CALC.percentrank(array, x, significance)
CALC.binomdist(number_s, trials, probability_s, cumulative)
CALC.expondist(x, lambda, cumulative)
CALC.forecast(x, known_y_values, known_x_values)
CALC.frequency(data_array, bins_array)
CALC.hypgeomdist(sample_s, number_sample, population_s, number_population)
CALC.intercept(arrayY, arrayX)
CALC.negbinomdist(number_f, number_s, probability_s)
CALC.percentrank(array, x, significance)
CALC.permut(number, number_chosen)
CALC.poisson(x, mean, cumulative)
CALC.prob(arrayx, arrayprob, lower_limit, upper_limit)
CALC.rank(number, array, order)
CALC.rsq(known_y_values, known_x_values)
Array is the array or range of data with numeric values that defines relative standing. X is the value for which you want to know the rank. Significance is an optional value that identifies the number of significant digits for the returned percentage value.
Example
CALC.percentrank([13,12,11,8,4,3,2,1,1,1],2,3);
// returns 0.333
(percent rank of the element 2 in the list above)
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