You can set a cut-off date and use the subscribers as at say 30 April. Then you use population to select your sample. If you need to, then you conduct another study as at 30 June - depends on what you are studying!

It really does depend, as Albert suggests, on what you are studying. You need to provide a lot more detail before we can give useful and constructive answers.

What is your hypothesi(e)s you want to test (it is better to generalise them where possible but with enough detail)

Do you want to track only subscribers or are comparing behaviour of subscribers/non-subscribers?

Do you want to capture static snapshots or track dynamic changes?

Dear Irshad

In order to answer this question/problem, several remarks have to be studied.

1. Moving population:

The sample should be drawn on specific characteristic of time (hour, day, month, year) and should be based on a specific and identified population, i.e. you should identified the above characteristics and draw the sample.

2. General remarks:

Research studies are usually carried out on sample of subjects rather than whole populations. The most challenging aspect of fieldwork is drawing a random sample from the target population to which the results of the study would be generalized. The key to a good sample is that it has to be typical of the population from which it is drawn. When the information from a sample is not typical of that in the population in a systematic way, we say that error has occurred. In actual practice, the task is so difficult that several types of errors, i.e. sampling error, non-sampling error, Response error, Processing error,…

In addition, the most important error is the Sampling error, which is statistically defined as the error caused by observing a sample instead of the whole population. The underlying principle that must be followed if we are to have any hope of making inferences from a sample to a population is that the sample be representative of that population. A key way of achieving this is through the use of “randomization”. There several types of random samples, Some of which are: Simple Random Sampling, Stratified Random Sampling, Double-stage Random Sampling... Moreover, the most important sample is the simple random sample which is a sample selected in such a way that every possible sample of the same size is equally likely to be chosen. In order to reduce the sampling error, the simple random sample technique and a large sample size have to be developed.

2. Specific remarks:

The following factors are highly affected the sample size and need to be identified:

• Population Size,
• Margin of Error,
• Confidence Level (level of significance) and
• Standard of Deviation.

Then, the sample size can be estimated by,

Necessary Sample Size = (z-score or t-value)2 * StdDev*(1-StdDev) / (margin of error)2 .

Regards,

Zuhair

@James, I have edited my question with more details.