports of the National sample survey Organization, Reports of trade associations, publications of international organizations such as UNO, IMF, World Bank, ILO, WHO, etc., Trade and Financial journals newspapers etc. Secondary sources consist of not only published records and reports, but also unpublished records. The latter category includes various records and registers maintained by the firms and organi organizati zations ons,, e.g., e.g., accoun accountin ting g and financ financial ial records records,, person personnel nel records records,, regist register er of members, minutes of meetings, inventory records etc. Features of Secondary Sources Though secondary sources are diverse and consist of all sorts of materials, they have certain common characteristics.

First, they are readymade and readily available, and do not require the trouble of constructing tools and administering them. Second, they consist of data which a researcher has no original control over collection and classification. Both the form and the content of secondary sources are shaped by others. Clearly, this is a feature which can limit the research value of secondary sources. Finally, secondary sources are not limited in time and space. That is, the researcher using them need not have been present when and where they were gathered. Use of Secondary Data The second data may be used in three ways by a researcher. First, some specific information from from second secondary ary sources sources may be used used for referen reference ce purpos purpose. e. For exampl example, e, the general general statistical information in the number of co-operative credit societies in the country, their coverage of villages, their capital structure, volume of business etc., may be taken from published reports and quoted as background information in a study on the evaluation of performance of cooperative credit societies in a selected district/state.

Second, Second, secondary data may be used as bench marks against which the findings findings of research research may be tested, e.g., the findings of a local or regional survey may be compared with the national averages; the performance indicators of a particular bank may be tested against the corresponding indicators of the banking industry as a whole; and so on. Finally, secondary data may be used as the sole source of information for a research project. Such studies as securities Market Behaviour, Financial Analysis of companies, Trade in credit allocation in commercial banks, sociological studies on crimes, historical studies, and the like, depend primarily on secondary data. Year books, statistical reports of government departments, report of public organizations of Bureau of Public Enterprises, Censes Reports etc, serve as major data sources for such research studies. Advantages of Secondary Data

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Secondary sources have some advantages: Secondary data, if available can be secured quickly and cheaply. Once their source of documents and reports are located, collection of data is just matter of desk work. Even the tediousness of copying the data from the source can now be avoided, thanks to Xeroxing facilities. Wider geographical area and longer reference period may be covered without much cost. Thus, the use of secondary data extends the researcher’s space and time reach. The use use of seco secon ndary ary data data broad roaden enss the the data ata base base from from whic which h scien cienti tifi ficc generalizations can be made. Environmental and cultural settings are required for the study. • The use of secondary data enables a researcher to verify the findings bases on primary data. It readily meets the need for additional empirical support. The researcher need not wait the time when additional primary data can be collected. •

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Disadvantages 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. The definitions definitions adopted by those 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 need to 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 are published tow or three years later after compilation, and no new figures will be available for 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 primarily on proximity. For example, most of the unpublished official records and compilation compilationss are located in the capital city, and they are not within the easy reach of researchers based in far off places. •

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Q6. Case Study: You are engaged to carry out a market survey on behalf of a leading Newspa Newspaper per that is keen keen to increa increase se its circul circulati ation on in Bangal Bangalore ore City, in order order to ascertain reader habits and interests. Develop a title for the study; define the research problem and the objectives or questions to be answered by the study. Ans: Generally, there is a significant relationship between the race or ethnic group and the language medium of the newspapers. Generally, Kannada newspapers are mostly read by the kannad kannadiga igass respon responden dents, ts, Tamil Tamil newspa newspaper perss by the tamili tamilians ans etc. Howeve However, r, there there is no significant relationship in the readership of English newspapers whereby they are read by all the ethnic groups. Title: Reader’s habits and interests in Bangalore Research Problem: To ascert ascertain ain the reader reader habits habits and interests interests and to increas increasee news news paper paper circul circulati ation on in Bangalore City. Objectives or questions to be answered:

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1. Have you read an entire book in the last 12 months? a. Yes. b. No. 2. How much time do you spend reading web pages each day? a. I don’t read web pages. b. Less than two hours. c. Two to four hours. d. Five or more hours. 3. Where do you read? Check all that apply. a. In school. b. On the bus. c. In a car or truck. d. In bed. e. At the computer. f. In the bathroom. g. In the kitchen or family room. h. At the library. 4. Have you ever pretended that you read a book when you hadn’t? a. Yes. b. No. 5. Why do you usually read a book? a. Because I think I should. b. Because it was assigned to me. c. Because I am interested in the topic or author. d. I don’t read books. 6. Have you ever pretended that you read a web page when you hadn’t? a. Yes. b. No. 7. What is the last book that you read? If you haven’t read a book, write “Not Applicable.” 8. Is being able to read is important? a. Yes. b. No.

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MB0050 Research Methodology Fall 10

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