mb0050 slides unit 08

C o n f i d e n t i a l

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Program : MBA

Semester : III

Subject Code : MB0050

Subject Name : Research Methodology

Unit Number : 8

Unit Title : Data Processing

Lecture Number : 8

Lecture Title : Data Processing

Book Id : B1700

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Data Processing

Objectives :

Explain the significance and technique of data processing

Construct codes both for structured and unstructured

questionnaires following certain guidelines.

Classify and tabulate data in the required format.

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Unit-8 Data Processing


Lecture Outline

Introduction

Data Editing

Coding

Classification and Tabulation of Data

Summary

Check Your Learning

Activity

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Introduction

The critical job of the researcher begins after the data has been

collected.

The raw data that has been collected must be refined and

structured in such a format that it can lend itself to statistical

enquiry.

This process of preparing the data for an analysis is a structured

and sequential process.

The process starts by validating the measuring instrument which

could be a questionnaire or any other primary technique. This is

followed by editing, coding, classifying and tabulating the obtained

data.

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Data Editing

Data editing is the process that involves detecting and correcting errors

(logical inconsistencies) in data.

While carrying out the editing the researcher needs to ensure that:

The data obtained is complete in all respects.

It is accurate in terms of information recorded and responses sought.

Questionnaires are legible and are correctly deciphered, especially the open-

ended questions.

The response format is in the form that was instructed.

The data is structured in a manner that entering the information will not be a

problem.

The editing process is done at two levels, field editing and centralized in-

house editing. Some of the standard processes used for centralized in-

house editing include backtracking, allocating missing values, plugging

values and discarding unsatisfactory values.

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Coding

The process of identifying and denoting a numeral to the

responses given by a respondent is called coding.

Usually, the codes that have been formulated are organized into

fields, records and files.

In order to manage the data entry process, it is best to prepare a

method for entering the records. This coding scheme for all the

variables under study is called a code book.

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Coding

Coding Closed-ended Structured Questions:

The method of coding for structured questions is easier as the response

categories are decided in advance.

The coding method to be followed for different questions:

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Dichotomous questions

For dichotomous questions, which are on a nominal scale, the responses can be binary.

Ranking questions

For ranking questions where there are multiple objects to be ranked, the person will have to make multiple columns, with column numbers equaling the number of objects to be ranked.


Coding

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Scaled questions

For questions that are on a scale, usually an interval scale, the question/statement will have a single column and the coding instruction would indicate what number needs to be allocated for the response options given in the scale.

Missing values It is advisable to use a standard format for signifying a nonresponse or a missing value.



In case data obtained from the primary instrument is too huge to

be interpret, the researcher might decide to reduce the

information into homogenous categories. This method of

arrangement is called classification of data. This can be done on

the basis of class intervals.

Numerical data, like the ratio scale data, can be classified into class

intervals. Formula for determining the number of class intervals:

I = R/(1 + 3.3 log N)

where,

I = size of class interval,

R = Range (i.e., difference between the values of the largest item

and smallest item among the given items),

N = Number of items to be grouped.

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Once the categories and codes have been decided upon, the

researcher needs to arrange the same according to some logical

pattern. This is referred to as tabulation of data.

This involves an orderly arrangement of data into an array that is

suitable for a statistical analysis.

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Summary

Data processing refers to the primary data that has been collected

specifically for the study.

The researcher has to check for omissions or errors. This is the editing

stage of the data processing. This is done first at the field and then at the

central office level.

At this stage, the research team conducts some data treatment such as

allocating the missing values, if possible, backtracking and sometimes,

plugging the incomplete data.

Once this is completed, the researcher prepares code book. Classification

into attributes or class intervals is carried out and the entered data is now

ready for analysis in a tabular form.

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Check Your Learning

1. What is data editing?

Ans: Data editing is the process that involves detecting and correcting errors

(logical inconsistencies) in data.

2. Distinguish between field editing and centralized in-house editing.

Ans: Field editing is the preliminary editing of the collected information done by

the field investigators or supervisors, while the second level of editing

(Centralized in-house editing) takes place at the researchers end.

3. What is Coding?

Ans: The process of identifying and denoting a numeral to the responses given

by a respondent is called coding.

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Activity

Find some tabular data and identify whether they have used class

intervals. Identify which are exclusive or inclusive data. Why do

you think they have been used? Make a code book for any of

these tables.

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