No it is not correct.
Differing from standard deviations, the coded deviation method finds the mean of grouped data from the assumed mean using unit deviations. This is a shorter way to find the mean.
Did you mean, "How do you calculate the 99.9 % confidence interval to a parameter using the mean and the standard deviation?" ? The parameter is the population mean μ. Let xbar and s denote the sample mean and the sample standard deviation. The formula for a 99.9% confidence limit for μ is xbar - 3.08 s / √n and xbar + 3.08 s / √n where xbar is the sample mean, n the sample size and s the sample standard deviation. 3.08 comes from a Normal probability table.
You cannot because the median of a distribution is not related to its standard deviation.
The variance or standard deviation.
You cannot because the standard deviation is not related to the median.
No it is not correct.
=stdev(...) will return the N-1 weighted sample standard deviation. =stdevp(...) will return the N weighted population standard deviation.
You calculate the standard error using the data.
Differing from standard deviations, the coded deviation method finds the mean of grouped data from the assumed mean using unit deviations. This is a shorter way to find the mean.
Did you mean, "How do you calculate the 99.9 % confidence interval to a parameter using the mean and the standard deviation?" ? The parameter is the population mean μ. Let xbar and s denote the sample mean and the sample standard deviation. The formula for a 99.9% confidence limit for μ is xbar - 3.08 s / √n and xbar + 3.08 s / √n where xbar is the sample mean, n the sample size and s the sample standard deviation. 3.08 comes from a Normal probability table.
You cannot because the median of a distribution is not related to its standard deviation.
Standard deviation can be calculated using non-normal data, but isn't advised. You'll get abnormal results as the data isn't properly sorted, and the standard deviation will have a large window of accuracy.
The variance or standard deviation.
The standard deviation stretch is used to stretch the output values using a normal distribution. The result of this stretch is similar to what is seen by the human eye.
The standard deviation, in itself, cannot be high nor low. If the same measurements were recorded using a unit that was a ten times as large (centimetres instead of millimetres), the standard deviation for exactly the same data set would be 1.8. And if they were recorded in metres the sd would be 0.018
The answer depends on what functions are built into your calculator. Read the calculator manual.