A sampling frame is a complete list of all the elements in the population. For example:
Next, let’s talk about the sample that we are going to draw from this population.
As you all know, a sample is only a part of a statistical population, and hence it can represent the population to only to some extent. Of course, it is intuitively logical that the larger the sample, the more likely it is to represent the population. Obviously, the limiting case is that: when the sample size tends to the population size, the sample will tend to be identical to the population. But, of course, in general, the sample is much smaller than the population.
The point is that, in general, statistical sampling seeks to determine how accurate a description of the population the sample and its properties will provide. We may have to compromise on accuracy, but there are certain such advantages of sampling because of which it has an extremely important place in data-based research studies.
· Although cost per unit in a sample is greater than in a complete investigation, the total cost will
be less (because the sample will be so much smaller than the statistical population from which
it has been drawn).
· A sample survey can be completed faster than a full investigation so that variations from
sample unit to sample unit over time will largely be eliminated.
· Also, the results can be processed and analyzed with increased speed and precision because
there are fewer of them.
2. More detailed information may be obtained from each sample unit.
3. Possibility of follow-up:
(After detailed checking, queries and omissions can be followed up --- a procedure which might prove impossible in a
complete survey).
4. Sampling is the only feasible possibility where tests to destruction are undertaken or where the population is
effectively infinite.
The next two important concepts that need to be considered are those of sampling and non-sampling errors.
- The complete list of the BCS students of Virtual University of Pakistan on February 15, 2003
- Speaking of the sampling frame, it must be kept in mind that, as far as possible, our frame should be free fromvarious types of defects:
- does not contain inaccurate elements
- is not incomplete
- is free from duplication, and
- Is not out of date.
Next, let’s talk about the sample that we are going to draw from this population.
As you all know, a sample is only a part of a statistical population, and hence it can represent the population to only to some extent. Of course, it is intuitively logical that the larger the sample, the more likely it is to represent the population. Obviously, the limiting case is that: when the sample size tends to the population size, the sample will tend to be identical to the population. But, of course, in general, the sample is much smaller than the population.
The point is that, in general, statistical sampling seeks to determine how accurate a description of the population the sample and its properties will provide. We may have to compromise on accuracy, but there are certain such advantages of sampling because of which it has an extremely important place in data-based research studies.
ADVANTAGES OF SAMPLING
1. Savings in time and money.· Although cost per unit in a sample is greater than in a complete investigation, the total cost will
be less (because the sample will be so much smaller than the statistical population from which
it has been drawn).
· A sample survey can be completed faster than a full investigation so that variations from
sample unit to sample unit over time will largely be eliminated.
· Also, the results can be processed and analyzed with increased speed and precision because
there are fewer of them.
2. More detailed information may be obtained from each sample unit.
3. Possibility of follow-up:
(After detailed checking, queries and omissions can be followed up --- a procedure which might prove impossible in a
complete survey).
4. Sampling is the only feasible possibility where tests to destruction are undertaken or where the population is
effectively infinite.
The next two important concepts that need to be considered are those of sampling and non-sampling errors.
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