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Henry Kaiser suggested a rule for selecting a number of components m less than the number needed for perfect reconstruction: set m equal to the number of eigenvalues greater than I. This rule is often used in common factor analysis as well as in PCA. Several lines of thought lead to Kaiser's rule, but the simplest is that since an eigenvalue is the amount of variance explained by one more component, it doesn't make sense to add a component that explains less variance than is contained in one variable. Since a component analysis is supposed to summarize a set of data, to use a component that explains less than a variance of I is something like writing a summary'of a book in which one section of the summary is longer than the book sectio~it summarizes--which makes no sense. However, Kaiser's ma-jor justification for th5 rule was that it matched pretty well the ultimate rule of doing several component analyses with diff-nt- numbers of komponents, and seeing which analysis made sense. That ultimate rule is much easier today than it was a generation ago, so Kaiser's rule seems obsolete.
Statistician is searching the \home ground" effect and is studying 20 football games, of which 14 were won by the home team and 6 by the visitors. Therefore the game is a Bernoulli
give me question on mean is the aimplest average to understand and easy to compute
Dr. Jim Mirabella UNIT EIGHT: DATA ANALYSIS PROJECT All Excel output should be copied into a single Word document where you must enter all of your responses to the questions below.
Choose any published database from the internet or Bethel library (such as those from the Census Bureau or any financial sites). You may opt to use one of the data files provided b
how to determine GRR?
Use the given information to find the P-value. The test statistic in a two-tailed test is z = 1.49 P-value = (round to four decimal places as needed)
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i am new to stata and i am trying to figure out how to calculate expected growth of sales tax revenue as well as average growth rate of sales tax revenue in stata. I have a dataset
The PCA is amongst the oldest of the multivariate statistical methods of data reduction. It is a technique for simplifying a dataset, by reducing multidimensional datasets to lower
1 Se toma una muestra de 81 observaciones con una desviación estándar de 5. La media de la muestra es de 40. Determine el intervalo de de confianza de 99% para la media
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