mb0050 set-2

SIKKIM MANIPAL UNIVERSITY

RESEARCH METHODOLOGY – 4 CREDITS

SUBJECT CODE - MB0050

BOOK ID – B1206

ASSIGNMENT SET-1

1.

a) Explain the General characteristics of observation.

Answer:

General Characteristics of Observation Method

Observation as a method of data collection has certain characteristics.

i. 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.

ii. 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 colour 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.

iii.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 behaviour occur. It grasps the significant events and

occurrences that affect social relations of the participants.

iv.Observation should be exact and be based on standardized tools of

research and such as observation schedule, social metric scale etc., and

precision instruments, if any.

b) What is the Utility of Observation in Business Research?

Answer:

SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143

SIKKIM MANIPAL UNIVERSITYUtility of Observation in Business Research

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

studying

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

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

crowd behaviour, leadership styles, managerial style, other behaviours and

actions;

(b) The behaviour 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.

2.

a) Briefly explain Interviewing techniques in Business Research?

Answer:

Interviewing techniques in Business Research

The interview process consists of the following stages:

- Preparation

- Introduction

- Developing rapport

- Carrying the interview forward

- Recording the interview

- Closing the interview

i. Preparation

The interviewing requires some preplanning and preparation. The

interviewer should keep the copies of interview schedule/guide (as the case may

be) ready to use. He should have the list of names and addresses of respondents,

he should regroup them into contiguous groups in terms of location in order to

save time and cost in traveling. The interviewer should find out the general daily

routine of the respondents in order to determine the suitable timings for interview.

Above all, he should mentally prepare himself for the interview. He should think

about how he should approach a respondent, what mode of introduction he could

adopt, what situations he may have to face and how he could deal with them. The

interviewer may come across such situations as respondents; avoidance,

reluctance, suspicion, diffidence, inadequate responses, distortion, etc. The


SIKKIM MANIPAL UNIVERSITYinvestigator should plan the strategies for dealing with them. If such preplanning

is not done, he will be caught unaware and fail to deal appropriately when he

actually faces any such situation. It is possible to plan in advance and keep the

plan and mind flexible and expectant of new development.

ii. Introduction

The investigator is a stranger to the respondents. Therefore, he should be

properly introduced to each of the respondents. What is the proper mode of

introduction? There is no one appropriate universal mode of introduction. Mode

varies according to the type of respondents. When making a study of an

organization or institution, the head of the organization should be approached first

and his cooperation secured before contacting the sample inmates/employees.

When studying a community or a cultural group, it is essential to approach the

leader first and to enlist cooperation. For a survey or urban households, the

research organization’s letter of introduction and the interviewer’s identity card

can be shown. In these days of fear of opening the door for a stranger, residents

cooperation can be easily secured, if the interviewer attempts to get him

introduced through a person known to them, say a popular person in the area e.g.,

a social worker. For interviewing rural respondents, the interviewer should never

attempt to approach them along with someone from the revenue department, for

they would immediately hide themselves, presuming that they are being contacted

for collection of land revenue or subscription to some government bond. He

should not also approach them through a local political leader, because persons

who do not belong to his party will not cooperate with the interviewer. It is rather

desirable to approach the rural respondents through the local teacher or social

worker.

After getting himself introduced to the respondent in the most appropriate

manner, the interviewer can follow a sequence of procedures as under, in order to

motivate the respondent to permit the interview:

a. With a smile, greet the respondent in accordance with his cultural

pattern.

b. Identify the respondent by name.

c. Describe the method by which the respondent was selected.

d. Mention the name of the organization conducting the research.SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143

SIKKIM MANIPAL UNIVERSITYe. Assure the anonymity or confidential nature of the interview.

f. Explain their usefulness of the study.

g. Emphasize the value of respondent’s cooperation, making such

statements as “You are among the few in a position to supply the

information”. “Your response is invaluable.” “I have come to learn

from your experience and knowledge”.

iii. Developing Rapport

Before starting the research interview, the interviewer should establish a

friendly relationship with the respondent. This is described as “rapport”. It means

establishing a relationship of confidence and understanding between the

interviewer and the respondent. It is a skill which depends primarily on the

interviewer’s commonsense, experience, sensitivity, and keen observation.

Start the conversation with a general topic of interest such as weather,

current news, sports event, or the like perceiving the probable of the respondent

from his context. Such initial conversation may create a friendly atmosphere and a

warm interpersonal relationship and mutual understanding. However, the

interviewer should “guard against the over rapport” as cautioned by Herbert

Hyman. Too much identification and too much courtesy result in tailoring replied

to the image of a “nice interviewer.” The interviewer should use his discretion in

striking a happy medium.

iv. Carrying the Interview Forward

After establishing rapport, the technical task of asking questions from the

interview schedule starts. This task requires care, self-restraint, alertness and

ability to listen with understanding, respect and curiosity. In carrying on this task

of gathering information from the respondent by putting questions to him, the

following guidelines may be followed:

1) Start the interview. Carry it on in an informal and natural conversational style.

2) Ask all the applicable questions in the same order as they appear on the schedule

without any elucidation and change in the wording. Ask all the applicable questions

listed in the schedule. Do not take answers for granted.


SIKKIM MANIPAL UNIVERSITY3) If interview guide is used, the interviewer may tailor his questions to each respondent,

covering of course, the areas to be investigated.

4) Know the objectives of each question so as to make sure that the answers adequately

satisfy the question objectives.

5) If a question is not understood, repeat it slowly with proper emphasis and appropriate

explanation, when necessary.

6) Talk all answers naturally, never showing disapproval or surprise. When the

respondent does not meet the interruptions, denial, contradiction and other

harassment, he may feel free and may not try to withhold information. He will be

motivated to communicate when the atmosphere is permissive and the listener’s

attitude is non judgmental and is genuinely absorbed in the revelations.

7) Listen quietly with patience and humility. Give not only undivided attention, but also

personal warmth. At the same time, be alert and analytic to incomplete, non specific

and inconsistent answers, but avoid interrupting the flow of information. If necessary,

jot down unobtrusively the points which need elaboration or verification for later and

timelier probing. The appropriate technique for this probing is to ask for further

clarification in such a polite manner as “I am not sure, I understood fully, is

this….what you meant?”

8) Neither argue nor dispute.

9) Show genuine concern and interest in the ideas expressed by the respondent; at the

same time, maintain an impartial and objective attitude.

10) Should not reveal your own opinion or reaction. Even when you are asked of your

views, laugh off the request, saying “Well, your opinions are more important than

mine.”

11) At times the interview “runs dry” and needs re-stimulation. Then use such expressions

as “Uh-huh” or “That interesting” or “I see” “can you tell me more about that?” and

the like.

12) When the interviewee fails to supply his reactions to related past experiences,

represent the stimulus situation, introducing appropriate questions which will aid in


SIKKIM MANIPAL UNIVERSITYrevealing the past. “Under what circumstances did such and such a phenomenon

occur?” or “How did you feel about it and the like.

13) At times, the conversation may go off the track. Be alert to discover drifting, steer the

conversation back to the track by some such remark as, “you know, I was very much

interested in what you said a moment ago. Could you tell me more about it?”

14) When the conversation turns to some intimate subjects, and particularly when it deals

with crises in the life of the individual, emotional blockage may occur. Then drop the

subject for the time being and pursue another line of conversation for a while so that a

less direct approach to the subject can be made later.

15) When there is a pause in the flow of information, do not hurry the interview. Take it

as a matter of course with an interested look or a sympathetic half-smile. If the silence

is too prolonged, introduce a stimulus saying “You mentioned that… What happened

then?”

v. Additional Sittings

In the case of qualitative interviews involving longer duration, one single

sitting will not do, as it would cause interview weariness. Hence, it is desirable to

have two or more sittings with the consent of the respondent.

vi. Recording the Interview

It is essential to record responses as they take place. If the note taking is

done after the interview, a good deal of relevant information may be lost. Nothing

should be made in the schedule under respective question. It should be complete

and verbatim. The responses should not be summarized or paraphrased. How can

complete recording be made without interrupting the free flow of conversation?

Electronic transcription through devices like tape recorder can achieve this. It has

obvious advantages over note-taking during the interview. But it also has certain

disadvantages. Some respondents may object to or fear “going on record”.

Consequently the risk of lower response rate will rise especially for sensitive

topics.


SIKKIM MANIPAL UNIVERSITYIf the interviewer knows short-hand, he can use it with advantage.

Otherwise, he can write rapidly by abbreviating word and using only key words

and the like. However, even the fast writer may fail to record all that is said at

conversational speed. At such times, it is useful to interrupt by some such

comment as “that seems to be a very important point, would you mind repeating

it, so that I can get your words exactly.” The respondent is usually flattered by this

attention and the rapport is not disturbed.

The interviewer should also record all his probes and other comments on

the schedule, in brackets to set them off from responses. With the pre-coded

structured questions, the interviewer’s task is easy. He has to simply ring the

appropriate code or tick the appropriate box, as the case may be. He should not

make mistakes by carelessly ringing or ticketing a wrong item.

vii. Closing the Interview

After the interview is over, take leave off the respondent thanking him

with a friendly smile. In the case of a qualitative interview of longer duration,

select the occasion for departure more carefully. Assembling the papers for

putting them in the folder at the time of asking the final question sets the stage for

a final handshake, a thank-you and a good-bye. If the respondent desires to know

the result of the survey, note down his name and address so that a summary of the

result could be posted to him when ready.

viii. Editing

At the close of the interview, the interviewer must edit the schedule to

check that he has asked all the questions and recorded all the answers and that

there is no inconsistency between answers. Abbreviations in recording must be

replaced by full words. He must ensure that everything is legible. It is desirable to

record a brief sketch of his impressions of the interview and observational notes

on the respondent’s living environment, his attitude to the survey, difficulties, if

any, faced in securing his cooperation and the interviewer’s assessment of the

validity of the respondent’s answers.

b) What are the problems encountered in Interview?

Answer:

Interview Problems


SIKKIM MANIPAL UNIVERSITYIn personal interviewing, the researcher must deal with two major problems,

inadequate response, non-response and interviewer’s bias.

i) Inadequate response

Kahn and Cannel distinguish five principal symptoms of inadequate

response. They are:

- partial response, in which the respondent gives a relevant but incomplete

answer

- non-response, when the respondent remains silent or refuses to answer the

question

- irrelevant response, in which the respondent’s answer is not relevant to the

question asked

- inaccurate response, when the reply is biased or distorted and

- verbalized response problem, which arises on account of respondent’s

failure to understand a question or lack of information necessary for

answering it.

ii) Interviewer’s Bias

The interviewer is an important cause of response bias. He may resort to

cheating by ‘cooking up’ data without actually interviewing. The interviewers can

influence the responses by inappropriate suggestions, word emphasis, tone of

voice and question rephrasing. His own attitudes and expectations about what a

particular category of respondents may say or think may bias the data. Another

source of response of the interviewer’s characteristics (education, apparent social

status, etc) may also bias his answers. Another source of response bias arises from

interviewer’s perception of the situation, if he regards the assignment as

impossible or sees the results of the survey as possible threats to personal interests

or beliefs he is likely to introduce bias.

As interviewers are human beings, such biasing factors can never be

overcome completely, but their effects can be reduced by careful selection and

training of interviewers, proper motivation and supervision, standardization or

interview procedures (use of standard wording in survey questions, standard

instructions on probing procedure and so on) and standardization of interviewer

behaviour. There is need for more research on ways to minimize bias in the

interview.

iii) Non-response


SIKKIM MANIPAL UNIVERSITYNon-response refers to failure to obtain responses from some sample

respondents. There are many sources of non-response; non-availability, refusal,

incapacity and inaccessibility.

iv) Non-availability

Some respondents may not be available at home at the time of call. This

depends upon the nature of the respondent and the time of calls. For example,

employed persons may not be available during working hours. Farmers may not

be available at home during cultivation season. Selection of appropriate timing for

calls could solve this problem. Evenings and weekends may be favourable

interviewing hours for such respondents. If someone is available, then, line

respondent’s hours of availability can be ascertained and the next visit can be

planned accordingly.

v) Refusal

Some persons may refuse to furnish information because they are ill-

disposed, or approached at the wrong hour and so on. Although, a hardcore of

refusals remains, another try or perhaps another approach may find some of them

cooperative. Incapacity or inability may refer to illness which prevents a response

during the entire survey period. This may also arise on account of language

barrier.

vi) Inaccessibility

Some respondents may be inaccessible. Some may not be found due to

migration and other reasons. Non-responses reduce the effective sample size and

its representativeness.

vii)Methods and Aims of control of non-response

Kish suggests the following methods to reduce either the percentage of

non-response or its effects:

1) Improved procedures for collecting data are the most obvious remedy for

non-response. Improvements advocated are (a) guarantees of anonymity, (b)

motivation of the respondent to co-operate (c) arousing the respondents’

interest with clever opening remarks and questions, (d) advance notice to the

respondents.

2) Call-backs are most effective way of reducing not-at-homes in personal

interviews, as are repeated mailings to no-returns in mail surveys.


SIKKIM MANIPAL UNIVERSITY3) Substitution for the non-response is often suggested as a remedy. Usually this

is a mistake because the substitutes resemble the responses rather than the

non-responses. Nevertheless, beneficial substitution methods can sometimes

be designed with reference to important characteristics of the population. For

example, in a farm management study, the farm size is an important variable

and if the sampling is based on farm size, substitution for a respondent with a

particular size holding by another with the holding of the same size is

possible.

Attempts to reduce the percentage or effects on non-responses aim at

reducing the bias caused by differences on non-respondents from respondents. The

non-response bias should not be confused with the reduction of sampled size due to

non-response. The latter effect can be easily overcome, either by anticipating the

size of non-response in designing the sample size or by compensating for it with a

supplement. These adjustments increase the size of the response and the sampling

precision, but they do not reduce the non-response percentage or bias.

3.

a) What are the various steps in processing of data?

Answer:

The various steps in processing of data may be stated as:

Identifying the data structures

Editing the data

Coding and classifying the data

Transcription of data

Tabulation of data.

Objectives:

After studying this lesson you should be able to understand:

Checking for analysis

Editing

Coding

Classification

Transcription of data

Tabulation

Construction of Frequency Table


SIKKIM MANIPAL UNIVERSITY Components of a table

Principles of table construction

Frequency distribution and class intervals

Graphs, charts and diagrams

Types of graphs and general rules

Quantitative and qualitative analysis

Measures of central tendency

Dispersion

Correlation analysis

Coefficient of determination

- Checking for Analysis

In the data preparation step, the data are prepared in a data format, which

allows the analyst to use modern analysis software such as SAS or SPSS. The major

criterion in this is to define the data structure. A data structure is a dynamic collection

of related variables and can be conveniently represented as a graph where nodes are

labelled by variables. The data structure also defines and stages of the preliminary

relationship between variables/groups that have been pre-planned by the researcher.

Most data structures can be graphically presented to give clarity as to the frames

researched hypothesis. A sample structure could be a linear structure, in which one

variable leads to the other and finally, to the resultant end variable.

The identification of the nodal points and the relationships among the nodes

could sometimes be a complex task than estimated. When the task is complex, which

involves several types of instruments being collected for the same research question,

the procedures for drawing the data structure would involve a series of steps. In

several intermediate steps, the heterogeneous data structure of the individual data sets

can be harmonized to a common standard and the separate data sets are then

integrated into a single data set. However, the clear definition of such data structures

would help in the further processing of data.

- Editing

The next step in the processing of data is editing of the data instruments.

Editing is a process of checking to detect and correct errors and omissions. Data

editing happens at two stages, one at the time of recording of the data and second at

the time of analysis of data.


SIKKIM MANIPAL UNIVERSITY- Data Editing at the Time of Recording of Data

Document editing and testing of the data at the time of data recording is done

considering the following questions in mind.

Do the filters agree or are the data inconsistent?

Have missing values been set to values, which are the same for all research questions?

Have variable descriptions been specified?

Have labels for variable names and value labels been defined and written?

All editing and cleaning steps are documented, so that, the redefinition of

variables or later analytical modification requirements could be easily incorporated into

the data sets.

- Data Editing at the Time of Analysis of Data

Data editing is also a requisite before the analysis of data is carried out. This

ensures that the data is complete in all respect for subjecting them to further analysis.

Some of the usual check list questions that can be had by a researcher for editing data sets

before analysis would be:

Is the coding frame complete?

Is the documentary material sufficient for the methodological description of the

study?

Is the storage medium readable and reliable.

Has the correct data set been framed?

Is the number of cases correct?

Are there differences between questionnaire, coding frame and data?

Are there undefined and so-called wild codes?

Comparison of the first counting of the data with the original documents of the

researcher.

The editing step checks for the completeness, accuracy and uniformity of the data

as created by the researcher.

Completeness: The first step of editing is to check whether there is an answer to all the

questions/variables set out in the data set. If there were any omission, the researcher

sometimes would be able to deduce the correct answer from other related data on the

same instrument. If this is possible, the data set has to rewritten on the basis of the new

information. For example, the approximate family income can be inferred from other

answers to probes such as occupation of family members, sources of income, approximate

spending and saving and borrowing habits of family members etc. If the information is


SIKKIM MANIPAL UNIVERSITYvital and has been found to be incomplete, then the researcher can take the step of

contacting the respondent personally again and solicit the requisite data again. If none of

these steps could be resorted to the marking of the data as missing must be resorted to.

Accuracy: Apart from checking for omissions, the accuracy of each recorded answer

should be checked. A random check process can be applied to trace the errors at this step.

Consistency in response can also be checked at this step. The cross verification to a few

related responses would help in checking for consistency in responses. The reliability of

the data set would heavily depend on this step of error correction. While clear

inconsistencies should be rectified in the data sets, fact responses should be dropped from

the data sets.

Uniformity: In editing data sets, another keen lookout should be for any lack of

uniformity, in interpretation of questions and instructions by the data recorders. For

instance, the responses towards a specific feeling could have been queried from a positive

as well as a negative angle. While interpreting the answers, care should be taken as a

record the answer as a positive question response or as negative question response in all

uniformity checks for consistency in coding throughout the questionnaire/interview

schedule response/data set.

The final point in the editing of data set is to maintain a log of all corrections that have

been carried out at this stage. The documentation of these corrections helps the researcher

to retain the original data set.

- Coding

The edited data are then subject to codification and classification. Coding

process assigns numerals or other symbols to the several responses of the data set. It

is therefore a pre-requisite to prepare a coding scheme for the data set. The

recording of the data is done on the basis of this coding scheme.

The responses collected in a data sheet varies, sometimes the responses could

be the choice among a multiple response, sometimes the response could be in terms

of values and sometimes the response could be alphanumeric. At the recording stage

itself, if some codification were done to the responses collected, it would be useful

in the data analysis. When codification is done, it is imperative to keep a log of the

codes allotted to the observations. This code sheet will help in the identification of

variables/observations and the basis for such codification.

The first coding done to primary data sets are the individual observation

themselves. This responses sheet coding gives a benefit to the research, in that, the

verification and editing of recordings and further contact with respondents can be SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143

SIKKIM MANIPAL UNIVERSITYachieved without any difficulty. The codification can be made at the time of

distribution of the primary data sheets itself. The codes can be alphanumeric to keep

track of where and to whom it had been sent. For instance, if the data consists of

several public at different localities, the sheets that are distributed in a specific

locality may carry a unique part code which is alphabetic. To this alphabetic code, a

numeric code can be attached to distinguish the person to whom the primary

instrument was distributed. This also helps the researcher to keep track of who the

respondents are and who are the probable respondents from whom primary data

sheets are yet to be collected. Even at a latter stage, any specific queries on a

specific responses sheet can be clarified.

The variables or observations in the primary instrument would also need

codification, especially when they are categorized. The categorization could be on a

scale i.e., most preferable to not preferable, or it could be very specific such as

Gender classified as Male and Female. Certain classifications can lead to open

ended classification such as education classification, Illiterate, Graduate,

Professional, Others. Please specify. In such instances, the codification needs to be

carefully done to include all possible responses under Others, please specify. If the

preparation of the exhaustive list is not feasible, then it will be better to create a

separate variable for the Others please specify category and records all responses as

such.

Numeric Coding: Coding need not necessarily be numeric. It can also be

alphabetic. Coding has to be compulsorily numeric, when the variable is subject to

further parametric analysis.

Alphabetic Coding: A mere tabulation or frequency count or graphical

representation of the variable may be given in an alphabetic coding.

Zero Coding: A coding of zero has to be assigned carefully to a variable. In many

instances, when manual analysis is done, a code of 0 would imply a no response

from the respondents. Hence, if a value of 0 is to be given to specific responses in

the data sheet, it should not lead to the same interpretation of non response. For

instance, there will be a tendency to give a code of 0 to a no, then a different coding

than 0 should be given in the data sheet. An illustration of the coding process of

some of the demographic variables is given in the following table.

Question Variable Response categories Code SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143


Number observation

1.1 Organisation Private Pt

Public Pb

Government Go

3.4 Owner of Vehicle Yes 2

No 1

4.2 Vehicle performs Excellent 5

Good 4

Adequate 3

Bad 2

Worst 1

5.1 Age Up to 20 years 1

21-40 years 2

40-60 years 3

5.2 Occupation Salaried S

Professional P

Technical T

Business B

Retired R

Housewife H

Others =

= Could be treated as a separate variable/observation and the actual response could be

recorded. The new variable could be termed as other occupation

The coding sheet needs to be prepared carefully, if the data recording is not done by

the researcher, but is outsourced to a data entry firm or individual. In order to enter the data in

the same perspective, as the researcher would like to view it, the data coding sheet is to be

prepared first and a copy of the data coding sheet should be given to the outsourcer to help in

the data entry procedure. Sometimes, the researcher might not be able to code the data from

the primary instrument itself. He may need to classify the responses and then code them. For

this purpose, classification of data is also necessary at the data entry stage.

- Classification

When open ended responses have been received, classification is

necessary to code the responses. For instance, the income of the respondent


SIKKIM MANIPAL UNIVERSITYcould be an open-ended question. From all responses, a suitable classification

can be arrived at. A classification method should meet certain requirements or

should be guided by certain rules.

First, classification should be linked to the theory and the aim of the

particular study. The objectives of the study will determine the dimensions

chosen for coding. The categorization should meet the information required to

test the hypothesis or investigate the questions.

Second, the scheme of classification should be exhaustive. That is,

there must be a category for every response. For example, the classification of

martial status into three category viz., married Single and divorced is not

exhaustive, because responses like widower or separated cannot be fitted into

the scheme. Here, an open ended question will be the best mode of getting the

responses. From the responses collected, the researcher can fit a meaningful and

theoretically supportive classification. The inclusion of the classification Others

tends to fill the cluttered, but few responses from the data sheets. But others

categorization has to carefully used by the researcher. However, the other

categorization tends to defeat the very purpose of classification, which is

designed to distinguish between observations in terms of the properties under

study. The classification others will be very useful when a minority of

respondents in the data set give varying answers. For instance, the reading habits

of newspaper may be surveyed. The 95 respondents out of 100 could be easily

classified into 5 large reading groups while 5 respondents could have given a

unique answer. These given answer rather than being separately considered

could be clubbed under the others heading for meaningful interpretation of

respondents and reading habits.

Third, the categories must also be mutually exhaustive, so that each

case is classified only once. This requirement is violated when some of the

categories overlap or different dimensions are mixed up.

The number of categorization for a specific question/observation at the

coding stage should be maximum permissible since, reducing the categorization

at the analysis level would be easier than splitting an already classified group of

responses. However the number of categories is limited by the number of cases

and the anticipated statistical analysis that are to be used on the observation.

- Transcription of Data


SIKKIM MANIPAL UNIVERSITYWhen the observations collected by the researcher are not very large,

the simple inferences, which can be drawn from the observations, can be

transferred to a data sheet, which is a summary of all responses on all

observations from a research instrument. The main aim of transition is to

minimize the shuffling proceeds between several responses and several

observations. Suppose a research instrument contains 120 responses and the

observations has been collected from 200 respondents, a simple summary of

one response from all 200 observations would require shuffling of 200 pages.

The process is quite tedious if several summary tables are to be prepared from

the instrument. The transcription process helps in the presentation of all

responses and observations on data sheets which can help the researcher to

arrive at preliminary conclusions as to the nature of the sample collected etc.

Transcription is hence, an intermediary process between data coding and data

tabulation.

- Methods of Transcription

The researcher may adopt a manual or computerized transcription.

Long work sheets, sorting cards or sorting strips could be used by the

researcher to manually transcript the responses. The computerized

transcription could be done using a data base package such as spreadsheets,

text files or other databases.

The main requisite for a transcription process is the preparation of the

data sheets where observations are the row of the database and the

responses/variables are the columns of the data sheet. Each variable should be

given a label so that long questions can be covered under the label names. The

label names are thus the links to specific questions in the research instrument.

For instance, opinion on consumer satisfaction could be identified through a

number of statements (say 10); the data sheet does not contain the details of

the statement, but gives a link to the question in the research instrument

though variable labels. In this instance the variable names could be given as

CS1, CS2, CS3, CS4, CS5, CS6, CS7, CS8, CS9 and CS10. The label CS

indicating Consumer satisfaction and the number 1 to 10 indicate the

statement measuring consumer satisfaction. Once the labelling process has

been done for all the responses in the research instrument, the transcription of

the response is done.

- Manual Transcription


SIKKIM MANIPAL UNIVERSITYWhen the sample size is manageable, the researcher need not use any

computerization process to analyze the data. The researcher could prefer a

manual transcription and analysis of responses. The choice of manual

transcription would be when the number of responses in a research instrument

is very less, say 10 responses, and the numbers of observations collected are

within 100. A transcription sheet with 100x50 (assuming each response has 5

options) row/column can be easily managed by a researcher manually. If, on

the other hand the variables in the research instrument are more than 40 and

each variable has 5 options, it leads to a worksheet of 100x200 sizes which

might not be easily managed by the researcher manually. In the second

instance, if the number of responses is less than 30, then the manual worksheet

could be attempted manually. In all other instances, it is advisable to use a

computerized transcription process.

- Long Worksheets

Long worksheets require quality paper; preferably chart sheets, thick

enough to last several usages. These worksheets normally are ruled both

horizontally and vertically, allowing responses to be written in the boxes. If

one sheet is not sufficient, the researcher may use multiple rules sheets to

accommodate all the observations. Heading of responses which are variable

names and their coding (options) are filled in the first two rows. The first

column contains the code of observations. For each variable, now the

responses from the research instrument are then transferred to the worksheet

by ticking the specific option that the observer has chosen. If the variable

cannot be coded into categories, requisite length for recording the actual

response of the observer should be provided for in the work sheet.

The worksheet can then be used for preparing the summary tables or

can be subjected to further analysis of data. The original research instrument

can be now kept aside as safe documents. Copies of the data sheets can also be

kept for future references. As has been discussed under the editing section, the

transcript data has to be subjected to a testing to ensure error free transcription

of data.

A sample worksheet is given below for reference.



Transcription can be made as and when the edited instrument is ready for processing.

Once all schedules/questionnaires have been transcribed, the frequency tables can be

constructed straight from worksheet. Other methods of manual transcription include adoption

of sorting strips or cards.

In olden days, data entry and processing were made through mechanical and semi

auto-metric devices such as key punch using punch cards. The arrival of computers has

changed the data processing methodology altogether.

- Tabulation

The transcription of data can be used to summarize and arrange the

data in compact form for further analysis. The process is called tabulation.

Thus, tabulation is a process of summarizing raw data displaying them on

compact statistical tables for further analysis. It involves counting the number

of cases falling into each of the categories identified by the researcher.

Tabulation can be done manually or through the computer. The choice

depends upon the size and type of study, cost considerations, time pressures

and the availability of software packages. Manual tabulation is suitable for

small and simple studies.

b) How is data editing is done at the Time of Recording of Data?

Answer:

Data Editing at the Time of Recording of Data

Document editing and testing of the data at the time of data recording is done

considering the following questions in mind.

Do the filters agree or are the data inconsistent?

Have missing values been set to values, which are the same for all research questions?

Have variable descriptions been specified?

Have labels for variable names and value labels been defined and written?

All editing and cleaning steps are documented, so that, the redefinition of variables or later

analytical modification requirements could be easily incorporated into the data sets.


http://resources.smude.edu.in/slm/wp-content/uploads/2010/09/clip-image003.jpg

SIKKIM MANIPAL UNIVERSITY4.

a) What are the fundamental of frequency Distribution?

Answer:

Frequency Distribution

Variables that are classified according to magnitude or size are often arranged

in the form of a frequency table. In constructing this table, it is necessary to determine

the number of class intervals to be used and the size of the class intervals.

A distinction is usually made between continuous and discrete variables. A

continuous variable has an unlimited number of possible values between the lowest

and highest with no gaps or breaks. Examples of continuous variable are age, weight,

temperature etc. A discrete variable can have a series of specified values with no

possibility of values between these points. Each value of a discrete variable is distinct

and separate. Examples of discrete variables are gender of persons (male/female)

occupation (salaried, business, profession) car size (800cc, 1000cc, 1200cc)

In practice, all variables are treated as discrete units, the continuous variables

being stated in some discrete unit size according to the needs of a particular situation.

For example, length is described in discrete units of millimetres or a tenth of an inch.

b) What are the types and general rules for graphical representation of data?

Answer:

The most commonly used graphic forms may be grouped into the following

categories:

i. Line Graphs or Charts

ii. Bar Charts

iii. Segmental presentations.

iv. Scatter plots

v. Bubble charts

vi. Stock plots

vii. Pictographs

viii. Chesnokov Faces

The general rules to be followed in graphic representations are:

a. The chart should have a title placed directly above the chart.

b. The title should be clear, concise and simple and should describe the nature

of the data presented.

c. Numerical data upon which the chart is based should be presented in an

accompanying table.


SIKKIM MANIPAL UNIVERSITYd. The horizontal line measures time or independent variable and the vertical

line the measured variable.

e. Measurements proceed from left to right on the horizontal line and from

bottom to top on the vertical.

f. Each curve or bar on the chart should be labelled.

g. If there are more than one curves or bar, they should be clearly

differentiated from one another by distinct patterns or colours.

h. The zero point should always be represented and the scale intervals should

be equal.

i. Graphic forms should be used sparingly. Too many forms detract rather than

illuminating the presentation.

j. Graphic forms should follow and not precede the related textual discussion.

5. Strictly speaking, would case studies be considered as scientific research? Why

or why not?

Answer:

Case studies are a tool for discussing scientific integrity. Although one of the most

frequently used tools for encouraging discussion, cases are only one of many possible tools.

Many of the principles discussed below for discussing case studies can be generalized to other

approaches to encouraging discussion about research ethics.

Cases are designed to confront readers with specific real-life problems that do not

lend themselves to easy answers. Case discussion demands critical and analytical skills and,

when implemented in small groups, also fosters collaboration (Pimple, 2002). By providing a

focus for discussion, cases help trainees to define or refine their own standards, to appreciate

alternative approaches to identifying and resolving ethical problems, and to develop skills for

analyzing and dealing with hard problems on their own. The effective use of case studies is

comprised of many factors, including:

appropriate selection of case(s) (topic, relevance, length, complexity)

method of case presentation (verbal, printed, before or during discussion)

format for case discussion (Email or Internet-based, small group, large group)

leadership of case discussion (choice of discussion leader, roles and responsibilities for

discussion leader)

outcomes for case discussion (answers to specific questions, answers to general questions,

written or verbal summaries)

Research methods don't seem so intimidating when you're familiar with the

terminology. This is important whether you're conducting evaluation or merely reading


SIKKIM MANIPAL UNIVERSITYarticles about other studies to incorporate in your program. To help with understanding, here

are some basic definitions used.

Variable: Characteristics by which people or things can be described. Must have more than

one level; in other words, to be able to change over time for the same person/object, or from

person to person, or object to object. Some variables, called attributes, cannot be manipulated

by the researcher (e.g., socioeconomic status, IQ score, race, gender, etc.). Some variables can

be manipulated but are not in a particular study. This occurs when subjects self-select the

level of the independent variable, or the level is naturally occurring (as with ex post facto

research).

Manipulation: Random assignment of subjects to levels of the independent variable

(treatment groups).

Independent variable: The treatment, factor, or presumed cause that will produce a change

in the dependent variable. This is what the experimenter tries to manipulate. It is denoted as

"X" on the horizontal axis of a graph.

Dependent variable: The presumed effect or consequence resulting from changes in the

independent variable. This is the observation made and is denoted by "Y" on the vertical axis

of a graph. The score of "Y" depends on the score of "X."

Population: The complete set of subjects that can be studied: people, objects, animals, plants,

etc.

Sample: A subset of subjects that can be studied to make the research project more

manageable. There are a variety of ways samples can be taken. If a large enough random

samples are taken, the results can be statistically similar to taking a census of an entire

population--with reduced effort and cost.

Case Study:

A case study is conducted for similar purpose as the above but is usually done with a smaller sample size for

more in-depth study. A case study often involves direct observation or interviews with single subjects or single

small social units such as a family, club, school classroom, etc. This is typically considered qualitative research.

Purpose: Explain or Predict

Type of Research to Use: Relational Study

In a relational study you start with a research hypothesis, that is, is what you're trying to "prove."

Examples of research hypotheses for a relational study:

The older the person, the more health problems he or she encounters.

4-H members attending 4-H summer camp stay enrolled in 4-H longer.SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143

SIKKIM MANIPAL UNIVERSITY The greater the number of money management classes attended, the greater the amount of

annual savings achieved.

Types of relational studies include correlational studies and ex post facto studies.

Correlational Study:

A correlational study compares two or more different characteristics from the same group of people

and explains how two characteristics vary together and how well one can be predicted from knowledge of the

other.

A concurrent correlational study draws a relationship between characteristics at the same point in time.

For example, a student's grade point average is related to his or her class rank.

A predictive correlational study could predict a later set of data from an earlier set. For example, a

student's grade point average might predict the same student's grade point average during senior year. A

predictive correlational study could also use one characteristic to predict what another characteristic will be at

another time. For example, a student's SAT score is designed to predict college freshman grade point average.

Ex Post Facto (After the Fact) Study:

An ex post facto study is used when experimental research is not possible, such as when people have

self-selected levels of an independent variable or when a treatment is naturally occurring and the researcher

could not "control" the degree of its use. The researcher starts by specifying a dependent variable and then tries

to identify possible reasons for its occurrence as well as alternative (rival) explanations such confounding

(intervening, contaminating, or extraneous) variables are "controlled" using statistics.

This type of study is very common and useful when using human subjects in real-world situations and

the investigator comes in "after the fact." For example, it might be observed that students from one town have

higher grades than students from a different town attending the same high school. Would just "being from a

certain town" explain the differences? In an ex post facto study, specific reasons for the differences would be

explored, such as differences in income, ethnicity, parent support, etc. It is important to recognize that, in a

relational study, "cause and effect" cannot be claimed. All that can be claimed is that that there is a relationship

between the variables.

For that matter, variables that are completely unrelated could, in fact, vary together due to nothing

more than coincidence. That is why the researcher needs to establish a plausible reason (research hypothesis) for

why there might be a relationship between two variables before conducting a study. For instance, it might be

found that all football teams with blue uniforms won last week. There is no likely reason why the uniform color

had any relationship to the games' outcomes, and it certainly was not the cause for victory. Similarly, you must

be careful about claiming that your Extension program was the "cause" of possible results.

6.

a) Analyse the case study and descriptive approach to research?

Answer:

i) Case Study and descriptive approach to research:

Descriptive research, also known as statistical research, describes data and

characteristics about the population or phenomenon being studied. Descriptive

research answers the questions who, what, where, when and how...SANTOSH GOWDA.H Reg No.: 5210757283rd semester, Disha institute of management and technology Mobile No.: 9986840143

SIKKIM MANIPAL UNIVERSITYAlthough the data description is factual, accurate and systematic, the

research cannot describe what caused a situation. Thus, Descriptive research

cannot be used to create a causal relationship, where one variable affects another.

In other words, descriptive research can be said to have a low requirement for

internal 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 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 e.g. 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.

Descriptive research does not fit neatly into the definition of either

quantitative or qualitative research methodologies, but instead it can utilize

elements of both, often within the same study. The term descriptive research refers

to the type of research question, design, and data analysis that will be applied to a

given topic. Descriptive statistics tell what is, while inferential statistics try to

determine cause and effect.

A case study is a research method common in social science. It is based on

an in-depth investigation of a single individual, group, or event. Case studies may

be descriptive or explanatory. The latter type is used to explore causation in order

to find underlying principles. They may be prospective, in which criteria are

established and cases fitting the criteria are included as they become available, or

retrospective, in which criteria are established for selecting cases from historical

records for inclusion in the study.

Rather than using samples and following a rigid protocol (strict set of

rules) to examine limited number of variables, case study methods involve an in-

depth, longitudinal (over a long period of time) examination of a single instance or

event: a case. They provide a systematic way of looking at events, collecting data,

analyzing information, and reporting the results. As a result the researcher may

gain a sharpened understanding of why the instance happened as it did, and what

might become important to look at more extensively in future research. Case

studies lend themselves to both generating and testing hypotheses.


SIKKIM MANIPAL UNIVERSITYAnother suggestion is that case study should be defined as a research

strategy, an empirical inquiry that investigates a phenomenon within its real-life

context. Case study research means single and multiple case studies, can include

quantitative evidence, relies on multiple sources of evidence and benefits from the

prior development of theoretical propositions. Case studies should not be confused

with qualitative research and they can be based on any mix of quantitative and

qualitative evidence. Single-subject research provides the statistical framework for

making inferences from quantitative case-study data

b) Distinguish between research methods & research Methodology.

Answer:

Research Methods Research Methodology

Research methods are the various procedures,

schemes, algorithms, etc. used in research. All

the methods used by a researcher during a

research study are termed as research methods.

They are essentially planned, scientific and

value-neutral. They include theoretical

procedures, experimental studies, numerical

schemes, statistical approaches, etc. Research

methods help us collect samples, data and find a

solution to a problem. Particularly, scientific

research methods call for explanations based on

collected facts, measurements and observations

and not on reasoning alone. They ac- cept only

those explanations which can be verified by

experiments.

Research methodology is a systematic way to

solve a problem. It is a science of studying how

research is to be carried out. Essentially, the

procedures by which researchers go about their

work of describing, explaining and predicting

phenomena are called research methodology. It

is also defined as the study of methods by which

knowledge is gained. Its aim is to give the work

plan of research.


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