Philip Withers

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Philip Withers
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  • Hi The factor loadings are calculated as the eigen vectors multiplied by the square root of teh eigenvalues. Hope this helps. Phil
    in PCA Comment by Philip Withers April 2011
  • Hi Albert Alan correctly identified your problem - when using the correlation matrix your data are standardised to a mean of zero and a SD of 1, and these standardised data are then used in the PCA analysis. You can either use Alan's formula for c…
  • The % of Var as output is the % of the variance of the 141 neuron scores that the first PC explains, and the second PC, and the third PC, etc. This does not directly relate to your plot of the casewise scores other than that the casewise scores for…
  • Hello Kerry Your question is a bit tricky! If you are using the Euclidean distance metric for clustering, and you are using a single metric for clustering, then the units for distance would be the square of the units for the metric, and the uni…
  • Hi In statistiXL, the Goodness of Fit module is intended to compare two frequency distributions, an expected one with observed data. The observed data can be a typical frequency distribution i.e. a range of X values and a corresponding range of h…
  • Hello Mauricio Your description of the data you have and the ANOVA analyses sounds fine. There is no problem per se with small sample sizes in doing the ANOVA analyses, but clearly the smaller the sample size the lower is your power in detecting …
  • Hello Paul Re your questions about ANOVA. 1) The probability value refers to the likelihood that there areno differences amongst the various groups of data e.g. a low P value (< 0.05, the scientifically-accepted level of probability) indicates…
  • Hello Dew I think that what you are looking for is a discriminant analysis, to discriminate between running faster and slower than 6 minutes. Use column A as your discriminant factor. You could use all of your variables (columns B to .....) as the…
  • Hello Klaus Regression with repeated X measures is not an option in statistiXL (or other packages that I know of), but the calculations are exactly the same as a regular regression on the data. The difference is that repeat of X measures allows se…
  • Hello James I am glad it seemed to do the trick. To answer your second question first - no, you don't add intereaction terms when you have nested terms - the idea behind nesting is that the nested groups are not the same as groups nested in another…
  • Hello James I think your experiment might be a four factor design - Factor 1 is Region (1 and 2), Factor 2 is Site (1, 2 or 3) nested within Region, Factor 3 is Trap (1, 2 or 3) nested within Site, Factor 4 is Bottle (1 or 2) nested within Trap. Bu…
  • re: query about PCA scores. It is standard for PCA analyses to have the scores output in standardised form (to a mean of 0), for the following reason. For PCA based on the correlation matrix, the raw data columns are standardised for the mean (to…
  • statistiXL provides a procedure for deciding whether it is valid to pool data sets, for contingency table and goodness of fit tests. This procedure is follows Zar (1999), based on the fact that the sum of chi-square values is also a chi-square valu…