An estimate for the mean of a set of observations is just that - an estimate. Another set of observations will give a different estimates. These estimates for the mean will have a distribution which will have a standard error. If you have two sub-populations, the mean of each sub-population will have a standards error and the se of the difference between the means is a measure of the variability of the estimates of the difference.A typical school work example: the heights of men and of women. There will be a mean height for men, Hm, with a se for men's heights and a mean height for women, Hw, with its own se. The difference in mean heights is Hm - Hw and which will have an estimated se.
the purpose and function of standard error of mean
Type I error.
yes
Yes
Estimates of the mean are then more reliable.
the sample mean is used to derive the significance level.
The standard score associated with a given level of significance.
Standard error is random error, represented by a standard deviation. Sampling error is systematic error, represented by a bias in the mean.
An estimate for the mean of a set of observations is just that - an estimate. Another set of observations will give a different estimates. These estimates for the mean will have a distribution which will have a standard error. If you have two sub-populations, the mean of each sub-population will have a standards error and the se of the difference between the means is a measure of the variability of the estimates of the difference.A typical school work example: the heights of men and of women. There will be a mean height for men, Hm, with a se for men's heights and a mean height for women, Hw, with its own se. The difference in mean heights is Hm - Hw and which will have an estimated se.
It would help to know the standard error of the difference between what elements.
Standard error is a measure of precision.
The standard error is the standard deviation divided by the square root of the sample size.
The standard error increases.
the purpose and function of standard error of mean
The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.The standard error should decrease as the sample size increases. For larger samples, the standard error is inversely proportional to the square root of the sample size.
You calculate the standard error using the data.