Posts Tagged ‘ factor ’

N-Way ANOVA

September 15, 2012
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N-Way ANOVA example Two-way analysis of variance is where the rubber hits the road, so to speak. This extends the concepts of ANOVA with only one factor to two factors. When there are two factors this means that there can be an interaction between the two factors that should be tested. As one might expect

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A quicky..

February 22, 2010
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If you’re (and you should) interested in principal components then take a good look at this. The linked post will take you by hand to do everything from scratch. If you’re not in the mood then the dollowing R functions will help you. An example. # Generates sample matrix of five discrete clusters that have

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One-way Analysis of Variance (ANOVA)

February 3, 2010
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One-way Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA) is a commonly used statistical technique for investigating data by comparing the means of subsets of the data. The base case is the one-way ANOVA which is an extension of two-sample t test for independent groups covering situations where there are more than two groups being compared. In one-way ANOVA the data

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Create factor variables in R

December 6, 2009
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Create factor variables in R

Instead of the factor() function which usually applies after defining a vector there’s the gl() base function to do this in one step, egfreq <- c(204,6,1,211,13,5,357,44,38,92,34,49) row <- gl(4,3,length=12) col <- gl(3,1,length=12) > col 1 2 3 1 2 3 1 2 3 1 2 3 Levels: 1 2 3 tt <- data.frame(freq,row,col) > xtabs(tt) col row   1   2   3 1 204   6  

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Design of Experiments – Optimal Designs

November 29, 2009
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When designing an experiment it is not always possible to generate a regular, balanced design such as a full or fractional factorial design plan. There are usually restrictions of the total number of experiments that can be undertaken or constraints on the factor settings both individually or in combination with each other. In these scenarios computer

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