Statistics Help @ Talk Stats Forum - Regression Analysis
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Linear regression, linear models, nonlinear regressionenThu, 25 May 2017 06:40:02 GMTvBulletin60http://www.talkstats.com/images/misc/rss.pngStatistics Help @ Talk Stats Forum - Regression Analysis
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Clustering
http://www.talkstats.com/showthread.php/69593-Clustering?goto=newpost
Wed, 24 May 2017 08:25:33 GMTi) T/F:Principal Components Analysis can be used to create a low dimensional projection of the data for use with clustering.
For the above, I read...i) T/F:Principal Components Analysis can be used to create a low dimensional projection of the data for use with clustering.

For the above, I read everywhere different interpretations on this question above, with mixed answers, so really curious with an explanation

ii) T/F: Factor Analysis and Principal Components Analysis have the same objective of modeling the correlation structure in multivariate data.

iii) T/F: Since cluster analysis is an unsupervised learning method, two different cluster partitions cannot be compared.

I *THINK* ii) and iii) are False, but not sure why. Stuck on i) entirely
]]>Regression Analysismaryjkluther23http://www.talkstats.com/showthread.php/69593-ClusteringSAS question
http://www.talkstats.com/showthread.php/69592-SAS-question?goto=newpost
Wed, 24 May 2017 08:20:21 GMT2 questions on SAS, with understanding EFA and PCA:
1) T/F: Common factors estimated using maximum likelihood estimation with a PROMAX rotation...2 questions on SAS, with understanding EFA and PCA:

1) T/F: Common factors estimated using maximum likelihood estimation with a PROMAX rotation are orthogonal.
2) T/F: Common factors estimated using Iterated Principal Factor Analysis with a VARIMAX rotation are orthogonal.
]]>Regression Analysismaryjkluther23http://www.talkstats.com/showthread.php/69592-SAS-questionBootstrapping pairwise not listwise, a problem with N
http://www.talkstats.com/showthread.php/69591-Bootstrapping-pairwise-not-listwise-a-problem-with-N?goto=newpost
Wed, 24 May 2017 04:40:12 GMTHi!
Hoping someone more statistically minded can help.
I have a number of variables with different N (they are performance measures and some...Hi!

Hoping someone more statistically minded can help.

I have a number of variables with different N (they are performance measures and some have been removed due to not understanding the task). I want to bootstrap the correlations but when I do this in SPSS it excludes listwise rather than making use of all the data available (i.e. pairwise). I am wondering if one workaround is to bootstrap each pair of correlations rather than producing the matrix of all variables? My decision on what to include in the regression model would be based on these correlations. So my next but related question is, is different N for the variables a problem for regression?

Many thanks!
]]>Regression Analysiswalrusandpossumhttp://www.talkstats.com/showthread.php/69591-Bootstrapping-pairwise-not-listwise-a-problem-with-N