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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 data le for this assignment is brain-body-wts.txt, which lists the averages brain weights (gm) and body weights (kg) for a number of animal species. Your task is to t an appr
A manufacturer has received complaints that aging production equipment is forcing workers to work overtime in order to meet production quotas. Historically, the average hours worke
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
"index number is an economic barometer" comment on this statement
i m doing MBA in singapore and i want a good work. i want a data for 200 observations and then answers for some questions. and i need the data to be approved by our professor first
Ten balls are put in 6 slots at random.Then expected total number of balls in the two extreme slots
CERTIFICATE OF AIRWORTHINESS FOR EXPORT When aircraft manufacturers go into series production of a new type of aircraft, then obviously they are hopeful of world wide sales. Sim
prepare a critical analysis of a quantitative study focusing on protection of human participants data collection data management and analysis problem statement and interpretation o
Cause and Effect Even a highly significant correlation does not necessarily mean that a cause and effect relationship exists between the two variables. Thus, correlation does
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
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