What is the way to calculate standard error in Microsoft Excel

[Edha]

How do I calculate standard error in excel. I am not getting the exact syntax to apply.

[Gania]

The formula you can try is =STDEV(range) / SQRT(COUNT(range)). Note that in Excel, STDEV is the sample std dev (variance computed using n-1), not the population std dev (STDEVP; variance computed using n).

[Shurod]

If your referring to statistics, I think you mean standard deviation (how far data is off from the average). In which case, you want to use STDEV. Assuming that your data are as :Known y's are in range A2: A20 & Known x's are in tange B2 : B20. Then try this =STEYX(A2:A20,B2:B20. Hope this is helpful.

[Erakna]

I have a good resource that can be helpful for you. The below link has detail info on the same. Try the formula samples that are mentioned below. Other than this there is one more reference you can try. Use the following = STDEVP (A1: A100) / COUNT (A1: A100) ^ 0.5

XL: Formula to Calculate the Standard Error of the Mean

[DanielaA]

The standard error is also called typical deviation is the square root of the variance. Both the typical deviation and variance are measures of dispersion. If there are n values: x1, x2, ... , X is the arithmetic mean and variance M is defined as: s ^ 2 = 1 / n Sum i = 1 to n of (xi-M) ^ 2. Universal notation for the variance is s squared. The typical deviation is:

• s = sqrt (s ^ 2)
• If you are using Excel STDEV function is = ()
• In the advanced courses shows that to calculate the variance should be divided by (n-1) instead of n. That gives a better estimate of the variance of the population.
• In Excel uses (n-1) for both the variance whose function is = var (), as typical for the diversion.
• Population or universe is the set of all elements under study, for example, I consider the height of the children 6 years of a population of 2,000,000 children aged 6 years, assuming you can not measure all take a sample for example, 300 random children.

This is a sample and the sample used s ^ 2 and s. The population variance is also typical and unique diversion while the samples vary with the sample. These unique values ​​are called parameters and used the Greek letter sigma squared to the variance and one-sigma deviation for the typical. s ^ 2 is an estimate of sigma squared. Dividing by (n-1) instead of n get a better estimate of sigma squared, in fact if I use n get an estimator with mean squared but not sigma (n-1) / n * sigma square is said to be a biased estimator.