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--- principal_component_analysis [2019/11/15 09:59] – hkimscil
+++ principal_component_analysis [2019/11/15 22:28] – [e.g. saq] hkimscil
@@ Line 1: / Line 1: @@
 ====== PCA ======
-Difference between PCA and FA
+[[https://www.theanalysisfactor.com/the-fundamental-difference-between-principal-component-analysis-and-factor-analysis/|Difference between PCA and FA]]
   * Both are data reduction techniques — they allow you to capture the variance in variables in a smaller set.
   * Both are usually run in stat software using the same procedure, and the output looks pretty much the same.
@@ Line 160: / Line 160: @@
   ggtitle("eigen on cov(t(data.matrix))")
 </code>
+====== e.g. saq ======
+SPSS Anxiety Questionnaire
+{{:r:saq8.csv}}
+<code>saq <- read.csv("http://commres.net/wiki/_media/r/saq.csv", header = T)
+</code>