This paper investigates methodologies for evaluating the probabilistic value (P-value) of the Kolmogorov–Smirnov (K–S) goodness-of-fit test using algorithmic program development implemented in Microsoft® Visual Basic® (VB). Six methods were examined for the one-sided one-sample and two methods for the two-sided one-sample cumulative sampling distributions in the investigative software implementation that was based on machine-precision arithmetic. For sample sizes n≤2000 considered, results from the Smirnov iterative method found optimal accuracy for K–S P-values≥0.02, while those from the SmirnovD were more accurate for lower P-values for the one-sided one-sample distribution statistics. Also, the Durbin matrix method sustained better P-value results than the Durbin recursion method for the two-sided one-sample tests up to n≤700 sample sizes. Based on these results, an algorithm for Microsoft Excel® function was proposed from which a model function was developed and its implementation was used to test the performance of engineering students in a general engineering course across seven departments.
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research article
Implementation of Kolmogorov–Smirnov P-value computation in Visual Basic®: implication for Microsoft Excel® library function
Page 1727-1741
Received 30 Mar 2011
Accepted 29 May 2011
Published online: 08 Jul 2011
Original Articles
Implementation of Kolmogorov–Smirnov P-value computation in Visual Basic®: implication for Microsoft Excel® library function
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