Statistics

avedev description returns average deviation example avedev(number1, number2, ) average description returns the arithmetic mean example average(number1, number2, ) averagea description returns the arithmetic mean example averagea(value1, value2, ) averageif description finds the average of the values in a given array that satisfy a given criteria, and returns the average value of the corresponding values in a second given array example averageif(range, criteria, average range) averageifs description finds the average of the values in a given array that satisfy a set of given criteria example averageifs(average range, criteria range1, criteria1, \[criteria range2, criteria2], ) binomdist description returns the cumulative beta probability density function example binomdist(number s, trials, probability s, cumulative) chidist description returns the chi squared distribution example chidist(x, degrees freedom) chiinv description returns the inverse of chidist example chiinv(probability, degrees freedom) chitest description returns the test for independence chitest returns the value from the chi squared (c2) distribution for the statistic and the appropriate degrees of freedom example chitest(actual range, expected range) confidence description returns the confidence interval example confidence(alpha, standard dev,size) correl description returns the correlation between two sets of data example correl(array1, array2) count description returns the count of the data listed in the arguments example count(value1, value2, ) counta description returns the count of the data listed in the arguments example counta(value1, value2, ) countblank description returns the count of the empty cells listed in the arguments example countblank(range) countif description returns the count of values that meet a specified criteria example countif(range, criteria) covar description returns covariance example covar(array1, array2) critbinom description returns the critical value for the cumulative binomial distribution example critbinom(trials, probability s, alpha) devsq description returns the sum of the squares of the mean deviation example devsq(number1, number2, ) expondist description returns the exponential distribution example expondist(x, lambda, cumulative) fdist description returns the f probability distribution example fdist(x, degrees freedom1, degrees freedom2) finv description returns the inverse of fdist example finv(probability,deg freedom1,deg freedom2) fisher description returns the fisher transformation example fisher(x) fisherinv description returns the inverse of fisher example fisherinv(y) forecast description returns the value forecasted by the linear trend example forecast(x, known ys, known xs) gammadist description returns the gamma distribution example gammadist(x, alpha,beta, cumulative) gammainv description returns the inverse of gammadist example gammainv(p, alpha, beta) gammaln description returns the natural logarithm of gamma function example gammaln(number) geomean description returns the geometric mean example geomean(number1, number2, ) growth description this feature enables you to calculate predicted exponential growth using existing data this calculates and returns an array of values used for the regression analysis example growth(known y's, \[known x's], \[new x's], harmean description returns the harmonic mean example harmean(number1, number2, ) hypgeom dist description returns the probability of a given number of sample successes, given the sample size, population successes and population size example hypgeom dist(sample s, number sample, population s, number population, cumulative) hypgeomdist description returns the hypergeometric distribution example hypgeomdist(sample, numberofsample, population, numberofpopulation) intercept description returns the y intercept of the least squares fit line example intercept(known y's, known x's) kurt description returns the kurtosis of the set of arguments example kurt(number1, number2, ) large description returns the kth largest value example large(array, k) logest description this feature enables you to calculate predicted exponential growth using existing data this calculates and returns an array of values used for the regression analysis example logest(known y's, \[known x's], \[const], \[stats]) loginv description returns the inverse of the lognormdist example loginv(probability, mean, standard dev) lognormdist description returns the cumulative lognormal distribution function example lognormdist(x, mean, standard dev) max description returns the largest value among the arguments example max(number1, number2, ) maxa description returns the largest value among the arguments example maxa(value1, value2, ) median description returns the median value among the arguments example median(number1, number2, ) min description returns the smallest value among the arguments example min(number1, number2, ) mina description returns the smallest value among the arguments example mina(value1, value2, ) mode description returns the most frequently occurring value example mode(number1, number2, ) negbinomdist description returns the negative binomial distribution example negbinomdist(number f, number s, probability s) normdist description returns the normal cumulative distribution example normdist(x, mean, standard dev, cumulative) norminv description returns the inverse of normdist example norminv(probability, mean, standard dev) normsdist description returns the probability that the observed value of a standard normal random variable will be less than or equal to the parameter example normsdist(value) normsinv description returns the standard normal random variable that has mean 0 and standard deviation 1 example normsdist(value) pearson description returns the pearson product example pearson(array1, array2) percentile description returns the kth percentile of the given values example percentile(array, k) percentrank description returns the position of a value in the range of values example percentrank(array, x, significance) permut description returns the number of permutations example permut(n, k) poisson description returns the poisson distribution example poisson(x, mean, cumulative) prob description returns a probability example prob(x range, prob range, lower limit, upper limit) quartile description returns which quarter a value belongs to within an ordered set of data example quartile(array, quart) rank description returns the position of a value in an ordered list example rank(number, ref, order) rsq description returns the square of the pearson product moment correlation coefficients example rsq(known y's, known x's) skew description returns the skewness of a distribution example skew(number1, number2, ) slope description returns the slope of the linear regression line example slope(known y's, known x's) small description returns the kth smallest value example small(array, k) standardize description returns the normalized value example standardize(x, mean, standard dev) stdev description returns the sample standard deviation example stdev(number1, number2, ) stdeva description returns the sample standard deviation example stdeva(value1, value2 , ) stdevp description returns the population standard deviation example stdevp(number1, number2, ) stdevpa description returns the population standard deviation example stdevpa(value1, value2, ) steyx description returns the standard error example steyx(known y's, known x's) trimmean description returns the mean after removing out liers example trimmean(array, percent) var description returns the sample variance example var(number1, number2, number n) vara description returns the sample variance example vara(value1, value2, value n) varp description returns the population variance example varp(listofvalues) varpa description returns the population variance example varpa(value1, value2, ) weibull description returns the weibull distribution example weibull(x,alpha,beta,cumulative) ztest description returns the p value of a z test example ztest(array, u0, sigma)