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Student name:   Course:  semester 3 fall 2014
Registration number:                                                                   Lc code:   
Subject name :   Research Methodology Subject code:  MB0050


1 Research  is  a  sequential  method  of  enquiry,  directed  towards  a  clear  implicit  or explicit objective. Describe in detail the steps to be carried out in a typical research study? (Meaning of Research Listing the steps, Explanation of the steps in a research study)

Answer:- Meaning of Research

The dictionary defines the former as a prefix meaning ‘again’, ‘anew’ or ‘over again’. Search is defined as a verb meaning ‘to examine closely and carefully’, ‘to test and try’, or ‘to probe’. Together, they form a noun describing a careful, systematic, patient study and investigation in some field of knowledge, undertaken to establish facts or principles.’

Listing the steps

  1. The management dilemma
  2. Defining the research problem
  3. Formulating the research hypotheses
  4. Developing the research proposal
  5. Research design formulation
  6. Sampling design
  7. Planning and collecting the data for research
  8. Data refining and preparation for analysis
  9. Data analysis and interpretation of findings
  10. The research report and implications for the manager’s dilemma

Explanation of the steps in a research study

The management dilemma

Any research starts with the need and desire to know more. This is essentially the management dilemma. It could be the researcher himself or herself or it could be a business manager who gets the study by done by a researcher. The need might be purely academic (basic or fundamental research) or there might be an immediate business decision that requires an effective and workable solution (applied research).


Defining the research problem

This is the first and the most critical step of the research journey. For example, a soft drink manufacturer who is making and selling aerated drinks now wants to expand his business. He wants to know whether moving into bottled water would be a better idea or he should look at fruit juice based drinks. Thus, a comprehensive and detailed survey of the bottled water as well as the fruit juice market will have to be done. He will also have to decide whether he wants to know consumer acceptance of a new drink.


Formulating the research hypotheses

In the model, we have drawn broken lines to link defining the research problem stage to the hypotheses formulation stage. The reason is that every research study might not always begin with a hypothesis; in fact, the task of the study might be to collect detailed data that might lead to, at the end of the study, some indicative hypotheses to be tested in subsequent research. For example, while studying the lifestyle and eating-out behavior of consumers at Pizza Hut, one may find that the young student group consume more pizzas


Developing the research proposal

Once the management dilemma has been converted into a defined problem and a working hypothesis, the next step is to develop a plan of investigation.This is called the research proposal. The reason for its placement before the other stages is that before you begin the actual research study in order to answer the research question you need to spell out the research problem, the scope and the objectives of the study and the operational plan for achieving this


Research design formulation

Based on the orientation of the research, i.e., exploratory, descriptive or causal, the researcher has a number of techniques for addressing the stated objectives. These are termed in research as research designs. The main task of the design is to explain how the research problem will be investigated. There are different kinds of designs available to you while doing a research. These will be discussed in detail in Unit 3.


Sampling design

It is not always possible to study the entire population. Thus, one goes about studying a small and representative sub-group of the population. This sub-group is referred to as the sample of the study. There are different techniques available for selecting the group based on certain assumptions. The most important criteria for this selection would be the representativeness of the sample selected from the population under study.



2 What are descriptive research designs?  Explain the different kinds of descriptive research designs.

(Meaning of Descriptive Research designs, Kinds of Descriptive research designs)

Answer:- Meaning of Descriptive Research designs

As the name implies, the objective of descriptive research studies is to provide a comprehensive and detailed explanation of the phenomena under study. The intended objective might be to give a detailed sketch or profile of the respondent population being studied. For example, to design an advertising and sales promotion campaign for high-end watches, a marketer would require a holistic profile of the population that buys such luxury products. Thus a descriptive study, (which generates data on who, what, when, where, why and how of luxury accessory brand purchase) would be the design necessary to fulfill the research objectives.

Descriptive research thus are conclusive studies. However, they lack the precision and accuracy of experimental designs, yet it lends itself to a wide range of situations and is more frequently used in business research. Based on the time period of the collection of the research information, descriptive research is further subdivided into two categories: cross-sectional studies and longitudinal studies.


Descriptive research designs

  1. Cross-sectional Studies

As the name suggests, cross-sectional studies involve a slice of the population. Just as in scientific experiments one takes a cross-section of the leaf or the cheek cells to study the cell structure under the microscope, similarly one takes a current subdivision of the population and studies the nature of the relevant variables being investigated.

There are two essential characteristics of cross-sectional studies:

  • The cross-sectional study is carried out at a single moment in time and thus the applicability is most relevant for a specific period. For example, one cross-sectional study was conducted in 2002 to study the attitude of Americans towards Asian-Americans, after the 9/11 terrorist attack. This revealed the mistrust towards Asians. Another cross-sectional study conducted in 2012 to study the attitude of Americans towards Asian- Americans revealed more acceptance and less mistrust. Thus the cross- sectional studies cannot be used interchangeably. .
  • Secondly, these studies are carried out on a section of respondents from the population units under study (e.g., organizational employees, voters, consumers, industry sectors). This sample is under consideration and under investigation only for the time coordinate of the study.

There are also situations in which the population being studied is not of a homogeneous nature but composed of different groups. Thus it becomes essential to study the sub-segments independently. This variation of the design is termed as multiple cross-sectional studies. Usually this multi-sample analysis is carried out at the same moment in time. However, there might be instances when the data is obtained from different samples at different time intervals and then they are compared. Cohort analysis is the name given to such cross- sectional surveys conducted on different sample groups at different time intervals. Cohorts are essentially groups of people who share a time zone or have experienced an event that took place at a particular time period.


  1. Longitudinal Studies

A single sample of the identified population that is studied over a longer period of time is termed as a longitudinal study design. A panel of consumers specifically chosen to study their grocery purchase pattern is an example of a longitudinal design. There are certain distinguishing features of the same:

  • The study involves the selection of a representative panel, or a group of individuals that typically represent the population under study.
  • The second feature involves the repeated measurement of the group over fixed intervals of time. This measurement is specifically made for the variables under study.
  • A distinguishing and mandatory feature of the design is that once the sample is selected, it needs to stay constant over the period of the study. That means the number of panel members has to be the same. Thus, in case a panel member due to some reason leaves the panel, it is critical to replace him/her with a representative member from the population under study.

Longitudinal study using the same section of respondents thus provides more accurate data than one using a series of different samples. These kinds of panels are defined as true panels and the ones using a different group every time are called omnibus panels. The advantages of a true panel are that it has a more committed sample group that is likely to tolerate extended or long data collecting sessions. Secondly, the profile information is a one-time task and need not be collected every time. Thus, a useful respondent time can be spent on collecting some research-specific information.


3 The  procedure  of  testing  hypothesis  requires  a  researcher  to  adopt  several  steps. Describe in brief all such steps. (Meaning of hypothesis Steps in testing hypothesis)

Answer:- Meaning of hypothesis

A hypothesis is a tentative statement about the relationship between two or more variables. A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states, “This study is designed to assess the hypothesis that sleep deprived people will perform worse on a test than individuals who are not sleep deprived.”


Steps in testing hypothesis

The following steps are followed in the testing of a hypothesis:

Setting up of a hypothesis:  The first step is to establish the hypothesis to be tested. As it is known, these statistical hypotheses are generally assumptions about the value of the population parameter; the hypothesis specifies a single value or a range of values for two different hypotheses rather than constructing a single hypothesis. These two hypotheses are generally referred to as (1) the null hypotheses denoted by H and (2) alternative hypothesis denoted by H . The null hypothesis is the hypothesis of the population parameter taking a specified value. In case of two populations, the null hypothesis is of no difference or the difference taking a specified value. The hypothesis that is different from the null hypothesis is the alternative hypothesis. If the null hypothesis H is rejected based upon the sample information, the alternative hypothesis H1  is accepted. Therefore, the two hypotheses are constructed in such a way that if one is true, the other one is false and vice versa.

Setting up of a suitable significance level:  The next step is to choose a suitable level of significance. The level of significance denoted by α is chosen before drawing any sample. The level of significance denotes the probability of rejecting the null hypothesis when it is true. The value of α varies from problem to problem, but usually it is taken as either 5 per cent or 1 per cent. A 5 per cent level of significance means that there are 5 chances out of hundred that a null hypothesis will get rejected when it should be accepted. When the null hypothesis is rejected at any level of significance, the test result is said to be significant. Further, if a hypothesis is rejected at 1 per cent level, it must also be rejected at 5 per cent significance level.

Determination of a test statistic: The next step is to determine a suitable test statistic and its distribution. As would be seen later, the test statistic could be t, Z, χ2  or F, depending upon various assumptions to be discussed later in the book.

Determination of critical region:   Before a sample is drawn from the population, it is very important to specify the values of test statistic that will lead to rejection or acceptance of the null hypothesis. The one that leads to the rejection of null hypothesis is called the critical region. Given a level of significance, α, the optimal critical region for a two-tailed test consists of that α/2 per cent area in the right hand tail of the distribution plus that α/2 per cent in the left hand tail of the distribution where that null hypothesis is rejected.

Computing the value of test-statistic:   The next step is to compute the value of the test statistic based upon a random sample of size n. Once the value of test statistic is computed, one needs to examine whether the sample results fall in the critical region or in the acceptance region.

Making decision: The hypothesis may be rejected or accepted depending upon whether the value of the test statistic falls in the rejection or the acceptance region. Management decisions are based upon the statistical decision of either rejecting or accepting the null hypothesis. In case a hypothesis is rejected, the difference between the sample statistic and the hypothesized population parameter is considered to be significant. On the other hand, if the hypothesis is accepted, the difference between the sample statistic and the hypothesized population parameter is not regarded as significant and can be attributed to chance.


4 a.   Distinguish between:

  1. Schedules and Questionnaires
  2. Open ended and closed ended questions
  3. Explain the questionnaire design process.

  (Differences Questionnaire design process)


  1. i. Schedules and Questionnaires: The questionnaires always, even the schedules, begin with standardized instructions. These begin by greeting the respondent and then introducing the researcher and then the purpose of questionnaire administration. For example, in the study on organic food products, the following instructions were given at the beginning of the questionnaire: ‘Hi. We __________ are carrying out a market research on the purchase behaviour of grocery products/organic food. We are conducting a survey of consumers, retailers and experts in the NCR for the same. As you are involved in the purchase and/or consumption of food products, we seek your cooperation for providing the following relevant information for our research. Thank you very much.’

Opening questions: After instructions come the opening questions, which lead the reader into the study topic. For example, a questionnaire on understanding the consumer’s buying behavior in malls can ask an opening question that is generic in nature, such as:  What is your opinion about shopping at a mall?

Study questions: After the opening questions, the bulk of the instrument needs to be devoted to the main questions that are related to the specific information needs of the study. Here also, the general rule is that the simpler questions, which do not require a lot of thinking or response time should be asked first as they build the tempo for answering the more difficult/sensitive questions later on. This method of going in a sequential manner from the general to the specific is called the funnel approach.

Classification information: This is the information that is related to the basic socio-economic and demographic traits of the person. These might include name (kept optional in some cases), address, e-mail address and telephone number.

Acknowledgement: The questionnaire ends by acknowledging the inputs of the respondent and thanking him for his cooperation and valuable contribution.


  1. ii. Open ended and closed ended questions:

Open-ended questions :In open-ended questions, the openness refers to the option of answering in one’s own words. They are also referred to as unstructured questions or freeresponse or free-answer questions. Some illustrations of this type are listed below:

  • What is your age?
  • Which is your favourite TV serial?
  • I like Nescafe because ________________________
  • My career goal is to ________________________

Closed-ended questions

In closed-ended questions, both the question and response formats are structured and defined.There are three kinds of formats as we observed earlier— dichotomous questions, multiple–choice questions and those that have a scaled response.

  1. Dichotomous questions: These are restrictive alternatives and provide the respondents only with two answers. These could be ‘yes’ or ‘no’, like or dislike, similar or different, married or unmarried, etc.
  2. Multiple-choice questions: Unlike dichotomous questions, the person is given a number of response alternatives here. He might be asked to choose the one that is most applicable. For example, this question was given to a retailer who is currently not selling organic food products:

Will you consider selling organic food products in your store?

  • Definitely not in the next one year
  • Probably not in the next one year
  • Undecided
  • Probably in the next one year
  • Definitely in the next one year

iii. Scales: Scales refer to the attitudinal scales. Since these questions have been discussed in detail in the earlier unit, we will only illustrate this with an example. The following is a question which has two sub-questions designed on the Likert scale. These require simple agreement and disagreement on the part of the respondent. This scale is based on the interval level of measurement.


Explain the questionnaire design process

  1. Convert the research objectives into information areas

This is the first step of the design process. By this time the researcher is clear about the research questions; research objectives; variables to be studied; research information required and the characteristics of the population being studied. Once these tasks are done, one can prepare a tabled framework so that the questions which need to be developed become clear


  1. Method of administration

Once the researcher has identified his information area; he needs to specify how the information should be collected. The researcher usually has available to him a variety of methods for administering the study. The main methods are personal schedule (discussed earlier in the unit), self-administered questionnaire through mail, fax, e-mail and web-based questionnaire


  1. Content of the questionnaire

The next step is to determine the matter to be included as questions in the measure. The researcher needs to do an objective quality check in order to see what research objective/information need the question would be covering before using any of the framed questions.


  1. Motivating the respondent to answer

The questionnaire should be designed in a manner that it involves the respondent and motivates him/her to give information. There are different situations which might lead to this. Each of these is examined separately here:

Does the person have the required information? It has been found that the person has had no experience with the issue being studied. Look at the following question:

How do you evaluate the negotiation skills module, viz., the communication and presentation skill module?                                                         (Incorrect)


5  a.   What is the analysis of variance? What are the assumptions of the technique? Give a few examples where the techniques could be used.

  1. The following data represents the number of units produced by four operators during three different shifts:

Perform a two-way analysis of variance and interpret the result.

(a.   Meaning, Assumptions and examples , b.   Formulas, Calculation, Solution and Interpretation to the problem)

Answer: a. Analysis of variance: A technique used to compare means of two or more samples (using the F distribution). This technique can be used only for numerical data.

The technique has found applications in the fields of economics, psychology, sociology, business and industry. It becomes handy in situations where we want to compare the means of more than two populations. Some examples could be to compare:

  • the mean cholesterol content of various diet foods
  • the average mileage of, say, five automobiles
  • the average telephone bill of households belonging to four different income groups and so on.

A Fisher developed the theory concerning ANOVA. The basic principle underlying the technique is that the total variation in the dependent variable is broken into two parts—one which can be attributed to some specific causes and the other that may be attributed to chance. The one which is attributed to the specific causes is called the variation between samples and the one which is attributed to chance is termed as the variation within samples. Therefore, in ANOVA, the total variance may be decomposed into various components corresponding to the sources of the variation.

In ANOVA, the dependent variable in question is metric (interval or ratio scale), whereas the independent variables are categorical (nominal scale). If there is one independent variable (one factor) divided into various categories, we have one-way or one-factor analysis of variance. In the two-way or two-factor analysis of variance, two factors each divided into the various categories are involved.

In ANOVA, it is assumed that each of the samples is drawn from a normal population and each of these populations has an equal variance. Another assumption that is made is that all the factors except the one being tested are controlled (kept constant). Basically, two estimates of the population variances are made. One estimate is based upon between the samples and the other one is based upon within the samples. The two estimates of variances can be compared for their equality using F statistic.


  1. Solution: Two-way ANOVA determines how a response is affected by two factors. For example, you might measure a response to three different drugs in both men and women.

Source of variation

Two-way ANOVA divides the total variability among values into four components. Prism tabulates the percentage of the variability due to interaction between the row and column factor, the percentage due to the row factor, and the percentage due to the column factor. The remainder of the variation is among replicates (also called residual variation).


X1 vs X2 nonsignificant
X1 vs X3 nonsignificant
X1 vs X4 nonsignificant
X2 vs X3 nonsignificant
X2 vs X4 P<.05


X3 vs X4 nonsignificant

X2 vs X4:

P-value = 2*P(t> 4 when df = 4) = 2*tcdf(4,100,4) = 0.02

.02 < .05

and for exaXple

X1 vs X2:


P-value = 2*P(t> .65 when df = 4) = 2*tcdf(.65,100,4) = 2*.28


6 Explain the Structure of the Research Report. What are the guidelines for effective report writing?

(Explanation of the Structure of the Research Report Guidelines for effective report writing)

Answer:- Structure of the Research Report

The reporting requires a structured format and by and large, the process is standardized. As stated above, the major difference amongst the types of reports is that all the elements that make a research report would be present only in a detailed technical report. Usage of theoretical and technical jargon would be higher in the technical report and visual presentation of data would be higher in the management report.

The process of report formulation and presentation is present. As can be observed, the preliminary section includes the title page, followed by the letter of authorization, acknowledgements, executive summary and the table of contents. Then come the background section, which includes the problem statement, introduction, study background, scope and objectives of the study and the review of literature (depends on the purpose). This is followed by the methodology section, which, as stated earlier, is again specific to the technical report. This is followed by the findings section and then come the conclusions. The technical report would have a detailed bibliography at the end.

In the management report, the sequencing of the report might be reversed to suit the needs of the decision-maker, as here the reader needs to review and absorb the findings. Thus, the last section on interpretation of findings would be presented immediately after the study objectives and a short reporting on methodology could be presented in the appendix.


Report Guidelines for effective report writing


Clear report mandate: While writing the research problem statement and study background, the writer needs to be absolutely clear in terms of why and how the problem was formulated. Clearly designed methodology: Any research study has its unique orientation and scope and thus has a specific and customized research design, sampling and data collection plan. In researches, that are not completely transparent on the set of procedures, one cannot be absolutely confident of the findings and resulting conclusions.

Clear representation of findings: Complete honesty and transparency in stating the treatment of data and editing of missing or contrary data is extremely critical.

Representativeness of study finding: A good research report is also explicit in terms of extent and scope of the results obtained, and in terms of the applicability of findings.


Thus, some guidelines should be kept in mind while writing the report.

Command over the medium: A correct and effective language of communication is critical in putting ideas and objectives in the vernacular of the reader/decision-maker.

Phrasing protocol: There is a debate about whether or not one makes use of personal pronoun while reporting. The use of personal pronoun such as ‘I think…..’ or ‘in my opinion…..’ lends a subjectivity and personalization of judgement. Thus, the tone of the reporting should be neutral.

For example: ‘Given the nature of the forecasted growth and the opinion of the respondents, it is likely that the……’ Whenever the writer is reproducing the verbatim information from another document or comment of an expert or published source, it must be in inverted commas or italics and the author or source should be duly acknowledged.

For example: Sarah Churchman, Head of Diversity, Price water house Coopers, states  ‘At PricewaterhouseCoopers we firmly believe that promoting work–life balance is a ‘business-critical’ issue and not simply the ‘right thing to do’.The writer should avoid long sentences and break up the information in clear chunks, so that the reader can process it with ease.

Simplicity of approach: Along with grammatically and structurally correct language, care must be taken to avoid technical jargon as far as possible. In case it is important to use certain terminology, then, definition of these terms can be provided in the glossary of terms at the end of the report.

Report formatting and presentation: In terms of paper quality, page margins and font style and size, a professional standard should be maintained. The font style must be uniform throughout the report. The topics, subtopics, headings and subheadings must be construed in the same manner throughout the report. The researcher can provide data relief and variation by adequately supplementing the text with graphs and figures.

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