Problems in processing of data in research methodology
Answers
The problem concerning “Don’t know” (or DK) responses: While processing the data, the researcher often comes across some responses that are difficult to handle. One category of such responses may be ‘Don’t Know Response’ or simply DK response. When the DK response group is small, it is of little significance. But when it is relatively big, it becomes a matter of major concern in which case the question arises: Is the question which elicited DK response useless? The answer depends on two points viz., the respondent actually may not know the answer or the researcher may fail in obtaining the appropriate information. In the first case the concerned question is said to be alright and DK response is taken as legitimate DK response. But in the second case, DK response is more likely to be a failure of the questioning process.
How DK responses are to be dealt with by researchers? The best way is to design better type of questions. Good rapport of interviewers with respondents will result in minimising DK responses. But what about the DK responses that have already taken place? One way to tackle this issue is to estimate the allocation of DK answers from other data in the questionnaire. The other way is to keep DK responses as a separate category in tabulation where we can consider it as a separate reply category if DK responses happen to be legitimate, otherwise we should let the reader make his own decision. Yet another way is to assume that DK responses occur more or less randomly and as such we may distribute them among the other answers in the ratio in which the latter have occurred. Similar results will be achieved if all DK replies are excluded from tabulation and that too without inflating the actual number of other responses.
Use or percentages: Percentages are often used in data presentation for they simplify numbers, reducing all of them to a 0 to 100 range. Through the use of percentages, the data are reduced in the standard form with base equal to 100 which fact facilitates relative comparisons. While using percentages, the following rules should be kept in view by researchers:
Two or more percentages must not be averaged unless each is weighted by the group size from which it has been derived.Use of too large percentages should be avoided, since a large percentage is difficult to understand and tends to confuse, defeating the very purpose for which percentages are used.
Answer:
There are many challenges in Data Processing.
Explanation:
Challenges in Processing of data are:
1. Collection of data - It is important to collect the exact and correct data for the input to get the proper result.
2. Duplication of data - Duplicate data is redundant and may produce an incorrect result.
3. Inconsistency of data - Data may be ambiguous. Raw data is heterogeneous in nature and is collected from autonomous data sources. It may conflict with each other in different levels.
4. Volume and Storage of data - Data is huge in volume and we need to keep a copy or backup of the data for safety. This increases the amount of stored data up to 150% or more.
5. Security - Hacking the data results in a data leak. It may cost highly to the data processing firm. Hackers might even change or delete the data that we have acquired and processed after a lot of struggle.
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