The data, after collection, has to be processed and analyzed in accordance with the outline laid down for the purpose at the time of developing the research plan. Processing implies editing, coding, classification and tabulation of collected data so that they are amenable to analysis. The term analysis refers to the computation of certain measures along with searching for patterns of relationship that exist among data-groups.

Coding is a process in which the data is divided in to a limited number of classes. In this process all the answers are assigned in any symbol or numeral order this is done with the help of set rules. Coding process assigns numerals or other symbols to the several responses of the data set.

At the time of response the volume of data is very large. And for efficient analysis it is necessary to concise the data in some alphabetic or numeric code

Numeric Coding : Coding need not necessarily be numeric. It can also be alphabetic. Coding has to be compulsorily numeric, when the variable is to be subject to further parametric analysis.

Alphabetic Coding

A mere tabulation or frequency count or graphical representation of the variable may be given 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 respondent. Hence, if a value of 0 is to given to a specific response in the data sheet, it should not lead to the same interpretation of on response for instance, there will be a tendency to given a code of 0 to a no answer. However, if the respondent had not chosen Yes or No. Then a different coding

Than 0 should be given in it the data sheet. illustration of the coding process of some of the demographic variables is given in the following table.

Question No.Variable/ ObservationResponse categoriesCode

1.1Organization PrivatePublicGovernmentPtPbGo3.4Owner of vehicle YesNo214.2Vehicle performanceExcellentGoodAdequateBadWorst543215.1AgeUp to 20 years21-40 years40-60 yearsAbove-60 years1234

Question No.Variable/ ObservationResponse categoriesCode5.2OccupationSalariedProfessionalTechnicalBusinessRetiredHousewifeothersSPTBRH*

They must also possess the characteristic of exhaustiveness (i.e. there must be a class for every data item) and also that of mutual exclusively which means that a specific answer can be placed in one and only one cell in a given category set. Another rule to be observed is that of unidimensionality by which is meant that every class is defined in terms of only one concept.

Before collection data:

Coding decision should usually be taken at the designing state of the questionnaire. This makes it possible to precode the questionnaire choices and which in turn is helpful for computer tabulation as one can straight forward key punch from the original questionnaires.

After collection data:

But in case of hand coding some standard method may be used. On such standard method is to code in the margin with colored pencil . The other method can be to transcribe the data from the questionnaire to a coding sheet.

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 orders 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 outsources to help in the data entry procedure, sometime, 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. Form this purpose, classification of data of also necessary at the data entry stage