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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.
A medical researcher has 100 bone cancer patients in a study. Every patient's condition is one of six types, type \A" to type \F". The 100 patients split as follows: x There
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JAR 21 SUPPLEMENTAL TYPE CERTIFICATION JAR 21 Part E introduces the need for Supplemental Type Certification when a manufacturer wishes to make major changes to the Type Desig
Canonical correlation analysis (CC) allows the investigation of the relationship between two ,sets of variables. For example, a sociologist may want to investigate the Relationship
prove that coefficient of correlation lies between -1 and+1
Given a certain population there are various ways in which a sample may be drawn from it. The chart below illustrates this point: Figure 1 In Judgem
A. Compute descriptive statistics for each stock and the S&P 500. Comment on your results. Which stocks are most volatile?
give me question on mean is the aimplest average to understand and easy to compute
Statistical Errors Statistical data are obtained either by measurement or by observation. Hence to think of perfect accuracy is only a delusion or a myth, It is no
Problem 1 Do male and female students differ significantly in regard to their average math achievement scores, grades in high school, and visualization test scores? Can you con
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