calorie
发表于 2025-3-23 10:17:08
Comparing More Than Two Groups: One-Way ANOVA,r visualizing the logical structure of an experiment, and derive the specification of a suitable linear model from the experiment’s diagram. Finally, we briefly remark on the one-way analysis of variance with unbalanced data.
恸哭
发表于 2025-3-23 16:00:27
Improving Precision and Power: Blocked Designs,rpretation of block-by-treatment interactions. We make extensive use of Hasse diagrams to discuss different variants of blocked designs. We introduce simple linear mixed models as an alternative to analysis of variance, particularly for incomplete block designs.
代理人
发表于 2025-3-23 21:40:35
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overhaul
发表于 2025-3-24 01:30:08
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青石板
发表于 2025-3-24 06:12:44
Comparing Treatment Groups with Linear Contrasts, procedures control the family-wise error rate, and we introduce four commonly used methods by Bonferroni, Tukey, Dunnett, and Scheffé. Finally, we discuss a larger real-life example to demonstrate the use of linear contrasts and highlight the need for careful definition of contrasts to correctly reflect the desired comparisons.
Mumble
发表于 2025-3-24 08:10:28
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hardheaded
发表于 2025-3-24 10:55:32
Many Treatment Factors: Fractional Factorial Designs,tors allow derivation of all effect aliases in a design. We discuss using fractional factorials with blocks, and we show how multiple generators can then be used to disentangle confounded effects. Screening experiments are an important application of fractional factorial designs; we also introduce Plackett–Burman designs for this purpose.
Incisor
发表于 2025-3-24 16:51:26
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Emg827
发表于 2025-3-24 19:09:05
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嘴唇可修剪
发表于 2025-3-25 02:38:44
Textbook 2021nces, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental condit