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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.
Sampling Error It is the difference between the value of the actual population parameter and the sample statistic. Samples are used to arrive at conclusions regarding the p
Linear Programming
Create the Venn diagram: A - you work for an insurance company. 80% of your company's staff is sales force and 70% of your company's sales is force is male. in your company
QUESTION ONE. (a) The probability that, a bomber hits a target on a bombing mission is 0.70 Three bombers are sent to bomb a particular target. (i) What is the probability
Q. Find relative maxima and minima? When finding relative maxima and minima in the Chapters absolute extrema problem, don't forget to use the first or second derivative test to
A researcher computed the F ratio for a four-group experiment. The computed F is 4.86. The degrees of freedom are 3 for the numerator and 16 for the denominator. 1. Is the computed
Statistical Process Control The variability present in manufacturing process can either be eliminated completely or minimized to the extent possible. Eliminating the variabilit
You are currently working with a supplier who is producing a shaft whose diameter specification is 6.00 ± .003 inches. Currently, the process is yielding shafts wit
The box plot displays the diversity of data for the income; the data ranges from 20 being the minimum value and 1110 being the maximum value. The box plot is positively skewed at 4
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