![]() , which ultimate depend on the calculation of z-scores and using the standard normal distribution. The parameter, z, represents the output we are interested in and. For example, NORM.S.DIST (1,TRUE) returns the value 0.8413 and NORM.S.DIST (1,FALSE) returns the value 0.2420. Normal probabilities for sampling distributions The NORM.S.DIST function returns values for the standard normal cumulative distribution function (CDF) and the standard normal probability density function (PDF). ![]() Using other calculators you can compute general If you want to compute the probability of the event \( a \le X\le b\), we make the crucial observation that the events Indeed, consider a normally distribution variable \(X\), with population \(\mu\) and standard deviation \(\sigma\). The standard normal distribution probabilities play a crucial role in the calculation of all normal distribution probabilities. The answer is simple, the standard normal distribution is the normal distribution when the population mean \(\mu\) is 0 and the population standard deviation is \(\sigma\) is 1. Well, that is the obvious first question we need to answer: what is the standard normal distribution. Why is that? Because of normalization of scores allows you to have to events that are equivalent. That is right: if you know how to compute Standard Normal Distribution probabilities, then you can compute the probabilities of any normal distribution. The Standard Normal Distribution is one of the most important distributions because it allows you to compute the probabilities associated to ANY normal distribution.
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