What is Standard Error and it's importance?
In Statistics and data analysis standard error has great importance. The term "standard error" is used to refer to the standard deviation of various sample statistics, such as the mean or median. For example, the "standard error of the mean" refers to the standard deviation of the distribution of sample means taken from a population. The smaller the standard error, the more representative the sample will be of the overall population.
The relationship between the standard error and the standard deviation is such that, for a given sample size, the standard error equals the standard deviation divided by the square root of the sample size. The standard error is also inversely proportional to the sample size; the larger the sample size, the smaller the standard error because the statistic will approach the actual value.
How to Calculate Standard Error of Data given Variance?
Standard Error of Data given Variance calculator uses Standard Error of Data = sqrt(Variance of Data/Sample Size) to calculate the Standard Error of Data, Standard Error of Data given Variance formula is defined as the standard deviation of the sample means of different samples inside a single population, and calculated using the variance of the data. Standard Error of Data is denoted by σ_{μ} symbol.
How to calculate Standard Error of Data given Variance using this online calculator? To use this online calculator for Standard Error of Data given Variance, enter Variance of Data (V) & Sample Size (N) and hit the calculate button. Here is how the Standard Error of Data given Variance calculation can be explained with given input values -> 1.341641 = sqrt(18/10).