The sample standard error.
Random error.
The sample mean will seldom be the same as the population mean due to sampling error. See the related link.
Standard error of the sample mean is calculated dividing the the sample estimate of population standard deviation ("sample standard deviation") by the square root of sample size.
Zero
Sampling Error
standard error
0. The expected value of the sample mean is the population mean, so the expected value of the difference is 0.
No.
The sample standard error.
Random error.
The sample mean will seldom be the same as the population mean due to sampling error. See the related link.
Standard error of the sample mean is calculated dividing the the sample estimate of population standard deviation ("sample standard deviation") by the square root of sample size.
The sampling error is the error one gets from observing a sample instead of the whole population. The bigger it is, the less faith you should have that your sample represents the true value in the population. If it is zero, your sample is VERY representative of the population and you can trust that your result is true of the population.
The sample consisted of the entire population.
You calculate the actual sample mean, and from that number, you then estimate the probable mean (or the range) of the population from which that sample was drawn.
The same basic formula is used to calculate the sample or population mean. The sample mean is x bar and the population mean is mu. Add all the values in the sample or population and divide by the number of data values.