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\title{Psychology 594} % Enter your title between curly braces
\author{Some Later Assignments} % Enter your name between curly braces
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\large
I. (1) problem 10.17 (do in MATLAB)
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(2) Give the partial covariance matrix and the partial
correlation matrix for predicting the 4 variables from 8;
also, give the regression coefficients for predicting 4 from
8.
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II. When you are in SYSTAT and in the discriminant module,
do an example using \verb+iris.syz+, and maybe comment on the nice colors you get.
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Also, use the \verb+classify.m+ file in MATLAB to do the discriminant analysis on the iris data (think as input, \verb+load+ \verb+fisheriris+,
unless you want to do a lot of inputting yourself). Also, comment on what you can get in SYSTAT that doesn't
seem to come with MATLAB when you do a discriminant analysis.
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III. Do a K-means analysis in SYSTAT for the Iris data (3
groups); also, do this in MATLAB for 10 random starts and see
what happens.
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IV. Go get yourself a proximity matrix from Michael Lee's web site
(and one you will want to be interested in for your final
``takehome'')
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Input this into SYSTAT ``by hand'' (e.g., type =
dissimilarity) and do three analyses: a two-dimensional
multidimensional scaling; a complete-link hierarchical cluster
analysis; a Tversky-Corter additive tree representation.
Compare what the three tell you about your data. Are they
``consistent''?
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