Runs Test (Wald-Wolfowitz)
Computes the Wald-Wolfowitz runs test, which checks whether a sequence of two values is random or has a pattern. A run is a stretch of consecutive equal values; too few runs indicate clustering (a trend), and too many indicate systematic alternation. By comparing the observed number of runs with the number expected under randomness, the z statistic reveals whether the order of the data is compatible with pure chance. It's useful for checking residuals, time series and number generators. Enter the sequence with two distinct symbols.
Resultado
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Runs Test (Wald-Wolfowitz)
Computes the Wald-Wolfowitz runs test, which checks whether a sequence of two values is random or has a pattern. A run is a stretch of consecutive equal values; too few runs indicate clustering (a trend), and too many indicate systematic alternation. By comparing the observed number of runs with the number expected under randomness, the z statistic reveals whether the order of the data is compatible with pure chance. It's useful for checking residuals, time series and number generators. Enter the sequence with two distinct symbols.
Is the sequence random or does it hide a pattern?
Look at a sequence of ups and downs, hits and misses, heads and tails. Does it look random? The human eye is terrible at this: it tends to see patterns where there are none and to call random what is actually regular. The Wald-Wolfowitz runs test delivers an objective verdict by counting something simple — how many blocks of consecutive equal values the sequence has.
Each block of identical values in a row is a run. In a random sequence there is an expected number of runs that depends on how many elements there are of each type. Too few runs suggest clustering, like a tide that rises and stays up for a long time; too many suggest forced alternation. The z statistic measures how far the observed number of runs strays from that expectation.
Enter the sequence using two distinct symbols, separated by commas or spaces — for example, ones and zeros, or the letters A and B. The tool counts the runs, identifies how many elements there are of each type and returns the z statistic. It's a classic test for checking the randomness of regression residuals, time series and number-generator outputs.
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