Internal Assignment No :- 2

Paper Title :- Research Methodology for Management

MBA :-- 206

1. i) Explain quantitative and qualitative research ?

Market research can seem complicated when you are about to undertake it for the first time – what may help is that it broadly falls into two

distinctive areas that each have their own strengths: qualitative and quantitative research. -

quantitative research:- Quantitative research is a more logical and data-led approach which provides a measure of what people think from a statistical and numerical po

int of view. For example, if you wanted to know how many of your customers support a proposed change in your products or service and how strongly (on a scale) they support it.  Quantitative research can gather a large amount of data that can be easily organised and manipulated into reports for analysis. 

qualitative research :-

Unlike quantitative research which relies on numbers and data, qualitative research is more focused on how people feel, what they think and

why they make certain choices. For example, if you are thinking of changing your branding you would carry out qualitative research to see

what emotional reactions people have to the new identity and what they associate it with. - See more at: http://www.bl.uk/business-and-ip-

centre/articles/qualitative-and-quantitative-research-for-small-business#sthash.maXMtEeO.dpuf

ii) What is p;roba`bility sampling ?

A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These

days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.

Some DefinitionsBefore I can explain the various probability methods we have to define some basic terms. These are:

N = the number of cases in the sampling frame

n = the number of cases in the sample

NCn = the number of combinations (subsets) of n from N

f = n/N = the sampling fraction

iii) What is Hypothesis ?

Ans :-

A hypothesis is a proposed explanationfor a phenomenon. For a hypothesis to be a scientific hypothesis, the scientific method requires that

one can test it.Scientists generally base scientific hypotheses on previousobservations that cannot satisfactorily be explained with the

available scientific theories. Even though the words "hypothesis" and "theory" are often used synonymously, a scientific hypothesis is not the

same as a scientific theory. Aworking hypothesis is a provisionally accepted hypothesis proposed for further research.

iv) RATING EXPLAIN GRAPHIC SCALE ?

Ans :- A graphic rating scale, defined as any rating scale consisting of points on a continuum, is a generic label given to a broad

category of rating formats ( Cascio, 1991 ). Raters are presented with a description of a dimension on which the ratees are to be

evaluated, and a continuum with anchor points that demarcate levels of effectiveness along that continuum. The rater is asked to

judge the level of effectiveness for each ratee, using that rating continuum. The number of points on the rating scale can vary from

three upward. Research has indicated that five to nine scale points result in the highest quality of ratings ( Finn, 1972 ). Graphic

rating scales are probably the most common rating format. One reason for this popularity is that the graphic rating scale category

can be adapted to a wide variety of specific formats. Other reasons for their popularity include: (1) they are fairly easy to construct;

(2) they have a fairly high level of user acceptability; and (3) they have face validity ( Cardy and Dobbins, 1994 ). Graphic rating

scales can be differentiated based on the type and amount of information presented in the anchors. The most common format uses

ambiguous adjectives (e.g., “marginal,” “average,” or “outstanding”) as anchors. A more sophisticated format would use specific

behavioral descriptions for each anchor point

v) What is ANNOV ?

Ans :- Analysis of variance (ANOVA) tests the hypothesis that the means of two or more populations are equal. ANOVAs assess the importance of one or more factors by comparing the response variable means at the different factor levels. The null hypothesis states that all population means (factor level means) are equal while the alternative hypothesis states that at least one is different.

To perform an ANOVA, you must have a continuous response variable and at least one categorical factor with two or more levels. ANOVAs require data from approximately normally distributed populations with equal variances between factor levels. However, ANOVA procedures work quite well even if the normality assumption has been violated, unless one or more of the distributions are highly skewed or if the variances are quite different. Transformations of the original dataset may correct these violations.

Q.3) Explain the research processes in detail ?

Ans :-

The chief responsibility of a university is to produce and disseminate new knowledge. New knowledge is created through research. Research is based on primary and secondary sources, often together with original data collected via research "instruments" (surveys, interviews, questionnaires, "focus groups," etc.) to produce new knowledge on a particular topic.

Research may be categorized as either Basic or Applied:

Basic research looks at causes, effects, and the nature of things Applied research trys to find answers and solutions to specific problems.

The Research ProcessThe research process is the step-by-step procedure of developing one's research — and research paper. However, one can seldom progress in a step-by-step fashion as such. Writing a research paper frequently requires continuous, and sometimes extensive, re-evaluation and revision of both one's topic and the way it is presented.

It is often necessary to revise an initial research plan. You may need to add new material, delete extraneous material, or even change the topic completely, depending on what is discovered during your research. You may find that your topic is too broad and needs to be narrowed, or that sufficient information resources may not be available (e.g. the topic is too narrow, and needs to be expanded or changed). Sometimes what you learn may not support the thesis with which you began.

The research process involves identifying, locating, assessing, analyzing, and then developing and expressing your ideas. These are the same skills that will be needed in the post-university "real world" when you produce reports, proposals, or othe research for your employer. All of these activities will be based on primary and secondary sources from which recommendations or plans are formulated.

Theory in the Research ProcessAdvanced academic research is based on applying existing theory or a working hypothesis   (often as the basis for deducing new theory) to a research problem. Yet what can "theory" include, and is it required for the FIN-1 paper?

At its simplest, a "theory" is simply a hypothesis (idea) which has been validated by testing, usually in a form similar to if condition X prevails, then result Y will occur. A theory can be original and relatively simple; it need not be a Universal Truth derived from Aristotle. Could the thought that "Swedish-speaking Finns get better service at Stockmann's in Helsinki" be a "theory"? Possibly. But it would more easily be

thought of as one potential research question under the theory that there is a relationship between customer service and cultural stereotyping (involving not only language, but gender, race, age, height, weight, hair color, nationality, etc.). In other words, "if all other factors are equal, and one customer is Swedish-speaking and the other Finnish-speaking, would the quality of service be greater or lesser depending on the language spoken" [if X prevails, would Y then occur]?

If such questions were tested and found to be true, this could result in a "theory" on the human variables of customer service in multilingual, multicultural institutions, markets or communities.

Variations on this "theory" would then be repeatedly tested in order to arrive at a formulation that would be generally valid, together with an identification of factors that might cause it not to be valid.

Using Theory in the FIN-1 PaperThere are two primary functions of theory in the research paper:

1. To guide one's research. Theories help identify what the problem is, what the concepts or variables are, and what the results should be;

2. To reveal new insights into a topic, especially when using theories from quite different disciplines to show new analogies and ways of interpreting your topic, as discussed further in class.

Q.

Internal Assignment No :- 2

Research Methodology Management

MBA :-- 206

Q.1) i)

What is descriptive research ?

Descriptive research is used to describe characteristics of a population or phenomenon being studied. It does not answer questions about how/when/why the characteristics occurred. Rather it addresses the "what" question (what are the characteristics of the population or situation being studied?) [1] The characteristics used to describe the situation or population are usually some kind of categorical scheme also known as descriptive categories. For example, the periodic table categorizes the elements. Scientists use knowledge about the nature of electrons, protons and neutrons to devise this categorical scheme. We now take for granted the periodic table, yet it took descriptive research to devise it. Descriptive research generally precedes explanatory research. For example, over time the periodic table’s description of the elements allowed scientists to explain chemical reaction and make sound prediction when elements were combined.

ii) Explain non probability sampling ?

Ans ;- he difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling

does. Does that mean that nonprobability samples aren't representative of the population? Not necessarily. But it does mean that nonprobability samples cannot

depend upon the rationale of probability theory. At least with a probabilistic sample, we know the odds or probability that we have represented the population well.

We are able to estimate confidence intervals for the statistic. With nonprobability samples, we may or may not represent the population 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 over nonprobabilistic ones, and consider

them to be more accurate and rigorous. However, in applied social research there may be circumstances where it is not feasible, practical or theoretically sensible

to do random sampling. Here, we consider a wide range of nonprobabilistic alternatives.

iii) what is multivariate techniques ?

Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical

outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects

of all variables on the responses of interest.

Uses for multivariate analysis include:

design for capability (also known as capability-based design)

inverse design, where any variable can be treated as an independent variable

Analysis of Alternatives (AoA), the selection of concepts to fulfil a customer need

analysis of concepts with respect to changing scenarios

identification of critical design-drivers and correlations across hierarchical levels.

Multivariate analysis can be complicated by the desire to include physics-based analysis to calculate the effects of variables for a hierarchical "system-of-systems".

Often, studies that wish to use multivariate analysis are stalled by the dimensionality of the problem. These concerns are often eased through the use of surrogate

models, highly accurate approximations of the physics-based code. Since surrogate models take the form of an equation, they can be evaluated very quickly. This

becomes an enabler for large-scale MVA studies: while a Monte Carlo simulation across the design space is difficult with physics-based codes, it becomes trivial

when evaluating surrogate models, which often take the form of response-surface equations.

iv) Define null hypothesis and alternative hypothesis ?

A hypothesis test examines two opposing hypotheses about a population: the null hypothesis and the alternative hypothesis. How you set up these hypotheses depends on what you are trying to show.

Null hypothesis (H0)The null hypothesis states that a population parameter is equal to a value. The null hypothesis is often an initial claim that researchers specify using previous research or knowledge.

Alternative Hypothesis (H1)The alternative hypothesis states that the population parameter is different than the value of the population parameter in the null hypothesis. The alternative hypothesis is what you might believe to be true or hope to prove true.

v) What is chi square test ? Write is formula?

An important question to answer in any genetic experiment is how can we decide if our data fits any of the Mendelian ratios we have discussed. A

statistical test that can test out ratios is the Chi-Square or Goodness of Fit test.

Chi-Square Formula

Q.2) start merits and demerits in collecting data of a questionnaires? Describe main aspect of a questionnaire ?

dvantages of Questionnaire:(1) Economical:It is an economical way of accumulating information. It is economical both for the sender and for the

respondent in time, effort and cost. The cost of conducting the study with the help of questionnaire method is

very low. In questionnaire the researcher has to spend for paper printing and postage only. There is no need to

visit each and every respondent personally. So it does not require high cost for conduct of the research.

(2) Wide Coverage:It is probably the best metho d to collect information, compared to the other methods like interview or

observation, when the sample population is spread over a large territory. It permits a nationwide or even

international coverage.

Questionnaire makes it possible to contact with many people who could not otherwise be reached. It can cover

a large group at the same time. Goode and Hatt say that when the researcher has to cover the group of

respondents who are widely scattered, lie can use the questionnaire in order to minimize the cost.

For example, if the researcher wishes to poll the membership of the American Sociological Society,

transportation costs for interviewing would be excessive, both in terms of money and time. There may not be

enough time to make the necessary interview.

However, questionnaires could be distributed to all those members and information could be collected from

them. This can be done by a single researcher without the large funds otherwise required to hire an

interviewing staff to carry out the interview.

(3) Rapidity:Replies may be received very quickly in questionnaire method. In this case there is no need to visit the

respondent personally or continue the study over a long period. Thor “fore in comparison with other methods,

the mailed questionnaire is the quickest method.

(4) Suitable in Special Type of Response:The information about certain personal, secret matters can be best obtained through questionnaire method. For

example, information about sexual relationship, marital relationship, secret desires etc. can .be easily obtained

by ‘keeping the names of the respondents anonymous.

(5) Repetitive Information:Compared to other methods like schedule, interview or observation, questionnaire method is regarded as more

useful and cheap, where the repetitive information has to be collected at regular interval.

(6) An Easier Method:Questionnaire is comparatively an easier method to plan, construct and administer. It does not require much

technical skill or knowledge.

(7) It Puts Less Pressure on the Respondents:It puts less pressure on the respondents for immediate response. He can answer it at his own leisure, whereas

interview or observation demands specific fixation of time and situation,

(8) Uniformity:It helps in focusing the respondent’s attention on all the significant items. As it is administered, in a written form,

its standardized instructions for recording responses ensure some uniformity. Questionnaire does not permit

much of variation.

(9) Useful Preliminary Tool:Questionnaire may be used as a preliminary tool for conducting a depth study later on by any other method.

(10) Greater Validity:Questionnaire has some unique merits as regards validity of information. In methods like interview and

observation, the reliability of responses depends on the way the investigator has recorded them. Here they may

present biased or prejudiced information of their own. But in questionnaire method, the responses given by the

subjects are available in their own language and version. Therefore, it cannot be wrongly interpreted by the

researcher.

(11) Anonymity:Questionnaire ensures anonymity to its respondents. The respondents have a greater confidence that they will

not be identified by anybody for giving a particular view or opinion. They feel more comfortable and free to

express their view in this method.

(12) Most Flexible Tool for Data Collection:Questionnaire is no doubt the most flexible tool in collecting both quantitative and qualitative information.

Disadvantages of Questionnaire:(1) Limited Response:One of the major limitations of the questionnaire is that it can be applicable only to those respondents who

have a considerable amount of education. It can neither be used for illiterate nor for semi-literate persons.

The questionnaire quite often fails to cover very busy and pre-occupied persons among the respondents, lazy

and indifferent type of persons, the type of respondents who need to conceal a lot about themselves, the easy-

going and shirkers among the respondents, the persons who have a unreasonable contempt for research and

reform and the persons who unnecessarily doubt the research worker’s intentions, sincerity, devotion and

commitment.

These are the people who constitute a very important segment of the respondents to be covered in the

collection of data, but they can be seldom caught. Thus questionnaires are hardly appropriate for a larger

section of this type of population.

(2) Lack of Personal Contact:As in case of questionnaire the researcher does not go to the field, he is not able to establish a proper personal

relationship with the respondents. If the respondent fails to understand some of the technical terms or he has

any doubt, there is nobody to clarify these technical terms or doubts.

Even though the researcher tries in the best possible manner to make the questionnaire a simple, precise and

convenient one, the aim and objective of the questionnaire can be much better explained personally than

through any other means. Without the proper personal contact it is very difficult to motivate the respondent to

fill up the questionnaire.

(3) Poor Response:In case of mailed questionnaire method, the proportion of return is usually low. The factors which are likely to

affect the returns are: the layout of the questionnaire, its size, the organisation conducting the research work,

the nature of appeal, the kind of respondents chosen for research, inducement for response etc.

(4) Unreliability:The information collected through questionnaire cannot be said to be very much reliable or valid. If the subject

misinterprets a question or gives an incomplete or indefinite response very little can be done to connect such

response. As against this, in an interview there is always the possibility of rephrasing questions for further

clarification.

The questions can be repeated with adequate elaboration if it is so required. But in questionnaire method there

is no opportunity for repeating questions, explaining them or clarifying the doubts for a particular response.

Therefore, in it the validity of respondent’s response can hardly be examined.

The investigator here is not in a position to observe the gestures and expressions of the respondents. He

cannot cross check the inconsistencies or misrepresentation of the replies. So in questionnaire method,

reliability of responses is very low.

(5) Illegibility:Illegible handwriting of the respondent sometimes creates much difficulty for the researcher to understand the

responses. Sometimes the respondents erase and over write too much. These create many difficulties in

reading the answers.

(6) Incomplete Entries:Often most of the respondents fill up the questionnaire form very poorly. They sometimes leave out many

questions altogether or fill in such a way that, it becomes very difficult on the part of the investigator to follow

those responses. Other than this, there may be the problem of language, use of abbreviations and ambiguous

terms etc. All these make a questionnaire an incomplete one.

(7) Possibility of Manipulated Entries:In case of interview the investigator directly interacts with the respondents personal’ and intensively in a face to

face situation. He can judge a respondent, his attitude, understanding of the research topic and, if necessary,

can ask some cross questions to correct various errors.

So usually the respondent cannot manipulate his answer. But in questionnaire it is very difficult to detect the

errors of the respondents. Here the investigator does not have any facility to check the validity and reliability of

the information. In the absence of the researcher, the respondents may supply manipulated information.

(8) Useless in Depth-Studies:In questionnaire method, it is not possible on the part of the researcher to conduct an intensive or in-depth

study of the feelings, reactions and sentiments of the respondents. All these require a healthy interaction of the

researcher with the respondents. But in questionnaire method, the investigator is not present in the field, so

nothing can be done to establish rapport with the respondent. Due to this lack of interaction with the

respondent, the researcher cannot go into the details of the respondent’s life. So through questionnaire method

one cannot conduct an in-depth study.

(9) Response from Improper Representative Section of People:The respondents who return the questionnaires may not constitute a representative section of the entire group.

Only mere responsible, research minded or those in favour of the issue may prefer to respond. Some of the

important sections of the group may totally remain silent. This vitiates the final conclusions and findings.

(10) Lack of Rapport with the Subject:There are many people who would not like to share any important information unless and until they are

impressed about the rationale of the study and personality of the investigator. The questionnaire does not

provide for any opportunity to the investigator to establish rapport with the subject and this cannot attract the

respondent for a better response.

(11) Not Suitable for Delicate Issues:Some of the research areas are so delicate, sensitive, intricate and confidential in nature that it becomes

difficult to frame questions on them. It is impossible to put down certain delicate issues in writing.

MAIN ASPECTS OF THE QUESTIONNAIRE –1.General form – It can be structured or unstructured. Structured questionnaires are those in which there are definite, concrete and pre-

determined questions. The form of questions may be closed, open or multiple choice questions. In an unstructured questionnaire all these

characteristics are missing, the interviewer is given a guide on the type of info to be obtained and the formulation of questions is done by his

own experience and the replies are taken down in respondents own words.

2.Question sequence – A proper sequence of questions reduces the chance of individual questions being misunderstood. To make the

questionnaire effective the question – sequence must be clean and smoothly moving (the relation of one question to another should be

readily apparent). The opening question should be such as to erose human interest. Questions relating to personal wealth or character, or

questions putting strain on the memory of the respondent should be avoided at first.The question sequence must conform to the

respondents’ way of thinking. It should go from general to more specific or from easy to answer to the toughest.

Q. 4.

Sampling is a means of selecting a subset of units from a target population for the purpose of collecting information. This information is used to draw inferences about the population as a whole. The subset of units that are selected is called a sample. The sample design encompasses all aspects of how to group units on the frame, determine the sample size, allocate the sample to the various classifications of frame units, and finally, select the sample. Choices in sample design are influenced by many factors, including the desired level of precision and detail of the information to be produced, the availability of appropriate sampling frames, the availability of suitable auxiliary variables for stratification and sample selection, the estimation methods that will be used and the available budget in terms of time and resources.

Basic Design Elements. Most research designs can be constructed from four basic elements:

1. Time. A causal relationship, by its very nature, implies that some time has elapsed between the occurrence of the cause and the consequent effect.

While for some phenomena the elapsed time might be measured in microseconds and therefore might be unnoticeable to a casual observer, we

normally assume that the cause and effect in social science arenas do not occur simultaneously, In design notation we indicate this temporal element

horizontally - whatever symbol is used to indicate the presumed cause would be placed to the left of the symbol indicating measurement of the effect.

Thus, as we read from left to right in design notation we are reading across time. Complex designs might involve a lengthy sequence of observations

and programs or treatments across time.

2. Program(s) or Treatment(s). The presumed cause may be a program or treatment under the explicit control of the researcher or the occurrence of

some natural event or program not explicitly controlled. In design notation we usually depict a presumed cause with the symbol "X". When multiple

programs or treatments are being studied using the same design, we can keep the programs distinct by using subscripts such as "X1" or "X2". For a

comparison group (i.e., one which does not receive the program under study) no "X" is used.

3. Observation(s) or Measure(s). Measurements are typically depicted in design notation with the symbol "O". If the same measurement or observation

is taken at every point in time in a design, then this "O" will be sufficient. Similarly, if the same set of measures is given at every point in time in this

study, the "O" can be used to depict the entire set of measures. However, if different measures are given at different times it is useful to subscript the

"O" to indicate which measurement is being given at which point in time.

4. Groups or Individuals. The final design element consists of the intact groups or the individuals who participate in various conditions. Typically, there

will be one or more program and comparison groups. In design notation, each group is indicated on a separate line. Furthermore, the manner in which

groups are assigned to the conditions can be indicated by an appropriate symbol at the beginning of each line. Here, "R" will represent a group which

was randomly assigned, "N" will depict a group which was nonrandomly assigned (i.e., a nonequivalent group or cohort) and a "C" will indicate that the

group was assigned using a cutoff score on a measurement