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2011
In studying methods for the analysis of quantitative data, we first focused on problems involving a single sample of numbers and then turned to a comparative analysis of two different samples. Now we are ready for the analysis of several samples.
Jay L. Devore, Kenneth N. Berk
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In studying methods for the analysis of quantitative data, we first focused on problems involving a single sample of numbers and then turned to a comparative analysis of two different samples. Now we are ready for the analysis of several samples.
Jay L. Devore, Kenneth N. Berk
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1998
Analysis of Variance (ANOVA) is used to test whether the variability in response data taken for different levels of manipulated variables can be attributed just to random fluctuations, or is caused by the impact of different input levels. Such an approach has been briefly discussed in Section 8.5.
Bernard Ycart +2 more
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Analysis of Variance (ANOVA) is used to test whether the variability in response data taken for different levels of manipulated variables can be attributed just to random fluctuations, or is caused by the impact of different input levels. Such an approach has been briefly discussed in Section 8.5.
Bernard Ycart +2 more
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, 2016 1981
In Chapter 15 we considered two-way crossed classifications, and in this section we discuss briefly the theory of the three-way crossed classification with one observation per cell. The theory is based upon principles discussed in earlier chapters. As an example we shall use some data from an experiment discussed by Lemus (1960), slightly modified.
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In Chapter 15 we considered two-way crossed classifications, and in this section we discuss briefly the theory of the three-way crossed classification with one observation per cell. The theory is based upon principles discussed in earlier chapters. As an example we shall use some data from an experiment discussed by Lemus (1960), slightly modified.
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1974
We have used the t-test in chapter 4 to compare the means of two samples, but we often need to compare the mean values of larger numbers of samples. For example is there a significant difference between the mean diameter of four samples of a species of Jurassic pollen, is the porosity of five sandstones different?
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We have used the t-test in chapter 4 to compare the means of two samples, but we often need to compare the mean values of larger numbers of samples. For example is there a significant difference between the mean diameter of four samples of a species of Jurassic pollen, is the porosity of five sandstones different?
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Randomization and the Analysis of Variance
Biometrics, 1975This paper attempts to strengthen faith in randomization, first by defining it in general and second by showing how it is the fundamental means, in many experiments, of generating the probability space. It is defined by the natural structure of the experimental units (E.U.'s) not by a particular experimental design imposed on that structure.
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1971
The statistical significance of a difference between two means was discussed in earlier chapters. What if there are more than two means to compare? Not infrequently one is confronted with several groups, wondering whether they may all be regarded as samples of the same population, or alternatively whether the groups differ so considerably from one ...
W. Sluckin, T. G. Connolly
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The statistical significance of a difference between two means was discussed in earlier chapters. What if there are more than two means to compare? Not infrequently one is confronted with several groups, wondering whether they may all be regarded as samples of the same population, or alternatively whether the groups differ so considerably from one ...
W. Sluckin, T. G. Connolly
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Permutational Multivariate Analysis of Variance (PERMANOVA)
, 2017Marti J. Anderson
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1978
The methods of analysis of variance are now so widely used in experimental work that some knowledge of them is desirable. An introduction to them is given in this chapter.
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The methods of analysis of variance are now so widely used in experimental work that some knowledge of them is desirable. An introduction to them is given in this chapter.
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