## Statistics for experimenters: an introduction to design, data analysis, and model buildingIntroduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for ``statistical thinking'' by using examples drawn from actual case studies. |

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### Contents

SCIENCE AND STATISTICS | 1 |

COMPARING TWO TREATMENTS | 19 |

Appendix 2A Calculation of the Sample Average Sample | 53 |

Copyright | |

20 other sections not shown

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16 runs addition analysis of variance Answer Appendix appropriate approximately assumption autocorrelation balanced incomplete block batch binomial distribution block variables calculated catalyst chapter column compute concentration confidence interval confounding pattern consider contour correlation defining relation degrees of freedom denote example Exercise experiment experimental design experimental error F distribution fitted fN fN following data four fractional factorial design frequency function grand average half-fraction illustrated independent investigation Latin square least squares estimates linear main effects mean square measured mechanistic model normal distribution null hypothesis observations obtained parameters particular plant plot Poisson distribution population possible probability problem produced random sampling randomly ratio reactor reference distribution replicated residuals response surface sample variance shown in Figure shown in Table shows significance level standard deviation standard error statistical statistically independent sum of squares Suppose temperature transformation treatment averages two-factor interactions variance a2 variance table variation vector yield zero