 average(array)
 returns the average of 'array', a synonym for 'mean(array)'
 beta(u, v)
 evaluate the beta function with shape factors 'u' and 'v'
 betai(u, v, x)
 the incomplete beta function
 bincof(n, k)
 the binomial coefficient for 0 < k < n
 binomdist(s, n, p)
 the cumulative binomial distribution for 0 < s < n, and 0 < p < 1
 binomfreq(s, n, p)
 the frequecies (densities) of the binomial distribution for 0 < s < n, and 0 < p < 1
 cauchydist(x, location[, scale=1])
 the cumulative Cauchy (Lorentz) distribution
 cauchyfreq(x, location[, scale=1])
 densities of the Cauchy (Lorentz) distribution
 cauchyinv(p, location[, scale=1])
 the inverse of the cumulative Cauchy (Lorentz) distribution
 chidist(chi2, df)
 returns probability for 'chi2' with 'df' degrees of freedom
 chifreq(chi2, df)
 the chi^{2} density (frequencies) function
 chiinv(p, df)
 returns the critical value for chi2 for probability 'p' with 'df' degrees of freedom,
a replacement for printed versions of the chi2 distribution

classes(start, step, array, range)
 create a frequency distribution using 'start'
and 'step' to define classes for 'array'. Returns the number of items in 'array'
as result and the size of each class in the destination range.
example: classes(0;1;a1:a10;b1:b5)
 correl(range1; range2[;"destination"])
 A synonym for pearson(). For non parametric correlations see
spearman() and kendall().
 count(array)
 count elements of 'array'
examples: count(1, 2, 3), count(a1:a10), count(a1:a10, c1:d10)
 covar(range1; range2)
 returns the covariance between array1 and array2.
 erf(expr)
 evaluate the error function at 'expr'
 erfc(expr)
 the complementary error function
 expdist(x, lamda)
 the cumulative exponential distribution
 expfreq(x, lamda)
 the density function of the exponential distribution
 expinv(p, lamda)
 the inverse of the cumulative exponential distribution
 factorial(expr)
 returns the factorial of 'expr' (expr!) where expr is a positive integer
 fdist(f, df1, df2)
 returns the probability (1alpha) of 'f' with 'df1' degrees of freedom in the numerator and 'df2' in the denominator
 ffreq(f, df1, df2)
 the probability density function of the Fdistribution
 finv(p, df1, df2)
 returns the critical value of the Fdistribution,
a replacement for printed versions of the Fdistribution
 ftest(array1; array2[;"destination"])
 compare variances and return the probability of the Fstatistics.
If destination is given this range is filled with mean, SD, n of array1 and mean, SD, n of array2.
examples: ftest(a1:a10;b1:b10), ftest(a1:a10; 1,2,3,4; "c1:c10")
 gammaln(x)
 returns the natural logarithm of the gamma function, ln(Γ(x))
 gammp(a, x)
 the incomplete gamma function
 gammq(a, x)
 complementary incomplete gamma function
 geomdist(x, p)
 the cumulative geometric distribution
 geomfreq(x, p)
 densities of the geometric distribution
 gmean(array)
 returnes the geometric mean of 'array'
 hmean(array)
 returnes the harmonic mean of 'array'
 hyperdist(k, N, m, n)
 the cumulative hypergeometric distribution
 hyperfreq(k, N, m, n)
 densities of the hypergeometric distribution
 kendall(range1; range2[;"destination"])
 Kendall's non parametric rank correlation.
If destination is given this range is filled with Kendall's tau, the number of standard deviations from zero,
the two sided significance level, and the number of valid cases.
 kurt(array)
 returnes the kurtosis of 'array'
 logisdist(x, location[, scale=1])
 the cumulative logistic distribution
 logisfreq(x, location[, scale=1])
 densities of the logistic distribution
 logisdist(p, location[, scale=1])
 the inverse cumulative logistic distribution
 
 lognormdist(x, m, s)
 cumulative lognormal distribution
 lognormfreq(x, m, s)
 lognormal density function
 lognorminv(p, m, s)
 inverse cumulative lognormal distribution
 max(array)
 highest value of 'array'
examples: max(1, 2, 3), max(a1:a10), max(a1:a10, c1:d10)
 mean(array)
 returns the arithmetic mean of 'array'
examples: mean(1, 2, 3), mean(a1:a10), mean(a1:a10, c1:d10)
 median(array)
 returnes the median of 'array',
a synonym for quartile2(array)
 min(array)
 lowest value of 'array'
examples: min(1, 2, 3), min(a1:a10), min(a1:a10, c1:d10)
 normdist(x, m, s)
 probability of the cumulative normal distribution at 'x' with mean 'm' and standard deviation 's',
a replacement for printed versions of the cumulative normal distribution
 normfreq(x, m, s)
 frequency (density) of the normal distribution at 'x' with mean 'm' and standard deviation 's'.
 norminv(p, m, s)
 return the critical value of the cumulative normal distribution for probability 'p' with mean 'm' and standard deviation 's',
a replacement for printed versions of the inverse cumulative normal distribution
 pearson(array1; array2[;"destination"])
 Pearsons parametric correlation.
If destination is given this range is filled with Pearsons r, Fisher's z, the probability of r <> 0, and the number of valid cases.
 poisdist(x, m)
 the cumulative poisson distribution
 poisfreq(x, m)
 the frequencies (densities) of the poisson distribution
 ptukey(q, nmeans, df[,nranges=1])
 the cumulative density function of the Studentized Range Distribution.
 qtukey(p, nmeans, df[,nranges=1])
 returns the quantiles of the Studentized Range Distribution, the inverse of ptukey().
 quartile1(array)
 calculates the 25% quartile of 'array'
 quartile2(array)
 calculates the 50% quartile of 'array',
a synonym for median(array)
 quartile3(array)
 calculates the 75% quartile of 'array'
 rank(value; array)
 returns the rank of 'value' in 'array' with midtie ranking. If 'value'
is not present in 'array' a rank of 0 is returned.
 regression(range1; range2; "destination")
 linear regression analysis of independent variable 'array1' and dependent variable 'array2'.
The destination range is filled with slope, intersept, mean1, mean2, SE of slope, variance1, variance2, variance of fit, F of regression and significance.
example:regression(a1:a10;b1:b10;"c1:c10")
 skew(array)
 returnes the skewness of 'array'
 spearman(range1; range2[;"destination"])
 Spearmans non parametric rank correlation.
If destination is given this range is filled with sum of squared rank differences, number of SD's the sum differs from expected, the significance of this SD,
Spearmans r_{s}, the probability of r_{s} <> 0, and the number of valid cases.
 stdev(array)
 standard deviation of mean
examples: stdev(1, 2, 3), stdev(a1:a10), stdev(a1:a10, c1:d10)
 sterr(array)
 standard error of mean
examples: sterr(1, 2, 3), sterr(a1:a10), sterr(a1:a10, c1:d10)
 sum(array)
 sum of all values of 'array'
examples: sum(1, 2, 3), sum(a1:a10), sum(a1:a10, c1:d10)
 tdist(t, df)
 returns the probability (1alpha) of 't' with 'df' degrees of freedom
 tfreq(t, df)
 the probability density function of the tdistribution
 tinv(p, df)
 returns the critical t of Student's tdistribution,
a replacement for printed versions of the tdistribution
 ttest(array1; array2[;"destination"])
 compare means and return the probability of the tstatistics.
If destination is given this range is filled with mean, SD, n of array1, mean, SD, n of array2, probability for equal variances, Welch's corrected df, corrected probability.
examples: ttest(a1:a10;6,7,4), ttest(a1:a10; b1:b10; "c1:c10")
 ttest2(range1; range2[;"destination"])
 paired ttest for dependent samples.
If destination is given this range is filled with mean and SD of range1, mean and SD of range2, number of valid cases and probability.
 utest(array1; array2[;"destination"])
 MannWhitney U Test, a non parametric alternative to ttest().
If destination is given this range is filled with rank sum 1, rank sum 2, U, Z, n1, n2, plevel, Z corrected for ties, and the corrected plevel.
 variance(array)
 variance of 'array'
examples: variance(1, 2, 3), variance(a1:a10), variance(a1:a10, c1:d10)
 weibdist(x, shape[, scale=1])
 the cumulative weibull distribution
 weibfreq(x, shape[, scale=1])
 densities of the weibull distribution
 weibinv(p, shape[, scale=1])
 inverse cumulative weibull distribution
