~ @8Pack*?8 @EACT EACT1 f!`TXP|āȁ d < @======060701 =======vDistribution istThere is a variety of different types of distribution, but the most well-known is normal distribution, which is essential for performing statistical calculations. Normal distribution is a symmetrical distribution centered on the greatest occurrences of mean data (highest frequency), with the frequency decreasing as you move away from the center. Poisson distribution, geometric distribution, and various other distribution shapes are also used, depending on the data type. oisCertain trends can be determined once the distribution shape is determined. You can calculate the probability of data taken from a distribution being less than a specific value. oertFor example, distribution can be used to calculate the yield rate when manufacturing some product. Once a value is established as the criteria, you can calculate normal probability when estimating what percent of the products meet the criteria. oConversely, a success rate target (80% for example) is set up as the hypothesis, and normal distribution is used to estimate the proportion of the products will reach this value. onvNormal probability density calculates the probability density of normal distribution from a specified x value. NoNormal distribution probability calculates the probability of normal distribution data falling between two specific values. InInverse cumulative normal distribution calculates a value that represents the location within a normal distribution for a specific cumulative probability. StStudent-t probability density calculates t probability density from a specified x value. StStudent-t distribution probability calculates the probability of t distribution data falling between two specific values. StLike t distribution, distribution probability can also be calculated for V, F, Binomial, Poisson, and Geometric distributions. ike@STAT[EXE]8Pack*?( @GUIDE