CALC.pearson(array1, array2)
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)
Returns the Pearson product moment correlation coefficient, r, a dimensionless index that ranges from -1.0 to 1.0 inclusive and reflects the extent of a linear relationship between two data sets.
Example
CALC.pearson([9,7,5,3,1],[10,6,1,5,3]);
// returns 0.6993
| << CALC.negbinomdist(number_f, number_s, probability_s) | © 1996-2013 InetSoft Technology Corporation (v11.4) | CALC.percentile(array, k) >> |