rm project iv-th sem

8/12/2019 RM Project IV-Th Sem

1/53

Project Topic: Processing of the Data

1

Chapter 1:Processing of the data and its various stages.

Q.1. Explain the concept of Processing of the Data and analyze in detail the

different stages in the Data Processing.

Ans1. Points of the answer:

1.1) Concept of the Data and the Types of the Data.1.2) Introduction to the Processing of the Data.1.3)

Various Stages in the Processing of the Data.

a) Editing.b) Coding.c) Classification.d) Tabulation.e) Transcription.f) Graphical Representation.

1.1) Concept of Data and Types of Data:Data plays a very important role in the research activity. Facts, information or the

premises systematically collected and presented properly for the purpose of drawing the

information is called as the data. Statistical information collected compiled and then

presented for the purpose of establishing relationship between the two variables can be

included in the data.

Data can be collected from the primary and the secondary sources. Primary sources refer

to the information obtained first hand by the researcher on the variables of the interest for


2/53


2

the specific purpose of the study. Secondary data refers to the second hand information

which gathered from the existing sources.

There are two types of the data namely Primary Data and the Secondary Data. The

Primary data are that which are collected afresh and for the first time and therefore it

happens to be original in the character. The secondary data are those which have already

been collected by someone else and which have been passed through the statistical

process. The researcher has to decide which type of the data is appropriate for his study

and accordingly he should select one of the methods for the data collection.

A researcher begins to collect the data only when the research problem is identified and

the research design has been prepared. The researcher has to decide which type of the

data he would be using for his study and he has to select the method accordingly.

For that he should first explore the secondary data available from the various sources and

then examine the possibility of using it for his studies. This is called as survey of the

literature. In several times he will find the secondary data inadequate, outdated and

unusable and hence realizes the need for the collecting the primary data.

1.2) Introduction to the Processing of the Data:

In any research project collection of the data is followed by the processing of the data and

also the analysis of the data. The Processing and the analysis of the data involves the


3/53


3

answers to the research problems. The processing of the data refers to the consolidation,

recasting, rearranging and the regrouping of the data so that the job analysis is made very

easy. The Analysis of the data refers to the seeing of the data in the light of the

hypothesis and the research questions and the prevailing theories and then drawing the

conclusions that are amenable to the theory formulation as possible.

Data processing is an intermediary stage of the work between the data collection and the

data analysis. The completed instruments of the data collection viz: interview

schedules/questionnaires/ data sheets field noted contain a vast mass of the data. They

cannot straight away provide the answers to the research questions. Like any other raw

materials they need processing. Data processing involves summarization of the data in

order to make them amenable to analyze.

The processing of the data requires advance planning at the stage of the planning of the

research design. The advance planning may cover such aspects as categorization of the

variables, and the preparation of the dummy tables. This should be done with reference to

the requirements of the testing the hypothesis/ investigation questions. This type of the

preplanning will help us in the better identification of the data needs and their adequate

coverage in the tools for the collection of the data.

Data processing consists of a number of stages which are as follows:

1) Editing.2) Classification.3) Coding.


4/53


4

4) Tabulation.5) Transcription.6) Graphical Representation.Data processing depends to a large extent on the nature of the data. It may be qualitative

or quantitative in the nature. If the data is in the verbal form then it has to be changed into

the numerical form for the better understanding. The main factor to be considered in the

processing of the data is the correlation of the nature of the data and the technique of the

data processing.

If a researcher is interested in studying the data of the two political parties then it may be

futile to attempt to quantify large quantities of the verbal data. Depending on the

objectives of the study and on the basis of the data a specific categories may be formed in

order to draw a systematic conclusions and comparative analysis.

Most of the researchers think that the data processing only is done only after the data is

collected completely and then they have to face certain problems these problems can be

avoided if there is a careful plan of the data processing is prepared as an integral part of

the research design. The plan may be based on the type and the number of the variables to

be studied, the complexity of the hypothesis, the number of the respondents and the

extent of the data to be collected.

If the data which is to be collected is very limited simple data processing may be done

manually. If the data which is to be collected is very large and complex the assistance of

the trained staff like the coders and the computers may be necessary. The planning


5/53


5

appears to be very simple but actually it is not in the absence of a well designed plan for

the data processing.

The organizing of the data is a very systematic arrangement of the data collection in order

to ensure its effective processing and the analysis.

1.3) Various Stages in the Processing of the Data:

The processing of the data is the process of Editing, Coding, Classifying, Tabulation,

Transcription and Graphical Representation of the Data for the purpose of the Data

analysis. The data analysis is needed to draw some conclusions and recommendations.

The following gives us a brief description of the various stages in the data processing.

Stages in the Data Processing.

1) Editing.2) Coding.3) Classification.4) Tabulation.1) Editing:This is the first stage in the processing of the data. This is the process in which the errors

if any are located and they are tried to be omitted and if they are found then the

corrections are made. Editing is needed when there is some inconsistency in the

responses which is entered in the questionnaire and also when the questionnaire contains

some partial or the vague answers which is given by the respondents.


6/53


6

Examples of Inconsistent or Vague Responses.

1) The Respondent has given the answers which are inconsistent with the other answers.The editor has to change the inconsistent answers or the responses so as to make it

consistent with the others. He has to use his judgment to find out the answers which is

correct and which one is inconsistent or incorrect.

2) The respondent may sometimes mark two answers instead of one answer to aparticular question. The editor has to judge which one is correct and which one is

incorrect. If it is difficult to judge the correctness of the given answers. At this

situation the editor may consider the answer as no information because the correct

answer is not given.

3) Sometimes the completed questionnaire may contain certain questions which are fakeor fictitious which may be due to the unethical interviewers. Also in the case of the

mail survey the respondents the respondents may arbitrary provide responses.

4) The changes which are made by the editor must be done by a separate ink preferablygreen ink or in pencil. The ink should not match with that of the interviewer of the

respondent.

Types of Editing:

1) Field Editing:Editing which is undertaken at the time of the field survey is called as the field editing. At

the time of the interview the interviewer may use several abbreviations due to the time

limitations. The abbreviations need to be spelt out fully later. The interviewer may also


7/53


7

go through the completed questionnaire to find out whether there is a need for completing

the partial or correcting the vague answers.

2) Central Editing:Editing which is done at the central office is called as the central editing. A single editor

should carry out the task because the consistency will be maintained. But in the case of

the large data two or more editors are needed. The multiple editors must be given proper

guidelines so that the work will be carried out properly. Sometimes the entire data may be

divided into two questionnaires and each part may be edited by separate editors.

Essential of Editing:

1) Completeness:The questionnaires must be checked properly. It should be seen that all the questions are

answered properly or not. If there are omissions then the editor may deduce proper

answers based on the other responses.

2) Accuracy:The editor should always see for the inconsistent answers which are given by the

respondents. The respondent may sometimes give misleading or the wrong answers

deliberately.

Respondents may be give misleading or the wrong answers deliberately.

1) Uniformity:


8/53


8

The editor should check whether the interviewees have interpreted the questions and the

instructions uniformity. The editor can also cross check the uniformity while going

through the completed questionnaire. For e.g the questions may have a scale of 1 to 5.

1 means Excellent and 5means poor. But an interviewer may interpret as 5 as excellent

and 1 means poor. In such a situation the responses would be incorrect. This problem can

be solved by giving the proper guidance to the interviewers.

Reliability:

The data collected must be up to date. The editor must discard the outdated data at the

time of the editing. Reliable and up-to-date data would help the interpreter to draw the

proper conclusions.

2) Coding:Coding is the process of assigning the codes or the symbols which may be numbers,

alphabets, alpha-numerical to the categories or the responses. Coding is necessary for the

tabulation and the analysis of the data. It is required especially when the sample size is

large and there is large number of the responses. Coding can be considered as an

important element of the classification.

Coding involves the following steps:

1) Specify the categories or the classes into which responses are to be classified.2) Allocate the individual codes to each category.3) Classification:


9/53


9

Classification refers to the grouping of the data under the different categories or the

classes. The categories may be in respect of the age, gender, education, area. With a

category there can be sub-categories. For instance, in the case of the gender there can be

males, and females. The males and the females can be further sub-divided according to

the age, income, education level.

Principles/ Guidelines of the coding / Classification:

1. Mutually Exclusive:2. Appropriateness.3. Exhaustive.1. Mutually Exclusive:The categories must be mutually exclusive. A specific case or the response must be

classified only once in one category only. For instance on the basis of the occupation one

may place the response of a particular respondent in a definite pre-determined category.

But the problem may arise if the respondent may belong to the two categories. For

instance the respondent may belong to the managerial occupation (full time) and the

professional or the consultant occupation (part time) or a given person may work as a

clerical staff (full time) and a student (part time). This problem can be solved by the

classifying the information or responses under the Principal Occupation Status

2. Appropriateness:The classification/coding must be appropriate to the research work. For instance, a

researcher studying about the brand loyalty of the readymade garments may then classify


10/53


10

the population in the certain groups which are appropriate to the survey. The senior

citizens and the kids may be ignored as they are not much loyal to the brands as far as the

readymade garments are concerned.

3. Exhaustive:The classification may be exhaustive in nature. There must be a separate category where

the responses can be fitted or placed. The respondent must belong to a certain category.

For instance if the classification is based on the students then there must be a category for

every class of the students. If the classification is done only on the basis of the arts,

commerce and science then the certain students may be excluded such as the engineering

students, management students, and the students belonging to the other professional or

the technical courses. Therefore there must be several classifications. But if there are too

many groups the researcher may include the isolated groups under the sinle category

called as the General Category.

4) Tabulation:It involves of the sorting of the data into the different categories and also involves the

counting the number of the cases/responses that belong to the each category. The

tabulation can be universe or bi-variate / multivariate. If only one variable is involved in

the tabulation viz Boys then it is called as the univariate tabulation e.g 10 out of 20 boys

(50%) have responded to a particular question.


11/53


11

If the two or more variables are involved in tabulating the data it is called as the bivariate

or the multivariate tabulation. Foe e.g if five boys are in the age group of 10 to 14 and

six boys in the age group of 15 to 19 have responded positively.

Tabulation can be drawn manually or mechanically or partly manual and partly

mechanical. Number of the tabulations depends on the variables, number of respondents.

If the number of the variables are few and the sample size is limited, then the tabulation

can be done manually, otherwise, with the help of the computers or the mechanically.

Importance of the Tabulation:

1) Tabulation as a part of the statistical process helps to arrange the raw data in the formof the statistical tables. This enables to analyze and to interpret the data easily and

effectively.Tabulation is a connecting link between the organization of the data and

its interpretation. If the tabulation is not done properly it will affect both the earlier

and the subsequent research process. In the absence of the tabulation it is difficult to

apply statistical techniques.Tabulation helps the researcher to determine and

communicate his findings in a form which can be understood by a common man.

Principles of the Tabulation.

1) Every table should have a clear concise and a suitable title so as to make the tableintelligible without referring to the text. Such title should be placed just above the

body of the table.

2) Every table should be given a distinct number to facilitate ready reference.3) The columns headings and the row headings of the table should be clear and brief.


12/53


12

Chapter 2: Transcription and Graphical Representation.

Q.2. Enumerate in detail the Transcription and the Graphical

Representation.

Ans.2. Points of the answer:

2.1) Concept of Transcription.

2.2) Methods of Tabulation.

2.3) Concept of Graphical Representation.

2.4) Types of Graphs.

2.5) General Rules in Graphical Representation.

2.1) Concept of Transcription:

The tabulation can directly be made from the schedules if there are very few schedules to

be tabulated and are to be processed. On the other hand the direct tabulation from the

edited scheduled/questionnaires is very difficult if the nimber of the schedules and the

number of the responses are very large.

Suppose an interview schedule contains 180 responses requiring tabulation to be done

and 210 simple and cross tables are to be constructed then each schedule has to be

handled at least 210 times for the tabulation. This will always result in the mutilation of

the schedule and the omissions and the commissions of the may easily occur in the

tabulations . In order to avoid these drawbacks data contained in the schedules/questions

are transferred to another material for the purpose of the tabulation. This intermediary

process is called as the transcription.


13/53


13

2.2.)Methods of the Tabulations:

(A) Manual Methods:

1. Listing or List and Tally Method.2. Card Sort and Count Method.3. Strip Method.4. Punch Card Method.1. Listing or the List method and Tally method:In this method a long size double foolscap size or a map drawing size is used. On this

sheet many columns are drawn and on the top of each of the column the code number

of the question is entered and the responses are entered in the rows. In the first

column the code number of the respondent is entered. In each column the code no of

the response of the respondent to the concerned question is entered. For each question

the no of the entries with a code no will be the frequency of a particular answer. If

more pages are used then every page is totaled. Generally single page is used. This is

easier for the smaller survey involving few respondents and a few tables.

2. Card Sort and Count Method:In this method a thick card with columns printed on the edges is used for each

questionnaire schedule. Each column has a number. Therefore allot code numbers for

each questionnaires/ item/ variable. Enter the code number or the value of the

response in the concerned column. Almost 40 column can be printed on the each side.

Thus response for the total of 80 questions/items variables can be entered. This


14/53


14

method facilitates easy tabulation. In each fact the response in the relevant column is

ascertained and the cards pertaining to a category are sorted out. Thus the cards

pertaining to the each category in a table are segregated. Then the number of the cards

in the each category is counted and frequently ascertained. For sorting out the cards

chalk piece boxes are used. The main advantage of this method is easy handling.

However the number of the items exceed 80 this method is not useful.

3. Strip Method:The long strips of 1 inch are used in this method. Each strip has 160 columns printed

on the each side. Thus the responses relating to the 320 items can be recorded in one

strip. The strip can also be rolled and made easy for the purpose of the handling. The

method of handling is the same as for the cards. Strips are very useful for the big

projects with a large number of the items.

4. Punch Card Method:This method is used in computers. Each card numbers 0 to 80 for the column and 0 to

9 for the rows. Thus the data relating to the items can be recorded in easy response

can be recorded in a single digit. Against each column the appropriate response is

number is punched. For the responses with more than one digit say, income the

required number of the columns may be used. It the number of the columns exceeds

that which can be used for each respondent, more than one card can be used.

However the direct punching of the cards would be possible only when the

questionnaire is precoded.


15/53


15

(B)Mechanical Methods:

1. Magnetic Tapes.

2. Floppy Disks.

3. Compact Disks.

1. Magnetic Tapes:

When we use a computer is used for the processing of the research data then punched

card are no longer in the use. They are replaced by the magnetic tapes and or the

disks. The data can be directly be key bound or it can be punched on the tapes or the

disks. It is a plastic ribbon that is coated on the one side with a non oxide or some

other material that can be magnetized. It may be in a large reel or a small cartage. The

tiny invisible spots are recorded by the electronic pulses on the coated side of the

tape. This tape can be crashed and can be reused also.

2. Floppy Disks:

It is another device that is used as an input medium. Data are keyed directly on to the

floppy disk. It is made out of the flexible plastic material. The plastic base is coated

with an iron oxide recording substance that is similar to the material applied to the

plastic ribbon of a magnetic tape. Data are recorded as tiny invisible magnetic sports

on a coated side. Like magnetic tape a disk is inexpensive and can be crashed and

reused many times.

3. Compact Disks:


16/53


16

This is the most modern and commonly used input and the output medium to record

the data. It consists of a plastic body layered with chemicals which has an iron oxide

layers. The data is written on these medium using LASER beams. This is the safest

method of inputting and presenting data. Its capacity ranges from 700 MB to 900 MB

depending upon the properties.

2.3) Concept of the Graphical Presentation:

Graphical presentation involves the use of the graphics, charts and the other pictorial

devices. These forms and devices reduce the large masses of the statistical data to a

form that can be quickly understood at a glance. The meaning of the figures in the

tabular form may be difficult for the mind to grasp and to retain. In presenting the

statistical data of the frequency distributions and the statistical computations it is

desirable to use the appropriate forms of the graphs.

Properl y constructed graphs and the char ts relieve the mind if the burdensome

detai ls by portraying the facts concisely, logi cally and simple.

By emphasizing new and the significant relationships are very useful in discovering

new facts and in developing hypothesis.

The device of the graphic representation is particularly useful when the prospective

readers are non-technical people or the general public. It is even useful to the

technical people for dramatizing the certain points about the data for the important

points which can be more effective captured in the pictures than in the tables.

However the graphics forms are not substitutes for the tables but are the additional

devices.


17/53


17

The graphical representation must be planned with the utmost care and diligence.

Graphic forms which are used should be very simple, clear, and accurate and also be

appropriate to the data. In planning this work the following questions must be

considered.

What is the purpose of the Diagram?

What facts can be emphasized?

What is the educational level of the audience?

How much time is available for the preparation of the chart?

What kind of the chart will portray the data most clearly and accurately?

2.4.)Types of the Graphs:

1. Line Graphs.

2. Bar Charts.

3. Segmental Representations.

4. Pictographs.

2.5.)General Rules:

The general Rules to be followed in the graphical representation are as follows:

1) The chart should have a title placed directly above the chart.2) The title should be very clear, concise, and simple and should describe the nature

of the data presented.

3) Numerical Data upon which the chart is based should be presented in anaccompanying table.

4) The horizontal line measures time or independent variable and the vertical line themeasured variable.


18/53


18

5) Measurements proceed from left to the right on the horizontal line, and frombottom to the top on the vertical line.

6) Each curve or the bar on the chart should be labeled.7) If there is more than one curve or the bars, they should be clearly differentiated

from one another by distinct patterns or the colours.

8) The zero points should always be represented and the scale intervals should beequal.

Chapter 3: Analysis of the Data.

Q.3. What is Analysis of the Data? Discuss in detail its purpose,

Characteristics, and the various types of the analysis of the Data.


3.1.) Concept of the Data Analysis.

3.2.) Definition of the Processing of the Data and Analysis of the Data.


19/53


19

3.3.) Purpose of the Data Analysis.

3.4.) Characteristics of the Analysis of the Data.

3.5.) Type of the Analysis of the Data.

3.1.) Concept of the Data Analysis:

The analysis of the data is the most skilled task in the research process. It is

dependent upon the researchers own judgment and the skill. Analysis means a

critical examination of the assembled and the grouped data for the studying the

characteristics of the object under the study and for the determining the patterns of the

relationships among the variables relating to it. Both the quantitative and the non-

quantitative methods are used.

The Analysis of the data is the most skilled task of all the stages of the research work.

It is the task which demands the researchers own judgment and the skill. It should be

done by the researcher himself always. A correct analysis needs familiarity with the

background of the survey and all the stages of the research. The analysis does not

necessarily be the statistical one. Quantitative and the non-quantitative methods of the

analysis can be done.

The steps followed in the analysis of the data will vary on the basis of the type of the

study. A part of the analysis is a matter of the working out the statistical distribution,

constructing diagrams, calculating simple measurements like the averages, measures


20/53


20

of the dispersions, percentages, correlations. Hence the statistical analysis forms the

part of the survey analysis in the theory of the research.

The problems raised by the analysis of the Data are directly raised by the complexity

of the hypothesis. Problems of the Data analysis involve all the questions raised in the

research design, for the secondary analysis to involve the designing and the

redesigning of the substitutes for the controlled experiment.

After the Data has been collected from the respective sample the next step is to

analyze the data which has been collected to test the research hypothesis. However

before analyzing the data to test the hypothesis the next step is to that some

preliminary steps which are needed to be completed. This will help to ensure that the

data are reasonably good and assumed to be of the good quality for the further

analysis.

The four steps are as follows:

1) Getting ready for the analysis.2) Getting a feel for the Data.3) Testing of the Goodnesss of the Data.4) Testing of the Hypothesis.Some writers of the subject of the Research Methodology have made the clear

distinction between the Processing of the Data and the Analysis of the Data.


21/53


21

Processing of the Data refers to concentrating, recasting of the data, and dealing

with the data in such a way that they become as amenable to analyze as possible.

Analysis of the Data may be considered as having a reference to the process of

viewing of the Data in the light of the hypothesis or the research questions, as

also, the prevailing theories and then drawing the conclusions that will make

some contributions in the matter of the theory formulation or the modifications.

The dividing line between the analysis of the data and the interpretation of the Data is

very difficult to draw. These two are symbiotic and they merge imperfectly. If the

analysis involves organizing the data in a particular manner it is mostly the

interpretative ideas that govern the task. If the end product of the analysis is the

setting up of the certain general conclusions then what these conclusions really mean

and reflect is the bare minimum that the researcher must feel obliged to know?

Interpretation is the way of the knowledge. Thus the task of the analysis can hardly be

said to be complete without the interpretation coming to illuminate the results. Proper

analysis of the data requires a familiarity with the background of the survey and with

all its stages.

The steps in the analysis of the Data depends upon the type of the study. In the case

there is a set of clearly formulated hypothesis then the each hypothesis can be seen as

a work prescribing a certain action to be taken vis a vis the data. The more specific

the hypothesis the more specific is the action. In such a study the analysis of the Data

is almost completely a mechanical procedure. The Part of the Analysis is working out


22/53


22

the statistical distribution, construction of the Diagrams and the calculations of the

simple measures like the averages, measures of the dispersions, percentages and the

correlations. Hence the statistical analysis forms the part of the survey analysis.

3.2.) Definition of the Processing of the Data and Analysis of the Data.

Processing of the Data r efers to concentr ating, recasting of the data, and dealing

with the data in such a way that they become as amenable to analyze as possible.

Analysis of the Data may be considered as having a reference to the process of

viewing of the Data in the li ght of the hypothesis or the research questions, as also,

the prevail ing theories and then drawing the conclusions that wi ll make some

contr ibutions in the matter of the theory formulation or the modifi cations.

Analysis of the Data do not make such a precise differentiation. Analysis is a

comprehensive process which involves processing.

3.3) Purpose of the Data Analysis:

The Statistical Analysis of the Data serves the following major purposes:

1) It summarizes the large mass of the Data into the data which can be understood andwhich is meaningful form. This will help in the reducing the data and it will facilitate

the further analysis.

2) Statistics make the exact description possible. For eg. when we say that theeducational level of the people in the X district is very high then the description is not

very specific but when the statistical measures like the percentages of the literate


23/53


23

people among the males and the females, the percentage of the degree holders among

the males and the females, and the like are available then the description becomes

exact.

3) Statistical analysis facilitates identification of the casual factors underlying complexphenomena. What are the factors which determine a variable like labour productivity

or the academic performance of the students? What are the relative contributions of

the causative factors? Answers to the questions can be obtained from the statistical

multivariate analysis.

4) Statistical analysis also helps making estimations or the generalizations from theresults of the sample surveys. This is another function of the inferential statistics.

Sample statistical based on the probability samples may give good estimates of a

particular population parameters. Any estimate will deviate from the true value due to

the sampling error. The process of the statistical inference enables us to evaluate the

accuracy of the estimates.

5) The statistical analysis is useful for the assessing the significance of the specificsample results under the assumed population conditions.

6) Statistical analysis aids in the drawing of the reliable inferences from theobservations. Data are collected and analyzed in order to predict or make the

inferences about the situations that have not been measured in full. The Statistical

prediction is one of the functions in the inferential statistics.


24/53


24

3.4) Characteristics of the Analysis of the Data:

The following are the main characteristics of the Data Analysis.:

1) The Analysis of the Data is one of the most important aspects of the research. Since itis a highly skilled and technical job it should be carried out by the researcher himself

or under the close observation of the guide. It demands a deep and intense knowledge

on the part of the researcher about the data to be analyzed. The researcher should

also possess judgment skill ability of the generalizations and should be familiar with

the background objects and the hypothesis of the study.

2) Data, facts and the figures are silent and they never speak for themselves but theyhave complexities. It is through the systematic analysis that the important

characteristics which are hidden in the data are brought out and the valid

generalizations are drawn. Analysis demands a thorough knowledge of ones data.

Without deep knowledge the analysis is considered to be aimless.. It is only by

organizing, analyzing and the interpreting the research data that we know their

important features, interrelationships and the cause effect relationships. The trends

and the sequences inherent in the phenomena are elaborated by the means of the

generalizations.

3) The function of the systematic analysis is to build an intellectual edifice in whichproperly sorted and shifted facts and the figures are placed in their appropriate

settings and the broader generalizations beyond the immediate contents of the facts

under study, consistent relationships or that general inferences can be drawn from

them the aim of a mature science.


25/53


25

4) The data to be analyzed and interpreted should be reproductive be really disposed tothe quantitative treatment and have a significance for the some systematic theory and

can be serve as a basis for the broader generalizations.

5) The steps envisaged in the analysis of the data will vary depending on the type of thestudy. A set of the clearly formulated hypothesis to start with the study presents a

norm prescribing a certain action to be taken. The more specific is the hypothesis the

more specific is the action to be taken and in such types of the studies the analysis of

the data is almost completely a mechanical procedure.

6) If the data is collected accordingly to the vague clues rather than according to thespecific hypothesis the data are analyzed inductively or invested during the process

and not by the means of the new prescribed set of the rules.

7) The task of the analysis is incomplete without the interpretations. In fact, the analysisof the data and the interpretations of the data are complementary to each other. The

end product of the analysis is the setting up of the certain general conclusions while

the interpretation deals with what these conclusions really mean.

8) Since the analysis and the interpretation of the data are interwoven the interpretationshould be more properly is conceived of as a special aspect of the analysis rather than

a distinct operation. Interpretation is the process to establish relationship between the

variables which are expressed in the findings and why such relationships exist.

9) For any successful study the task of the analysis and the interpretation should bedesigned before the data are actually collected with the exception of the formulate

studies where the researcher had no idea as to what kind of the answer he wants.


26/53


26

Otherwise there is always a danger to being too late and the chances of missing

important relevant data.

10) The most difficult task in the analysis and the interpretation of the data is theestablishment of the cause and the effect relationship especially in the cases of the

social and the personal problems. Research problems do not necessarily have one

factor or set of factors but they arise due to a complex variety of the factors and the

sequence. Karl pearsons has observed Nophenomena or stages in the sequence has

only one cause all antecedent stages are successive causes. When we scientifically

state causes we are really describing the successive stages of a routine of the

experience.

11) The human behavior cannot be reduced or explained with the help of the cause andthe effect relationships or the sequences as we face difficulties in detecting the factors

and in establishing the cause and the effect relationship because the nature of the

factors differ from one individual to the another and due to the fact that the cause and

the effect relationship both are the interdependent.

3.5)Types of the Analysis of the data:

Analysis of the survey or experimental data involves estimating the values of the

unknown parameters of the population and the testing of the hypothesis for drawing

the inferences. The Analysis can be categorized as follows:

1) Descriptive Analysis:2) Inferential Analysis.3) Correlation Analysis.4) Casual Analysis.


27/53


27

5) Multivariate Analysis.i) Multiple Discriminate Analyses.ii) Multiple Regression Analysis.iii) Multivariate Analysis of Varianceiv) Canonical Analysis.

1. Descriptive Analysis:It is the study of the distribution of one or the more variable. Such study provides us

with the profiles of the business group, work group, persons or the other subjects on

any of a multitude of the characteristics such as the size, composition, efficiency or

the preferences. The various measures that show the size and the shape of the

distribution along with the study of measuring the relationship between two or more

variables are available in the analysis.

2. Inferential Analysis:It is concerned with the various tests of the significance for the testing the hypothesis in

order to determine with what validity the data can indicate some conclusions. It is also

concerned with the estimation of the population values. It is mainly on the basis of the

inferential analysis that the task of the interpretation is performed.

3. Correlation Analysis:It studies the joint variation of the two or more variables for the determining the amount

of the correlation between the two or the more variables.

4. Casual Analysis:


28/53


28

It is concerned with the study of how one or more variables affect the changes in another

variable. It is the study of the functional relationship existing between the teo or the more

variables.

5. Multivariate Analysis:With the availability of the computer facilities there is a development of the multivariate

analysis which means the use of the statistical methods which analyze the more than the

two variables on a sample of the observations.

i) Multiple Discriminate Analysis:It is suitable that the researcher has a single dependent variable that cannot be

measured but can be classified into the two or the more groups on the basis on the

some attribute. The objective of this analysis happens to be to predict an

organizations possibility of belonging to a particular group which is based on the

several predicator variables.

ii) Multiple Regression Analysis:It is suitable when the researcher has only one dependent variable which is

presumed to be a function of two or more independent variables. The objective of

this analysis is to make the prediction about the dependent variable which is based

on the covariance with all the concerned independent variables.

iii) Multivariate Analysis of Variance:


29/53


29

This Analysis is the extension of the two way ANNOVA where in the ratio of the

among group variable to within group variance is worked out on a set of the

variables.

iv) Canonical Analysis:This analysis can be used in the case of both the measurable and the non

measurable variables for the purpose of the simultaneously predicting a set of the

dependent variables from their joint covariance with a set of the independent

variable.

Chapter 4: Interpretation of the Data.


30/53


30

Q.4. How will you do the Interpretation of the Data? Suggest the essentials of

the data interpretations. Enumerate the importance of the

interpretations of the data and recommend in detail the various forms

of the interpretations of the data.

Ans4: Points of the answer:

4.1) Concept and Essentials of the Data Interpretation.

4.2) Importance of Data Interpretations.

4.3) Forms of the Data Interpretations.

4.1) Concept and Essentials of the Data Interpretation.

Interpretation of the Data involves drawing inferences by the analyzing the data. The

analysis and the interpretation of the data are closely interlinked. The analysis of the data

often includes simultaneous interpretation of the results.

The following are the guidelines for the Data Interpretations:

1) Homogenous Data:2) Proper Processing of the Data.3)

Adequacy of the Data.

4) Accuracy of the Data.5) Suitability of the Data.6) Reliability of the Data.


31/53


31

1. Homogenous Data:Homogenous data is an important prerequisite to be considered while analyzing the data.

For e.g If the researcher collects the data on brand preferences from two or more areas

then the data variables must be same in all the areas. If the data are collected from the

three age groups or the income group in one area then the same criteria must be applied

in all the areas under the research. Homogenous data facilitate proper comparison and

therefore proper comparison and therefore there can be proper conclusions.

2. Proper Processing of the Data:Before the analysis and the interpretation the research should check whether the

researcher should check whether or not the data is processed or not with the respect to the

editing, coding classification and the tabulation. If the data is not processed properly with

special reference to the editing, then analysis and the interpretation of the data would be

defective, which in turn may provide defective results.

3. Adequacy of the Data:To draw the proper inferences, the data collection must be adequate. Inadequate data

makes analysis and interpretation difficult. The inadequacy of the data must be due to

small sample size. For instance if only 20 or 30 respondents are selected from a total

universe of 10 lakh people, then the data collected may not be sufficient enough for

drawing proper inferences especially in the case of commercial or social research.

4. Accuracy of the Data:


32/53


32

It is one of the most important prerequisite of the analysis and the interpretation of the

data. The data must be collected from the right source. The interviewers must be trained

to elicit the right responses from the respondents. Accuracy of the data helps to arrive at

the proper conclusions.

5. Suitability of the Data:The data collected must be appropriate or suitable to the research problem. The

appropriate data helps to draw the proper conclusions. For e.g a research conducted to

find out the brand loyalty ice-creams and if the data is collected from the senior citizens

due to the convenience then the inferences drawn may be wrong.

6. Reliability of the Data:The data collected must be up to date or reliable. Inferences drawn from the out dated

data may nor serve the purpose of the research. Therefore the researcher must focus on

the primary data to collect the up to date information. This is because the several research

studies especially commercial research requires the latest data.

1. Use of the Judgment.2. Uniform Basis of the Comparison.3. Proper Generalisations.4. Avoid Bias.1. Use of the Judgment.


33/53


33

Interpretation is said to be an art. Quite often the wisdom of the judgment is required

to draw inferences. Even in the case of the processing of the data a good deal of the

judgment is required on the part of the researcher.

2. Uniform Basis of the Comparison.Using the two or more variables on the different dimensions may lead to the wrong

findings. For e.g it would be difficult to determine the productivity if the output is

measured in the unit terms and the input is measured in the value terms. Bothe the

variables should be measured in the terms of the same measures.

3. Proper Generalizations:One should be very careful in generalizing the findings. One should always make a

proper analysis of the cause and the effect relationship. For e.g people generalize that

the High Job satisfaction leads to the high performance. But this may not be true.

Because high performance can also lead to the job satisfaction. This is because that

the higher the performance the higher the incentives, rewards, which in turn may lead

to the higher job satisfaction.

4. Avoid Bias:The interpreters must avoid the bias while drawing the inferences. For instance may

strongly favour advertising. If he sees the result that due to the advertising the sales

have been increased then he will always say that because of the advertising the sales

have been increased. In some cases this may not be true and therefore the researcher

must draw the proper inferences.


34/53


34

4.2) Importance of Data Interpretations:

The success of the researchers work largely depends on the quality of the interpretations.

After the collection of the data it must be processed in the terms of the coding,

classification and the Tabulations. The data which is processed is then analyzed and from

the data which is analyzed the researcher draws the following inferences. The importance

of the interpretations is briefly stated as follows:

1. Recommendations.2. Decision Making.3. Forecasting.4. Development of the Models.5. Development of the Hypothesis.6. Validates the Theory.7. Future References.8. Motivation to the Researcher.1. Recommendations:Recommendation means to give suggestions. The data interpretations may help to make

the recommendations especially in the case of the commercial and the social research.

For e.g if the research is conducted to find out the poverty in the backward areas then the

researcher will draw the inferences which are based on the analyzed data and then

provide the recommendations to overcome the problem of the poverty. Major causes of

the poverty may be consuming the alcohol and the gambling. In the case the researcher


35/53


35

may suggest the measures to reduce the burden of inherited debt and to overcome the

problem of the social evils which in turn will help to reduce the poverty.

2. Decision Making:Data interpretations help in the decision making. For e.g a research may be conducted to

find out the causes of the decline of the sales. The analysis of the data and the

interpretations may indicate the main cause of the decline in the sales. Poor after sales

service. Therefore the management may take suitable decisions to improve the after sales

service such as the following:

1) Training to the after sales service staff.2) Opening of the more service centre.3) Appointment of the competent staff.4) Monitoring customer feedback on the regular basis.3. Forecasting the trends:In the case of the social research the trends in the growth rate of the population, literacy

rate, income, and levels can be forecasted.

In the case of the commercial research the trends in the sales, profits, market shares can

be forecasted.

Based on the above forecasts the necessary actions can be taken by the concerned

authorities.

4. Development of Models:


36/53


36

The data interpretations may help to develop new models. For instance the researcher on

the brand loyalty may help to develop a new model on the brand loyalty. The model can

be used for the academic and the commercial purposes. For instance the AIDA model can

be used for the advertisers and the marketers. The model tells us that the customers

attention must be attracted, their interest must be developed in the minds of the

customers, strong desires must be created and finally the action must be induced.

5. Development of the Hypothesis:Hypothesis means the assumption. A pilot study can develop the hypothesis. The

interpretation of the pilot study enables the researcher to modify the hypothesis and

accordingly the new hypothesis can be developed with the research activity.

6. Validates Theory:The interpretation of the data may help to validate or invalidate the theory. For instance

the research may indicate that whether the present theory is relevant or not based on the

inferences drawn from the research work. In other words the inferences may either

support the current theory or prove it otherwise.

7. Future References:

The inferences drawn for a particular research activity can be used for the further

references. Further studies can be conducted based on the conclusions drawn fro the

earlier research activity.

8. Motivation to the Researcher:


37/53


37

Proper interpretation will generate proper recommendations. On the basis of the

recommendations effective decisions can be taken by the organization. If there are

excellent results the researcher interpreter may be rewarded with additional incentives.

4.3.) Forms of the Interpretations:

Depending upon the size and the nature of the data the statistical data can be interpreted

in various ways.

The some of the common and important forms or the basis of interpretation may be

described as follows:

1) Relationships2) Proportion.3) Percentages.4) Averages or other measures of the comparison.1) Relationship:The relationship has to be maintained properly. In general it is seen that unless the

comparative analysis or the study is made true form of the relationship between the

subject and the object cannot be determined. On the contrary unless true and the proper

relationships are established amongst the different aspects, interpretation csn never be

considered as complete.

2) Proportion:


38/53


38

It is another aspect of the study of the interpretation which can be made perfect.

Proportion is generally ascertained to determine the nature and the form of the absolute

changes in the subjects of the study. In particular if the object of the study is too must

variable over a period then the proportions are ascertained to interpret the data

information in a true form.

3) Percentages:Sometimes the basis of the interpretations is the percentage. If the object of the enquiry is

to determine the nature and the extent of the approximations only for a particular

objective, then the method of the percentage is often used for the making interpretations

as the basis. In this regard we must keep in the mind that although the method of the

percentage is somewhat crude and the approximate yet it is often used in the spheres of

the absolute figures.

4) Averages or the other measures of the comparison:Finally the method of the averages or the other measures of the comparisons are used to

interpret statistical data and the information. It is a matter of the common experience that

if a long statistical table is to be analysed and interpreted we have to take the help of the

various forms of the measuring the central or the other tendencies relating to them. In the

absence of these comparative measurements definite and the clear cut result may be

arrived at. Therefore the average or the other measures of the comparisons are considered

to be not only desirable but an essential and the integral part of the interpretation.


39/53


39

Chapter5: Tabulation Methods, Significance of Data Processing, Role of the

Computers in Data Processing, Need for the Statistical Techniques in

the Research Analysis.

Q.5. What are the various methods of the Tabulation and explain the

significance of the processing of the data. Discuss the role of the

computer in the data processing and the analysis. Explain the need for

the statistical techniques in the field of research analysis.


5.1.) Various Methods of the Tabulation.

5.2.) Significance of the Processing of the Data.

5.3.) Role of the Computers in the Data Processing.


40/53


40

5.4.) Need for the Statistical Techniques in the field of the Research.

5.1.) Various Methods of the Tabulations:

There are various Methods of the Tabulations:

1) Hand/ Manual Tabulation.2) Machine Tabulation.1) Hand Tabulation Method:Hand Tabulation is a traditional and a very old method of the tabulation in which the

work of the sorting, numbering, and the counting of the questionnaire is done by the

hands only. It is suitable to tabulate data on a small scale i.e the size of the sample

survey, the numbers of the respondents and the questions asked the small, say less than

500. Hand Tabulation is very easy and very simple to follow and execute.

Procedure for the Hand Tabulation.

The researcher first prepares a plan for the tabulation for the purpose. The plan is

prepared with the help of a number of the responses, principles of the classification, the

object of the research. Afterwards duly completed questionnaires are numbered serially.

After numbering the response sheets are sorted out and are grouped into the specific

categories. For e.g after numbering say 100 respondents then they can be classified and

grouped into the male and the female category. Afterwards counting of the individual

answers is taken up. Counting is often done in the sets of the five tally marks thus which

makes the totaling work very easy and very quick.


41/53


41

At the end the results of the counting are shown on the counting sheets for each response

separately. A sample of the hand tabulation is given below

Suppose a group of the 45 respondents is asked in the following questions:

Would you prefer branded products -----------Yes?

Over None Branded----------------No.

Merits of the Hand Tabulation:

1) Hand Tabulation is a simple easy and convenient method of the tabulation.2) Manual processing or the tabulation is flexible. It can be done by any junior staff

under the guidance of a supervisor, It does not require technicians.

3) Hand Tabulation can be done without coding or processing.4) Manual Tabulation is suitable where there is a great deal of the coded information or

where few respondents are interviewed extensively.

Demerits of the Hand Tabulation:

1) Manual Tabulation is a time consuming method. It takes time to analyse, group, countand record individual responses.

2) There are chances of the clerical and the human errors as it relies on the human handsand the memory.

3) Manual Tabulation does not facilitate cross classification to establish interrelationshipbetween different variables.

4) It cannot be used in the periodic types of the surveys.


42/53


42

2) Machine Tabulation Method:The need for the speedy analysis of the volumes of the data has resulted into the

substitution of the hand tabulation by the machine tabulations. Mechanical methods uses

automatic and the fast power machines for the sorting, counting, classifying and even

tabulation of the bulk data. Some machines like computers are equipped to perform most

complicated statistical jobs of the calculation analysis interpretation and even printing.In

the modern times computers are being extensively used for small and the big research

works for the data analysis.

Merits of the Machine Tabulations:

1) Machines can be used to handle extensive and vast volume of the data conveniently.2) It facilitated cross-classification and the study of the many variables simultaneously.3) It is extremely useful in the periodic surveys requiring addition and the up gradation

of already collected data at the regular intervals.

4) Machine Tabulation is more accurate and there are less chances of the errors in theprocess of the sorting and the counting.

5) It is time saving and the economical if used for the large scale surveys.Demerits of the Machine/ Mechanical Tabulation:

1) Machine Tabulation involves much clerical work and specified operations.2) It needs the prior sorting and the coding of the data before it id fed to machine. In the

olden dayspunch card were used for the coding purpose.

3) Machine tabulation is less flexible as machines can only act but cannot think.


43/53


43

4) The speed and the accuracy of the machines may induce researchers to collect largedata on unrelated topics and deviate from the original objectives of the research.

5.2) Significance of the Processing of the Data:

(A) Significance of the Editing:

1) It facilitates the coding of the data.

2) It helps to assure that the facts are consistent with the principles.

3) It co-ordinates with the data entry and ensures uniform entries.

4) It makes information acceptable for the tabulation.

5) It helps to remove unessential or irrelevant data.

(B) Significance of the Coding:

1) It supports transcription of the data.

2) It is a further purification and the crystallization of the raw edited data.

3) It sets the research design category in an orderly manner.

4) It supports the preparation of the interview schedules.

5) It gives a fundamental base for the formulation of the explicit rules and the

conventions that can be used to the base classifications and the observation

variables.


44/53


44

(C) Significance of the Classifications:

1) It identifies similarly in the data collected.

2) It maintains homogeneity.

3) It facilitates effective comparison.

4) It helps to maintain the clarity.

5) It helps to simplify complex data.

6) It specifies diversity in the unity of the data.

7) It achieves effective qualification.

8) It facilitates easy presentation and the interpretation of the data.

(D) Transcription of the Data:

1) It is intermediary process of supporting the coding and the tabulation.

2) It is made as and when edited instruments are ready processing.

3) It is a technique used to support posting the data from the questionnaire/

schedules on intermediary material in a summarized manner.

(E) Tabulations of the Data:

1) It is technique of summarizing and arranging the data in a compact form for the

further analysis.


45/53


45

2) It is useful for the periodic surveys.

3) It does not primarily requires skilled or technically qualified employees.

4) It is generally done without much of the processing and the coding .

5.3.) Role of the Computers in the Data Processing:

Computers are used in the data processing and the analysis. Computer data processing is

any process that a computer program does to enter the data and summarize, analyze or

otherwise convert the data into the usable information. The process may be automated

and run on the computer. It involves recording, analyzing, sorting summarizing,

calculating disseminating and sorting the data. Because data are most useful when it is

well presented and actually informative, data processing, systems are often referred to as

information systems. Nevertheless the terms are roughly synonymous, performing similar

conversions, data processing systems typically manipulate raw data into information and

likewise information systems typically take the new data in input to produce information

as output.

Data Processing and Analysis:

Data processing usually involves a great deal of the computation upon a relatively small

amount of the input data, resulting in a small volume of the output. In the early days of

the computers the emphasis was laid upon scientific data processing. This refers to a class

of the programs that organize and manipulate the data, usually large amounts of the

numeric data. The programs or the software packages run on the computer and saves us


46/53


46

the rigor of the manually calculating and tabulating the data which would be quite tedious

and time consuming.

Software packages such as SPSS( Statistical Package for Social Sciences), SAS(

Statistical Analysis System) and the few other programs are used for the data mining. The

use of such programs is found in several industries such as the finance, banking,

government, organizations, transport and the retail sector, health establishment.

Data processing and the information systems are the terms that are considered too broad

and are more specialized terms, data analysis is typically used. This is a focus on the

highly specialized and highly accurate algorithm derivations and the statistical

calculations that are less often observed in the typical general business environment. In

these contexts data analysis packages like the Stata, SAS or SPSS are often used.

Performing Chi-square Test and many other tests can be done using the SPSS packages.

Graphical representation and the charts and the tabulated form of the analysed are also

constructed using these packages. Comprehensive analysis in very less time can be done

using these packages; therefore role of the computers is of the great importance in the

data processing and the analysis.

5.4.) Need for the Statistical Techniques in the field of the Research:

The importance of the statistical technique in the social science research has increased in

the recent years due to the greater importance of the statistical information. In every

organization in every economic activity performance are codified in the statistical data

since figures help in representation data and make that easy and understandable. In the


47/53


47

social science research the importance of the statistical techniques has increased due to

the wider use of the quantitative techniques.

Statistical in the social sciences research help in the gaining accuracy and the reliability.

The results can be presented in brief and the precise language and the complex and

complicated problems can be studied in very simple way. It becomes possible to convert

abstract problems into quantifiable data. Statistical techniques are widely in the use.

Governments, politicians, economists, astrologers, need them and all types of the people

make use of statistical techniques. Nowadays there is hardly any field where statistics has

no place. Statistic affects everybody and touches life at many points.

Statistical techniques are the mathematical techniques used to facilitate the interpretation

of the numerical data collected for the various sources and the methods. The statistical

methods may be classified into the four sets of the techniques according to the major

purposes that they are intended to serve.

1) The first set of the techniques enable us to organize group data, to describe andinterpret these data in the terms of the derived measures of the central tendency, of

variability and to portray these data in the graphical form for more convenient

interpretations or more ready assimilations.

2) The second of the techniques will be useful to describe quantitatively the limitswithin which he may safely generalize about the large groups or the population on the

basis of the facts derived from the relatively small groups or the samples selected at

the random from these populations.


48/53


48

3) The third set of the techniques will help to describe quantitatively the degree of therelationship existing between measures of the different characteristics. For e.g the

relationship between the intelligence and the ability to make the sales can be

measured with this set of the techniques.

4) The fourth set techniques will enable the student to describe quantitavely fluctuationsoccurring in the time series to isolate these variations and to eliminate their influence

from the basic data when this is deemed desirable.

Chapter 6: Summary.


49/53


50/53


50

Chapter 7: Conclusions.

1) Research is a very important activity for any project. Without this activity the projectwill be incomplete. For that purpose we have to collect data. This data is available to

us in the Primary form and in the secondary form.


51/53


51

2) When Data is collected further processing of the Data is very necessary because,without the processing the inferences will not be drawn properly. One has to go

through many stages in the Data processing.

3) Computers are used in the data processing and the analysis. Computer data processingis any process that a computer program does to enter data and summarize analyze or

otherwise convert data into suitable information.

4) Statistics in the social science Research help in the gaining accuracy and thereliability. The results can be presented in the brief and the precise language and the

complex and the complicated problems can be studied in the very simple way.

5) To conclude a proper processing of the Data is very essential and without it properand fast inferences will not be drawn.

Chapter 8: Bibliography/ References.

1)Name of the Book: Research Methodology Methods and Techniques

Author: C.R.Kothari.

Publisher: New Age International (P) Ltd.

2) Name of the Book: Research Methodology for the Business


52/53


52

Author: Uma Sekaran.

3) Name of the Book: Methodology of the Research in Social ScienceAuthor: O.R. Krishnaswami

Publisher: Himalaya Publishing.

4) Name of the Book: Research Methods.Author: Ram Ahuja.

Publisher: Rawat Publishers.

Name: Mandar P. Khandeker

Roll No 23, M.Com Part II, University of Mumbai, Commerce Department

SemesterIV. Examination.

Subject: Research Methodology in Commerce.(Paper1)

Viva Date:_4.04.2014.______________.

Signature:________________.


53/53


rm project iv-th sem

Documents