It does this by comparing the prediction faults of the two products in excess of a specific time period. The exam checks the null hypothesis the two designs hold the same performance on regular, against the alternative that they don't. If the examination statistic exceeds a significant value, we reject the null hypothesis, indicating that the real difference in the forecast accuracy is statistically important.
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, is surely an extension from the Gaussian random stroll method, wherein, at each time, we may perhaps take a Gaussian step which has a likelihood of p or remain in precisely the same point out by using a chance of 1 ??p
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