Page 162 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Unit 8: Sampling and Sampling Distribution

Notes
Example:
 An MNC bank wants to pick up a sample among the credit card holders. They can
readily get a complete list of credit card holders, which forms their data bank. From
this frame, the desired individuals can be chosen. In this example, sample frame is
identical to ideal population namely all credit card holders. There is no sampling
error in this case.

 Assume that a bank wants to contact the people belonging to a particular profession
over phone (doctors, lawyers) to market a home loan product. The sampling frame
in this case is the telephone directory. This sampling frame may pose several
problems: (1) People might have migrated. (2) Numbers have changed. (3) Many
numbers were not yet listed. The question is “Are the residents who are included in
the directory likely to differ from those who are not included”? The answer is yes.
Thus in this case, there will be a sampling error.
8.5.4 Non-response Error

This occurs, because the planned sample and final sample vary significantly.

Example: Marketers want to know about the television viewing habits across the country.
They choose 500 households and mail the questionnaire. Assume that only 200 respondents
reply. This does not show a non-response error, which depends upon the discrepancy. If those
200 who replied did not differ from the chosen 500, there is no non-response error.
Consider an alternative. The people who responded are those who had plenty of leisure time.
Therefore, it is implied that non-respondents do not have adequate leisure time. In this case, the
final sample and the planned sample differ. If it was assumed that all the 500 chosen have leisure
time, but in the final analysis only 200 have leisure time and not others. Therefore, a sample
with respect to leisure time leads to response error.

8.5.5 Data Error

This occurs during the data collection, analysis of data or interpretation. Respondents sometimes
give distorted answers unintentionally for questions which are difficult, or if the question is
exceptionally long and the respondent may not have answer. Data errors can also occur depending
on the physical and social characteristics of the interviewer and the respondent. Things such as
the tone and voice can affect the responses. Therefore, we can say that the characteristics of the
interviewer can also result in data error. Also, cheating on the part of the interviewer leads to
data error. Data errors can also occur when answers to open-ended questions are being
improperly recorded.

8.5.6 Failure of the Interviewer to Follow Instructions

The respondent must be briefed before beginning the interview, “What is expected”? “To what
extent he should answer”? Also, the interviewer must make sure that respondent is familiar
with the subject. If these are not made clear by the interviewer, errors will occur.
Editing mistakes made by the editors in transferring the data from questionnaire to computers
are other causes for errors.
The respondent could terminate his/her participation in data gathering, because it may be felt
that the questionnaire is too long and tedious.

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