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How large would your sample have to be for appropriate estimation of the whole population?
First you have chose an estimator for what you want to know about the population. In general the level of variability in the result that any estimator provides will depend on the variability in the population. Therefore, the greater the variability in the population the larger your sample size must be. You will also need to decide how much precision is required in your estimate. The more precision you require the greater your sample size will have to be.
Is it desirable to have a two sample test with equal sizes?
If they are not matched pairs, it does not really matter. If the combined sample size is fixed (because of costs, say) then it is better to have a larger sample where more variability is expected.
How To Determine Sample Size?
I've included a couple of links. Statistical theory can never tell you how many samples you must take, all it can tell you the expected error that your sample should have given the variability of the data. Worked in reverse, you provide an expected error and the variability of the data, and statistical theory can tell you the corresponding sample size. The calculation methodology is given on the related links.
What is the sample size for a population of 20000?
The sample size will depend on a number of factors other than the populatoin.These include:the resources (time, money) available for data collection, cleaning and validation, input and storage, and analysis;the implications of getting the answer wrong;the variability of the characteristic that is being measured;whether or not a simple random sample is the best sampling scheme.
What is the difference between t-distribution and standard normal distribution?
the t distributions take into account the variability of the sample standard deviations. I think that it is now common to use the t distribution when the population standard deviation is unknown, regardless of the sample size.
How does sample size affect validity of results in a research?
A large sample reduces the variability of the estimate. The extent to which variability is reduced depends on the quality of the sample, what variable is being estimated and the underlying distribution for that variable.
Why do smaller populations need larger sample sizes?
They do not. Population size does not affect the sample size. The variability of the characteristic that you are trying to measure and the required accuracy will determine the appropriate sample size.
What things might influence the prediction while taking a sample?
Some factors that might influence the prediction while taking a sample include the size of the sample, the representativeness of the sample compared to the population, the variability within the sample, and the method of sampling used. These factors can impact the accuracy and reliability of the prediction based on the sample.
How large would your sample have to be for appropriate estimation of the whole population?
First you have chose an estimator for what you want to know about the population. In general the level of variability in the result that any estimator provides will depend on the variability in the population. Therefore, the greater the variability in the population the larger your sample size must be. You will also need to decide how much precision is required in your estimate. The more precision you require the greater your sample size will have to be.
What sample size is sufficient for stat?
A sample size of one is sufficient to enable you to calculate a statistic.The sample size required for a "good" statistical estimate will depend on the variability of the characteristic being studied as well as the accuracy required in the result. A rare characteristic will require a large sample. A high degree of accuracy will also require a large sample.
Is it desirable to have a two sample test with equal sizes?
If they are not matched pairs, it does not really matter. If the combined sample size is fixed (because of costs, say) then it is better to have a larger sample where more variability is expected.
How To Determine Sample Size?
I've included a couple of links. Statistical theory can never tell you how many samples you must take, all it can tell you the expected error that your sample should have given the variability of the data. Worked in reverse, you provide an expected error and the variability of the data, and statistical theory can tell you the corresponding sample size. The calculation methodology is given on the related links.
How does sample size affect your level of confidence in accepting a hypothesis?
A larger sample size generally leads to increased confidence in accepting a hypothesis, as it can provide more representative data and reduce the impact of random variability. However, the relationship between sample size and confidence levels also depends on factors like the variability within the data and the effect size of the hypothesis being tested.
What will affect the sample size calculation for a clinical trial?
Factors that will affect the sample size calculation for a clinical trial include the effect size (magnitude of the treatment effect), desired level of confidence, statistical power, variability in outcome measures, and the type of statistical test being used. Additionally, the expected dropout rate, study design, and practical considerations such as cost and feasibility can also impact the sample size calculation.
What is the sample size for a population of 20000?
The sample size will depend on a number of factors other than the populatoin.These include:the resources (time, money) available for data collection, cleaning and validation, input and storage, and analysis;the implications of getting the answer wrong;the variability of the characteristic that is being measured;whether or not a simple random sample is the best sampling scheme.
Does the standard deviation of x decrease in magnitude as the size of the sample gets smaller?
No. But a small sample will be a less accurate predictor of the standard deviation of the population due to its size. Another way of saying this: Small samples have more variability of results, sometimes estimates are too high and other times too low. As the sample size gets larger, there's a better chance that your sample will be close to the actual standard deviation of the population.
What is the difference between t-distribution and standard normal distribution?
the t distributions take into account the variability of the sample standard deviations. I think that it is now common to use the t distribution when the population standard deviation is unknown, regardless of the sample size.
