## Proceedings of the Statistical Computing Section |

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### Contents

Data Mining | 1 |

Tips for Data Mining Practitioners | 9 |

MAPLE Integrated into the Instruction of Probability and Statistics | 19 |

Copyright | |

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### Common terms and phrases

algorithm AMVUE analysis applied asymptotic bandwidth Bayesian bivariate bootstrap calculated Chen classifiers coefficients computed covariance cover solution cross-validation customers data mining data set DataSphere decile decision trees defined denote density estimate edits eigenfunctions elemental regressions equation error distribution example explanatory variables factor Figure formula frequency function gamma gamma distribution gauss Gibbs sampler given heteroscedastic hidden Markov models hypothesis independent iteration kernel Key Words level crossing likelihood linear regression Markov Markov chain Mathematical matrix mean method multivariate multivariate test node nonlinear normal distribution observed order statistics P-value parameters periodogram plot Poisson polynomial posterior predicted prime cover probability problem procedure purchase quantile quantile estimators random sample random variables rbias rmse ripple-fired row vectors Section sequence simulation smoothing squared error standard subsets SVCs Table technique TEE(ap test statistic tested list Theorem tion truncated univariate values variance variation weighted zero