Multivariate Data Analysis - Stanford University
Multivariate Data Analysis
Susan Holmes ?
Bio-X and Statistics
IMA Workshop, October, 2013
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you do not really understand something unless you can explain it to your grandmother -- Albert Einstein
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you do not really understand something unless you can explain it to your grandmother -- Albert Einstein I am your grandmother .........
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What are multivariate data ?
Simplest format: matrices:
If we have measured 10,000 genes on hundreds of patients
and all the genes are independent, we can't do better than
analyze each gene's behavior by using histograms or box
plots, looking at the means, medians, variances and other `one
dimensional statistics'. However if some of the genes are
acting together, either that they are positively correlated or
that they inhibit each other, we will miss a lot of important
information by slicing the data up into those column vectors
and studying them separately. Thus important connections
between genes are only available to us if we consider the
data as a whole. We start by giving a few examples of data
that we encounter.
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Athletes, performances in the decathlon.
100 long poid haut 400 110 disq perc jave 15 1 11.25 7.43 15.48 2.27 48.90 15.13 49.28 4.7 61.32 2 10.87 7.45 14.97 1.97 47.71 14.46 44.36 5.1 61.76 3 11.18 7.44 14.20 1.97 48.29 14.81 43.66 5.2 64.16 4 10.62 7.38 15.02 2.03 49.06 14.72 44.80 4.9 64.04 5 11.02 7.43 12.92 1.97 47.44 14.40 41.20 5.2 57.46
Clinical measurements (diabetes data).
relwt glufast glutest steady insulin Group
1 0.81
80
356
124
55
3
3 0.94
105
319
143
105
3
5 1.00
90
323
240
143
3
7 0.91
100
350
221
119
3
9 0.99
97
379
142
98
3
OTU read counts:
469478 208196 378462 265971 570812
EKCM1.489478
0
0
2
0
0
EKCM7.489464
0
0
2
0
2
EKBM2.489466
0
0 . .. ..1.2........ ......0.. ........ . .0. . . .. .. .
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