- 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 chi2 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 (1-alpha) 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 F-distribution
- finv(p, df1, df2)
- returns the critical value of the F-distribution,
a replacement for printed versions of the F-distribution
- ftest(array1; array2[;"destination"])
- compare variances and return the probability of the F-statistics.
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
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- 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 mid-tie 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 rs, the probability of rs <> 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 (1-alpha) of 't' with 'df' degrees of freedom
- tfreq(t, df)
- the probability density function of the t-distribution
- tinv(p, df)
- returns the critical t of Student's t-distribution,
a replacement for printed versions of the t-distribution
- ttest(array1; array2[;"destination"])
- compare means and return the probability of the t-statistics.
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 t-test 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"])
- Mann-Whitney U Test, a non parametric alternative to t-test().
If destination is given this range is filled with rank sum 1, rank sum 2, U, Z, n1, n2, p-level, Z corrected for ties, and the corrected p-level.
- 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
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