mba mb 0050 set 1 research methodology

8/3/2019 Mba Mb 0050 Set 1 Research Methodology

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Master of Business Administration

Semester IIIMB0050

Research Methodology- 4 Credits(Book ID: B1206)

Assignment Set- 1 (60 Marks)Note: Each question carries 10 Marks. Answer all the questionsQ.1 a) Differentiate between nominal, ordinal, interval and ratioscales, with an example of each.b) What are the purposes of measurement in social science

research?Ans. (a)Nominal, ordinal, interval and ratio scales are the levels of

measurement.

1. Nominal MeasurementThe level of measurement consists in assigning numerals or symbols to

different categories of a variable. The example of male and female

applicants to an MBA program mentioned earlier is an example of

nominal measurement. The numerals or symbols are just labels and have

no quantitative value. The number of cases under each category arecounted. Nominal measurement is therefore the simplest level of

measurement. It does not have characteristics such as order, distance or

arithmetic origin.

2. Ordinal MeasurementIn this level of measurement, persons or objects are assigned numerals

which indicate ranks with respect to one or more properties, either in

ascending or descending order.

ExampleIndividuals may be ranked according to their socio-economic class,

which is measured by a combination of income, education, occupation and

wealth. The individual with the highest score might be assigned rank 1, the

next highest rank 2, and so on or vice versa.

The numbers in this level of measurement indicate only rank order and

not equal distance or absolute quantities. This means that the distance


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between ranks 1 and 2 is not necessarily equal to the distance between

ranks 2 and 3.

Ordinal scales may be constructed using rank order, rating and paired

comparisons. Variables that lend themselves to ordinal measurement

include preference, ratings of organizations and economic status. Statistical

techniques that are commonly used to analyze ordinal scale data are the

median and rank order correlation coefficients.

3. Interval MeasurementThis level of measurement is more powerful than the nominal and ordinal

levels of measurement, since it has one additional characteristic equality

of distance. However, it does not have an origin or a true zero. This

implies that it is not possible to multiply or divide the numbers on an

interval scale.

ExampleThe Centigrade or Fahrenheit temperature gauge is an example of the

interval level of measurement. A temperature of 50 degrees is exactly 10

degrees hotter than 40 degrees and 40 degrees cooler than 60 degrees.

Since interval scales are more powerful than nominal or ordinal scales,

they also lend themselves to more powerful statistical techniques, such asstandard deviation, product moment correlation and t tests and F tests

of significance.

4. Ratio MeasurementThis is the highest level of measurement and is appropriate when

measuring characteristics which have an absolute zero point. This level of

measurement has all the 3 characteristics order, distance and origin.

ExampleHeight, weight, distance and area.

Since there is a natural zero, it is possible to multiple and divide the

numbers on a ratio scale. Apart from being able to use all the statistical

techniques that are used with the nominal, ordinal and interval scales,

techniques like the geometric mean and coefficient of variation may also be

used.


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The main limitation of ratio measurement is that it cannot be used for

characteristics such as leadership quality, happiness, satisfaction and other

properties which do not have natural zero points.

The different levels of measurement and their characteristics may be

summed up.

In the table below -

Levels of measurement CharacteristicsNominal No order, distance or origin

Ordinal Order, but no distance or originInterval Both order & distance, but no origin

Ratio Order, distance & origin

(b) Measurement also has several purposes.Three Purposes of ResearchSocial research can serve a variety of purposes. Three of the most

influential and common purposes of research are exploration, description

and explanation.

Exploration involves familiarizing a researcher with a topic. Explorationsatisfies the researcher's curiosity and desire for improved understanding.

Exploration tests the feasibility of undertaking a more extensive study.

Exploration helps develop the methods that will be used in a study.

Description involves describing situations and events through scientificobservation. Scientific descriptions are typically more accurate and precise

than causal ones. For example, the U. S. Census uses descriptive social

research in its examination of characteristics of the U. S. population.

Explanation involves answering the questions of what, where, when, andhow. Explanatory studies answer questions of why. For example, an

explanatory analysis of the 2002 General Social Survey (GSS) data

indicates that 38 percent of men and 30 percent of women said marijuanashould be legalized, while 55 percent of liberals and 27 percent of


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conservatives said the same. Given these statistics, you could start to

develop an explanation for attitudes toward marijuana legalization. In

addition, further study of gender and political orientation could lead to a

deeper explanation of this issue.

One of the primary purposes of classifying variables according to their level

or scale of measurement is to facilitate the choice of a statistical test used to

analyze the data. There are certain statistical analyses which are only

meaningful for data which are measured at certain measurement scales.

For example, it is generally inappropriate to compute the mean for

Nominal variables. Suppose you had 20 subjects, 12 of which were male,

and 8 of which were female. If you assigned males a value of '1' and

females a value of '2', could you compute the mean sex of subjects in your

sample? It is possible to compute a mean value, but how meaningful would

that be? How would you interpret a mean sex of 1.4? When you areexamining a Nominal variable such as sex, it is more appropriate to

compute a statistic such as a percentage (60% of the sample was male)

Q.2 a) What are the sources from which one may be able to identifyresearch problems?b) Why literature survey is important in research?

Ans. (a) The selection of a problem for research is not an easy task; itself is aproblem. One with a critical, curious and imaginative mind and is sensitive

to practical problems could easily identify problems for study.

The sources from which one may be able to identify research problems or

develop problems awareness are : Review of literatureAcademic experience Daily experience Exposure to field situations Consultations Brain storming Research Intuition


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(b) Frequently, an explanatory study is concerned with an area of subjectmatter in which explicit hypothesis have not yet been formulated. The

researchers task then is to review the available material with an eye on the

possibilities of developing hypothesis may have been stated by previous

research workers. The researcher has to take stock of these various

hypothesis with a view to evaluating their usefulness for further research

and to consider whether they suggest any new hypothesis. Sociological

journals, economic reviews, the bulletin of abstracts of current social

sciences research, directory of doctoral dissertation accepted by universities

etc afford a rich store of valuable clues. In addition to these general

sources, some governmental agencies and voluntary organizations publish

listings of summaries of research in their special fields of service.

Professional organizations, research groups and voluntary organizations are

a constant source of information about unpublished works in their special

fields.

Q.3 a) What are the characteristics of a good research design?b) What are the components of a research design?Ans. (a)Characteristics of a Good Research Design

1. It is a series of guide posts to keep one going in the right direction.2. It reduces wastage of time and cost.3. It encourages co-ordination and effective organization.4. It is a tentative plan which undergoes modifications, as circumstances

demand when the study progresses, new aspects, new conditions and

new relationships come to light and insight into the study deepens.

5. It has to be geared to the availability of data and the cooperation of theinformants.

6. It has also to be kept within the manageable limits.

(b) Components of a research design are :1. Dependent and Independent variables :

A magnitude that varies is known as variable. The concept may assume

different quantitative values, like height, weight, income, etc. Qualitative


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variables are not quantifiable in the strictest sense of objectivity. However,

the quantitative phenomena may also 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 to 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 variables.

For example, age is continuous variable; whereas the number of children is

a non- continuous variable.

When changes in one variable depends upon changes in one or more

variables, it is known as a dependent or endogenous variable, and the

variables that cause the changes in the dependent variable are known as the

independent or explanatory or exogenous 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 like income and prices of substitute commodity, then demand

also depends upon them in addition to the own price. Then, demand is a

dependent variable 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 affect the dependent variable are known as extraneous

variables. For instance, assume that a researcher wants to test the

hypothesis that there is relationship between childrens school

performance and their self-concepts, in which case the latter is an

independent variable and the former, the dependent variable. 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. The influencecaused by the extraneous variable on the dependent variable is technically

called as an experimental error.

3. ControlOne 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 study in such a manner that it

minimizes the effects of extraneous independent variables. The term


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control 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 an extraneous variable, when the dependent variables is

not free from its effects.

Research hypothesis : When a prediction or a hypothesizedrelationship is tested by adopting scientific methods, it is known as

research hypothesis. The research hypothesis is a predictive statement

which relates a dependent variable and an independent variable.

Generally, a research hypothesis must consist of at least one dependent

variable and one independent variable. Whereas, the relationships that

are assumed but not be tested are predictive statements that are not to

be objectively verified are not classified as research hypothesis.

Experimental and control groups : When a group is exposed to usualconditions in an experimental hypothesis-testing research, it is known as

control group. On the other hand, when the group is exposed to

certain new or special condition, it is known as an experimental group.

In the afore-mentioned example, the Group A cab be called a control

group and the Group B an experimental one. If both the groups A & B

are exposed to some special feature, then both the groups may be

called as experimental groups. A research design may include only the

experimental group or the both experimental and control groups

together.

Treatments : Treatments are referred to the different conditions towhich the experimental and control groups are subject to. In this

example considered, the two treatments are the parents with regular

earnings and those with no regular earnings. Likewise if a research study

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 truthof a statistical hypothesis relating to a given research problem. For

instance, experiment may be conducted to examine the yield of a

certain new variety of rice crop developed. Further, experiments may


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be categorized into two types namely, absolute experiment and

comparative experiment. If a researcher wishes to determine the impact

of a chemical fertilizer on the 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 as compared to

the impact of bio-fertilizer, then the experiment is known as a

comparative experiment.

Experiment Unit : Experimental units refer to the predetermined plots,characteristics or the blocks to which the different treatments are

applied. It is worth mentioning here that such experimental units must

be selected with great caution.

Q.4 a) Distinguish between Doubles sampling and multiphasesampling.b) What is replicated or interpenetrating sampling.Ans. a) Double Sampling & Multiphase Sampling

Double sampling refers to the subsection of the final sample form a pre-

selected larger sample that provided information for improving the final

selection. When the procedure is extended to more than two phases of

selection, it is then, called multi-phase sampling. This is also known as

sequential sampling, as sub-sampling is done from a main sample in

phases. Double sampling or multi-phase sampling is a compromise

solution for a dilemma posed by undesirable extremes. The statistics

based on the sample of n can be improved by using ancillary information

from a wide base : but this is too costly to obtain from the entire

population of N nL which includes the final sample n.

b) Replicated or Interpenetrating SamplingIt involves selection of a certain number of sub-samples rather than one

full sample from a population. All the sub-samples should be drawn using

the same sampling technique and each is a self-contained and adequate

sample of the population. Replicated sampling can be used with any basic

sampling technique: simple or stratified, single or multi-stage or single or

multiphase sampling. It provides a simple means of calculating the

sampling error. It is practical. The replicated samples can throw light on


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variable non-sampling errors. But disadvantage is that it limits the amount

of stratification that can be employed.

Q.5 a. How is secondary data useful to researcher?b. What are the criteria used for evaluation of secondary data?Ans. a) Use of Secondary Data

The secondary data may be used in three ways by a researcher. First, some

specific information from secondary sources may be used for reference

purpose. For example, the 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, secondary data may be used as a bench marks against which the

findings of 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 of a

research project. Such studies as securities Market Behavior, 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.

b) Secondary data should be evaluated. Ways for evaluation are :


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1. Data PertinenceThe first consideration in evaluation is to examine the pertinence of the

available secondary data to the research problem under study. The

following questions should be considered.

What are the definitions and classifications employed? Are theyconsistent?

What are the measurements of variables used? What is the degree towhich they conform to the requirements of our research?

What is the coverage of the secondary data in terms of topic and timer?Does this coverage fit the needs of our research?

On the basis of above consideration, the pertinence of the secondary data

to the research on hand should be determined as a researcher who is

imaginative and flexible may be able to redefine his research problem so as

to make use of otherwise unusable available data.

2. Data QualityIf the researcher is convinced about the available secondary data for his

needs, the next step is to examine the quality of the data. The quality if

data refers to their accuracy, reliability and competencies. The assurance

and reliability of the available secondary data depends on the organizationwhich collect them and the purpose for which they were collected. It is

important to go the original source of the secondary data rather than to use

an immediate source which has quoted from the original. Then only the

researcher can review the cautionary and other comments that were made

in the original source.

3. Data CompletenessThe completeness refers to the actual coverage of the published data. Thisdepends on the methodology and sampling design adopted by the original

organization. Is the methodology sound? Is the sample size small or large?

Answers to these questions may indicate the appropriateness and

adequacy. The question of possible bias should also be examined. The

researcher must be on guard when the source does not report the

methodology and sampling design. Then it is not possible to determine the

adequacy of the secondary data for the researchers study.


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Q.6 What are the differences between observation and interviewing asmethods of data collection? Give two specific examples ofsituations where either observation or interviewing would bemore appropriate.Ans. Observation means viewing or seeing. Observation may be defined as a

systematic viewing of a specific phenomenon in its proper setting for the

specific purpose of gathering data for a particular study. Observation is

classical method of scientific study.

Observation as a method of data collection has certain characteristics.

1. It is both a physical and a mental activity: The observing eye catches

many things that are present. But attention is focused on data that are

pertinent to the given study.

2. Observation is selective: A researcher does not observe anything and

everything, but selects the range of things to be observed on the basis of the

nature, scope and objectives of his study. For example, suppose a

researcher desires to study the causes of city road accidents and also

formulated a tentative hypothesis that accidents are caused by violation of

traffic rules and over speeding. When he observed the movements of

vehicles on the road, many things are before his eyes; the type, make, size

and color of the vehicles, the persons sitting in them, their hair style, etc.All such things which are not relevant to his study are ignored and only

over speeding and traffic violations are keenly observed by him.

3. Observation is purposive and not casual: It is made for the specific

purpose of noting things relevant to the study. It captures the natural social

context in which persons behavior occur. It grasps the significant events

and occurrences that affect social relations of the participants.

4. Observation should be exact and be based on standardized tools ofresearch and such as observation schedule, social metric scale etc., and

precision instruments, if any.

Interviewing is one of the prominent methods of data collection. It may be

defined as a two way systematic conversation between an investigator and

an informant, initiated for obtaining information relevant to a specific

study. It involves not only conversation, but also learning from the

respondents gesture, facial expressions and pauses, and his environment.

Interviewing requires face to face contact or contact over telephone and


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calls for interviewing skills. It is done by using a structured schedule or an

unstructured guide. Interviewing may be used either as a main method or

as a supplementary one in studies of persons. Interviewing is the only

suitable method for gathering information from illiterate or less educated

respondents. It is useful for collecting a wide range of data from factualdemographic data to highly personal and intimate information relating to a

persons opinions, attitudes, values, beliefs past experience and future

intentions. When qualitative information is required or probing is

necessary to draw out fully, and then interviewing is required. Where the

area covered for the survey is a compact, or when a sufficient number of

qualified interviewers are available, personal interview is feasible.

Interview is often superior to other data-gathering methods. People are

usually more willing to talk than to write. Once report is established, even

confidential information may be obtained. It permits probing into the

context and reasons for answers to questions. Interview can add flesh to

statistical information. It enables the investigator to grasp the behavioral

context of the data furnished by the respondents.

Observation is suitable for a variety of research purposes. It may be used

for studying

(a) The behavior of human beings in purchasing goods and services.: life

style, customs, and manner, interpersonal relations, group dynamics, crowd

behavior, leadership styles, managerial style, other behaviors and actions;

(b) The behavior of other living creatures like birds, animals etc.(c) Physical characteristics of inanimate things like stores, factories,

residences etc.

(d) Flow of traffic and parking problems

(e) movement of materials and products through a plant.

mba mb 0050 set 1 research methodology

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