Data Processing Made Easy

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PROCESSING OF DATA

INTRODUCTION
Data processing is an intermediary stage of work between data collection and data analysis. The completed instruments of data collection, viz., interview schedules/ questionnaires/ data sheets/field notes contain. a vast mass of data. They cannot straightaway provide answers to research questions. They, like raw materials, need processing. Data processing involves classification and summarisal1on of data in order to make them amenable to analysis Processing of data requires advance planning at the stage of planning the research design. This advance planning may covey such aspects as categorization of variables and preparation of dummy tables. This should be done with reference to the requirements of testing hypotheses/inves-tigative questions. This type of preplanning ensures better identification of data needs and their adequate coverage in the tools for collection of data. Data processing consists of a number of closely related operations, viz., (1) editing, (2) classification and coding, (3) transcription and (4) tabulation. EDITING

The first step in processing of data is editing of complete schedules/questionnaires. Editing is a process of checking to detect and or correct errors and omissions. Editing is done at two stages: first at the fieldwork stage and second at office. Field editing

During the stress of interviewing the interviewer cannot always record responses completely and legibly. Therefore after each interview is over, he should review the schedule to complete abbreviated responses, rewrite illegible responses and correct omissions. Office editing

All completed schedules/questionnaires should be thoroughly checked in the office for Completeness, accuracy and. Uniformity CLASSIFICATION AND CODING
Categorisation and classification
The edited data are classified and coded. The responses are classified into meaningful categories so as to bring out essential pattern. By this method, several hundred responses are reduced to five or six appropriate categories containing critical information needed for analysis. When to classify: Classification can be done at any phase prior to the tabulation. Certain items like sex, age, type of house, and the like are structured and pre classified in the data collection form itself. The respon-ses to open-ended questions are classified at the processing stage. Categorization Rules: A classification system should meet certain requirements or be guided by certain rules. First, classification should be linked to the theory and the aim of the particular study. Second, the scheme should be exhaustive. That is, there must be a category for every response. Third, the categories must also be mutually exclusive, so that each case is classified only once. Number of categories: How many categories should a scheme include? It is preferable to include many categories rather than a few, since reducing the number later is 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. Coding

Coding means assigning numerals or other symbols to the categories or responses. For each question a coding scheme is designed on the basis of the con med categories. The coding schemes with their assigned symbols together with specific coding instructions may be assembled in a book. The codebook will identify a specific item of variable/observation and the code number assigned to each category of that item. If the data are to be transferred to machine punch cards, the codebook will also identify the column in which it is entered. TRANSCRIPTION

Introduction
When only a few schedules are processed and hand-tabulated, tabulation can directly be made from the schedules. On the other hand, direct tabulation from the edited schedules/ questionnaires is difficult if the number of the schedules and the number of responses in them are large/ suppose an interview...
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