Search results
Results From The WOW.Com Content Network
Correction factor versus sample size n.. When the random variable is normally distributed, a minor correction exists to eliminate the bias.To derive the correction, note that for normally distributed X, Cochran's theorem implies that () / has a chi square distribution with degrees of freedom and thus its square root, / has a chi distribution with degrees of freedom.
Since the square root introduces bias, the terminology "uncorrected" and "corrected" is preferred for the standard deviation estimators: s n is the uncorrected sample standard deviation (i.e., without Bessel's correction) s is the corrected sample standard deviation (i.e., with Bessel's correction), which is less biased, but still biased
Unlike in the case of estimating the population mean of a normal distribution, for which the sample mean is a simple estimator with many desirable properties (unbiased, efficient, maximum likelihood), there is no single estimator for the standard deviation with all these properties, and unbiased estimation of standard deviation is a very ...
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
where X is a random variable which we have sampled N times, m is the sample mean, k is a constant and s is the sample standard deviation. This inequality holds even when the population moments do not exist, and when the sample is only weakly exchangeably distributed; this criterion is met for randomised sampling.
Newton's method is ideal to solve this problem because the first derivative of (), which is an integral of the normal standard distribution, is the normal standard distribution, and is readily available to use in the Newton's method solution.
In most such problems, if the standard deviation of the errors were known, a normal distribution would be used instead of the t distribution. Confidence intervals and hypothesis tests are two statistical procedures in which the quantiles of the sampling distribution of a particular statistic (e.g. the standard score ) are required.
This inversion technique is also known as the fixed point formula of SNR. Earlier works [9] [15] on the method of moments usually use a root-finding method to solve the problem, which is not efficient. First, the ratio of the sample mean to the sample standard deviation is defined as r, i.e., = ′ / /. The fixed point formula of SNR is ...