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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 Truly Canadian Restaurant stocks a private red table wine that it purchases from a local winery in the Niagara Falls region. The daily demand for the wine at the restaurant is
In PCA the eigknvalues must ultimately account for all of the variance. There is no probability,'no hypothesis, no test because strictly speaking PCA is not a statistical procedure
Ask question #Minimum The data in the accompanying table give the weights? (in g) of randomly selected quarters that were minted after 1964. The quarters are supposed to have a med
Stratified Sampling Stratified Sampling is generally used when the population is heterogeneous. In this case, the population is first subdivided into several parts (or s
Where do I Access the gss04student_corrected dataset
For the data analysis project, you will address some questions that interest you with the statistical methodology we are learning in class. You choose the questions; you decide h
1. Assume the random vector (Trunk Space, Length, Turning diameter) of Japanese car is normally distributed and the unbiased estimators for its mean and variance are the truth. For
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As one of the oldest multivariate statistical methods of data reduction, Principal Component Analysis (PCA)simplifies a dataset by producing a small number of derived
Caveat We must be careful when interpreting the meaning of association. Although two variables may be associated, this association does not imply that variation in the independ
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