The reliability of a sample size in representing a population doesn't solely depend on the percentage it represents of the total population. It also depends on how the sample is selected. If the sample is randomly selected and represents a diverse cross-section of the population, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000.

However, if the sample is not randomly selected or does not represent a diverse cross-section of the population, it may not be reliable, regardless of its size.

In statistics, a common rule of thumb is that a sample size of at least 30 is needed for the Central Limit Theorem to hold, which allows for the use of normal distribution approximations. However, larger sample sizes, like 1,200, generally provide a better approximation of the population.

So, in conclusion, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000, but it depends on how the sample is selected.

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The reliability of a sample size in representing a population doesn't solely depend on the percentage it represents of the total population. It also depends on how the sample is selected. If the sample is randomly selected and represents a diverse cross-section of the population, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000.

However, if the sample is not randomly selected or does not represent a diverse cross-section of the population, it may not be reliable, regardless of its size.

In statistics, a common rule of thumb is that a sample size of at least 30 is needed for the Central Limit Theorem to hold, which allows for the use of normal distribution approximations. However, larger sample sizes, like 1,200, generally provide a better approximation of the population.

So, in conclusion, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000, but it depends on how the sample is selected.

Knowee AI · Accepted Answer

The reliability of a sample size in representing a population doesn't solely depend on the percentage it represents of the total population. It also depends on how the sample is selected. If the sample is randomly selected and represents a diverse cross-section of the population, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000.

However, if the sample is not randomly selected or does not represent a diverse cross-section of the population, it may not be reliable, regardless of its size.

In statistics, a common rule of thumb is that a sample size of at least 30 is needed for the Central Limit Theorem to hold, which allows for the use of normal distribution approximations. However, larger sample sizes, like 1,200, generally provide a better approximation of the population.

So, in conclusion, a sample size of 1,200 could potentially be a reliable measure for a population of 6,000, but it depends on how the sample is selected.

Is a sample size of 1,200 a reliable measure for a population of 6,000?Yes, 1,200 is a large enough percentage of the population and should be representative.No, 1,200 is not a large enough percentage of the population and is not representative.

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