Page 65 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Quantitative Techniques-II

Notes 4.5.2 Data Processing

Processing data is very important in market research. After collecting the data, the next job of
the researcher is to analyze and interpret the data. The purpose of analysis is to draw conclusion.
There are two parts in processing the data.
1. Data Analysis
2. Interpretation of data
Analysis of the data involves organizing the data in a particular manner. Interpretation of data
is a method for deriving conclusions from the data analyzed. Analysis of data is not complete,
unless it is interpreted.

Steps in Processing of Data

1. Preparing raw data

2. Coding
3. Editing
4. Tabulation of data
5. Summarising the data

6. Usage of statistical tool.

Preparing Raw Data

Data collection is a significant part of market research. Even more significant is, to filter out the
relevant data from the mass of data collected. Data continues to be in raw form, unless they are
processed and analyzed.
Primary data collected by surveys, observations by field investigations are hastily entered into
questionnaires. Due to the pressure of interviewing, the researcher has to write down the
responses immediately. Many times this may not be systematic. The information so collected by
field staff is called raw data.

The information collected may be illegible, incomplete and inaccurate to some extent. Also the
information collected will be scattered in several data collection formats. The data lying in such
a crude form are not ready for analysis. Keeping this in mind the researcher must take some
measures to organize the data, so that it can be analyzed.
The various steps which are required to be taken for his purpose are (a) editing and (b) coding
and (c) tabulating.

Coding

Coding refers to all those activities which helps in transforming edited questionnaires into a
form which is ready for analysis. Coding speeds up the tabulation while editing eliminates
errors. Coding involves assigning numbers or other symbols to answers, so that the responses
can be grouped into limited number of classes or categories.

Example: 1 is used for male and 2 for female.

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