The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
It all depends on what you do with the information that you note. If you count up the number of odds [or evens] in the five rolls, your sample space is {0,1,2,3,4,5} with size 6. If you look for whether you had more odds than evens your sample space is {Y,N}, with size 2. If you subtract the number of even outcomes from the number of odd outcomes, your sample space is {-5,-4,,...,4,5} which is of size 11.
A random sample of size 36 is taken from a normal population with a known variance If the mean of the sample is 42.6. Find the left confidence limit for the population mean.
Assuming traditional cubic dice, the sample space consists of 216 points.
You cannot from the information provided.
With a good sample, the sample mean gets closer to the population mean.
The sample space for 1 roll is of size 6.
When a fair die is rolled, there are 6 possible outcomes {1,2,3,4,5,6}. The sample space consists of 6 points, so its size is 6.
Not sure about the relevance of sizzle! The size of the sample space is 46656.
The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.
Zero
It should reduce the sample error.
In general the mean of a truly random sample is not dependent on the size of a sample. By inference, then, so is the variance and the standard deviation.
It all depends on what you do with the information that you note. If you count up the number of odds [or evens] in the five rolls, your sample space is {0,1,2,3,4,5} with size 6. If you look for whether you had more odds than evens your sample space is {Y,N}, with size 2. If you subtract the number of even outcomes from the number of odd outcomes, your sample space is {-5,-4,,...,4,5} which is of size 11.
N is neither the sample or population mean. The letter N represents the population size while the small case letter n represents sample size. The symbol of sample mean is x̄ ,while the symbol for population mean is µ.
The standard deviation. There are many, and it's easy to construct one. The mean of a sample from a normal population is an unbiased estimator of the population mean. Let me call the sample mean xbar. If the sample size is n then n * xbar / ( n + 1 ) is a biased estimator of the mean with the property that its bias becomes smaller as the sample size rises.