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Methods of determining sample size

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Sunanda K. Chavan
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Methods of determining sample size - October 21st, 2010

There are six methods of determining sample size in market research. They are
1. Unaided Judgement: When no specific method is used to determine sample size, it is called Unaided Judgement. Such approach when used to arrive at sample size gives no explicit considerations to either the likely precision of the sample results or the cost of obtaining them (characteristics in which client should have interest). It is an approach to be avoided.
2. All –You –Can –Afford: In this method, a budget for the project is set by some (generally unspecified) process and, after the estimated fixed costs of designing the project, preparing a questionnaire (if required), analyzing the data, and preparing the report are deducted, the remainder of the budget is allocated to sampling. Dividing this remaining amount by the estimated cost per sampling unit gives the sample size.

This method concentrates on the cost of the information and is not concerned about its value. Although cost always has to be considered in any systematic approach to sample size determination, one also needs to give consideration to how much the information to be provided by the sample will be worth. This approach produces sample sizes that are larger than required as well as sizes that are smaller than optimal.
3. Required Size Per Cell: This method of determining sample size can be used on simple random, stratified random, purposive and quota samples. For example, in a study of attitudes with respect to fast food establishments in a local marketing area it was decided that information was desired for two occupational groups and for each of the four age groups. This resulted in 2 x 4 = 8 sample cells. A sample size of 30 was needed per cell for the types of statistical analyses that were to be conducted. The overall sample size was therefore 8 x 30 = 240.
4. Use of Traditional Statistical Model: The formula for traditional statistical model depends upon the type of sample to be taken and it always incorporates three common variables
• an estimate of the variance in the population from which the sample is to be drawn,
• the error from sampling that the researcher will allow, and
• the desired level of confidence that the actual sampling error will be within the allowable limits.
The statistical models for simple random sampling include estimation of means and estimation of proportion.
5. Use of Bayesian Statistical Model: The Bayesian model involves finding the difference between the expected value of the information to be provided by the sample size. This difference is known as expected net gain from sampling (ENGS). The sample size with the largest positive ENGS is chosen.

The Bayesian model is not as widely used as the traditional statistical models for determining sample size, even though it incorporates the cost of sampling and the traditional models do not. The reasons for the relative infrequent use of Bayesian model are related to greater complexity and perceived difficulty of making the estimates required for Bayesian model as compared to the traditional models.
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Re: Methods of determining sample size - June 9th, 2015

One of the information on Sample Size. Sample is the part of the promotion strategy and highly effective if, the product is launched for the first time. they allow users to try the product for the time and create moment of truth environment. the best art of Sample size is that you can gauge the effectiveness and if sample is presented in exceptional way then the result is positive.
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Re: Methods of determining sample size - February 23rd, 2016

Quote:
Originally Posted by sunandaC View Post
There are six methods of determining sample size in market research. They are
1. Unaided Judgement: When no specific method is used to determine sample size, it is called Unaided Judgement. Such approach when used to arrive at sample size gives no explicit considerations to either the likely precision of the sample results or the cost of obtaining them (characteristics in which client should have interest). It is an approach to be avoided.
2. All –You –Can –Afford: In this method, a budget for the project is set by some (generally unspecified) process and, after the estimated fixed costs of designing the project, preparing a questionnaire (if required), analyzing the data, and preparing the report are deducted, the remainder of the budget is allocated to sampling. Dividing this remaining amount by the estimated cost per sampling unit gives the sample size.

This method concentrates on the cost of the information and is not concerned about its value. Although cost always has to be considered in any systematic approach to sample size determination, one also needs to give consideration to how much the information to be provided by the sample will be worth. This approach produces sample sizes that are larger than required as well as sizes that are smaller than optimal.
3. Required Size Per Cell: This method of determining sample size can be used on simple random, stratified random, purposive and quota samples. For example, in a study of attitudes with respect to fast food establishments in a local marketing area it was decided that information was desired for two occupational groups and for each of the four age groups. This resulted in 2 x 4 = 8 sample cells. A sample size of 30 was needed per cell for the types of statistical analyses that were to be conducted. The overall sample size was therefore 8 x 30 = 240.
4. Use of Traditional Statistical Model: The formula for traditional statistical model depends upon the type of sample to be taken and it always incorporates three common variables
• an estimate of the variance in the population from which the sample is to be drawn,
• the error from sampling that the researcher will allow, and
• the desired level of confidence that the actual sampling error will be within the allowable limits.
The statistical models for simple random sampling include estimation of means and estimation of proportion.
5. Use of Bayesian Statistical Model: The Bayesian model involves finding the difference between the expected value of the information to be provided by the sample size. This difference is known as expected net gain from sampling (ENGS). The sample size with the largest positive ENGS is chosen.

The Bayesian model is not as widely used as the traditional statistical models for determining sample size, even though it incorporates the cost of sampling and the traditional models do not. The reasons for the relative infrequent use of Bayesian model are related to greater complexity and perceived difficulty of making the estimates required for Bayesian model as compared to the traditional models.
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