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If there are three different samples of the same size from a set population is it possible to get three different values for the same statistic?
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If there are 3 different samples from a set population can you get 3 different values for the same statistic?
Yes you can.
What is sample distribution?
Theoretically, it is the distribution of a statistic based on all possible samples of a given size. In practice, it may be the distribution under repeated samples.
What do you mean by a statistic and its sampling distribution?
A statistic is a summary measure of some characteristic of a population. If you were to take repeated samples from the population you would not get the same statistic each time - it would vary. And the set of values you would get is its sampling distribution.
How many different simple random samples of 7 are possible from a pool of 25?
There are 25C7 different samples of seven from a pool of 25.25C7 = 25!/(7!(25-7)!) = 480 700 different samples of 7
What is a sampling variability?
A sampling variability is the tendency of the same statistic computed from a number of random samples drawn from the same population to differ.
If there are 3 different samples from a set population can you get 3 different values for the same statistic?
Yes you can.
What is a sampling distribution?
The sampling distribution for a statistic is the distribution of the statistic across all possible samples of that specific size which can be drawn from the population.
What is the distribution of values taken by a statistic in all possible samples of equal size from the same population?
It is the sampling distribution of that variable.
What is the meaning of Sampling distribution of the test statistic?
Given any sample size there are many samples of that size that can be drawn from the population. In the population is N and the sample size in n, then there are NCn, but remember that the population can be infinite. A test statistic is a value that is calculated from only the observations in a sample (no unknown parameters are estimated). The value of the test statistic will change from sample to sample. The sampling distribution of a test statistic is the probability distribution function for all the values that the test statistic can take across all possible samples.
What is the purpose of a sampling distribution?
A statistic based on a sample is an estimate of some population characteristic. However, samples will differ and so the statistic - which is based on the sample - will take different values. The sampling distribution gives an indication of ho accurate the sample statistic is to its population counterpart.
How many simple random samples of size 5 can be selected from a population of size 35?
There are 324,632 possible samples.
What is sample distribution?
Theoretically, it is the distribution of a statistic based on all possible samples of a given size. In practice, it may be the distribution under repeated samples.
If repeating an experiment many times with different samples what values for the sample means would be possible?
The answer depends on the population and is described by the sampling distribution of the mean.
What do you mean by a statistic and its sampling distribution?
A statistic is a summary measure of some characteristic of a population. If you were to take repeated samples from the population you would not get the same statistic each time - it would vary. And the set of values you would get is its sampling distribution.
What is success independent samples design?
different samples of respondents from the population complete the survey over a time period
How many different simple random samples of 7 are possible from a pool of 25?
There are 25C7 different samples of seven from a pool of 25.25C7 = 25!/(7!(25-7)!) = 480 700 different samples of 7
What is the difference a parameter and a statistic?
A parameter is a number describing something about a whole population. eg population mean or mode. A statistic is something that describes a sample (eg sample mean)and is used as an estimator for a population parameter. (because samples should represent populations!)
