Trying
k
the means does not change
The distribution of sample means will not be normal if the number of samples does not reach 30.
No, it is not.
always zero
could a sample set have the same range but different means
The mean of the sample means, also known as the expected value of the sampling distribution of the sample mean, is equal to the population mean. In this case, since the population mean is 10, the mean of the sample means is also 10. The standard deviation of the sample means, or the standard error, would be the population standard deviation divided by the square root of the sample size, which is ( \frac{2}{\sqrt{25}} = 0.4 ).
No, to both questions.
Not necessarily. It needs to be a random sample from independent identically distributed variables. Although that requirement can be relaxed, the result will be that the sample means will diverge from the Normal distribution.
The sample is not a perfect representation of the population.
Half-life of 2000 years means that after 2000 years, half of the sample will decay - so of course the other half of the sample is still around.Half-life of 2000 years means that after 2000 years, half of the sample will decay - so of course the other half of the sample is still around.Half-life of 2000 years means that after 2000 years, half of the sample will decay - so of course the other half of the sample is still around.Half-life of 2000 years means that after 2000 years, half of the sample will decay - so of course the other half of the sample is still around.
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.