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What else can I help you with?
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 happens to the standard deviation as the sample size increases?
As the sample size increases, the standard deviation of the sample mean, also known as the standard error, tends to decrease. This is because larger samples provide more accurate estimates of the population mean, leading to less variability in sample means. However, the standard deviation of the population itself remains unchanged regardless of sample size. Ultimately, a larger sample size results in more reliable statistical inferences.
What is the standard deviation of the sample means called?
The standard deviation of the sample means is called the standard error of the mean (SEM). It quantifies the variability of sample means around the population mean and is calculated by dividing the population standard deviation by the square root of the sample size. The SEM decreases as the sample size increases, reflecting improved estimates of the population mean with larger samples.
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?
The larger the sample size the more confident you can be that the data you have collected is representative of what would happen on a larger scale. So if your results seem to prove your hypothesis right then the larger you sample size the more confident you can be in accepting your hypothesis.
What happen to the width of a confidence interval if the sample size is doubled from 100 to 200?
When the sample size is doubled from 100 to 200, the width of the confidence interval generally decreases. This occurs because a larger sample size reduces the standard error, which is the variability of the sample mean. As the standard error decreases, the margin of error for the confidence interval also decreases, resulting in a narrower interval. Thus, a larger sample size leads to more precise estimates of the population parameter.
What will affect the sample size calculation for a clinical trial?
A cost-benefit analysis. In particular, the cost of the experiment, the consequences of getting the wrong result, the rarity (or otherwise) of the condition that you want to study, the variability of that condition in the population.
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.
