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Discriminant analysis (DA) helps to determine which variables discriminate between two or more naturally occurring groups. Mathematically equivalent to MANOVA, it ' is extensively used when a set of explanatory variables are used to predict the group to which a given unit belongs (which is a nominal dependent variables). It cornhines the explanatory variables in order to create the largest F when the groups are used as a fixed factor in an ANOVA.
The model is constructed with a set of observations for which the classes are known. The set of observations are sometimes referred to as the training set.
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
Grouped data For grouped data, the formula applied is σ = Where f = frequency of the variable, μ= population mea
how detect sources of error in sample survey
Statistical Process Control The variability present in manufacturing process can either be eliminated completely or minimized to the extent possible. Eliminating the variabilit
We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that
a b c d e supply p 3 4 6 8 8 20 q 2 6 0 5 8 30 r 7 11 20 40 3 15 s 1 0 9 14 6 13 d 15 3 12 10 20
Problem : A company supplying electrical products, places a rush order for electric wires. Consignments of wires are to be sent immediately when they are available. Previous
The following table shows the results of fitting a linear regression model of starting annual salaries on a constant, GPA (4 point scale), and a variable (Metrics =1) indicating wh
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These techniques are applied when the rows and the columns of the data table represent the same units and when the measure is a disiance or a similarity. The goal of the analysis i
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