of the mean, i.e., the larger the size of the sample mean, the smaller shall be the S.E. This equation for standard error signifies that the size of the sample will have an inverse effect on the S.D. This distribution has two key parameters: the mean (µ) and the standard deviation (σ) which plays a key role in assets return calculation and in risk management strategy. However, few uses of the formula do assume a normal distribution Normal Distribution Normal Distribution is a bell-shaped frequency distribution curve which helps describe all the possible values a random variable can take within a given range with most of the distribution area is in the middle and few are in the tails, at the extremes. read more) of the sample data of the mean, “N” represents the sample size while “σ” signifies the S.D.

( standard deviation Standard Deviation Standard deviation (SD) is a popular statistical tool represented by the Greek letter 'σ' to measure the variation or dispersion of a set of data values relative to its mean (average), thus interpreting the data's reliability. This is higher because of the fact that standard errors use sample data or statistics while standard deviations use parameters or population data. It not be confused with standard deviation. Standard Error or SE is used to measure the accurateness with the help of a sample distribution that signifies a population taking standard deviation into use, or in other words, it can be understood as a measure with respect to the dispersion of a sample mean concerned with the population mean.

Calculate standard error