[Literature] Add notes on Exploratory Data Analysis

literature/literature.bib

@@ -117,6 +117,16 @@
   year = {2016}
 }
 
+@article{SanFish1994,
+  author = {Sanderson, Penelope and Fisher, Carolanne},
+  title = {Exploratory Sequential Data Analysis: Foundations},
+  year = {1994},
+  volume = {9},
+  url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.380.762&rep=rep1&type=pdf},
+  journal = {Human-Computer Interaction},
+  pages = {251–317},
+}
+
 @article{Stemler2001,
   title = {An overview of content analysis},
   author = {Stemler, Steve},

literature/notes

@@ -2665,3 +2665,54 @@ the design. In qualitative research, validation takes the form of triangulation.
 
 "Two fatal flaws that destroy the utility of a content analysis are faulty definitions of
 categories and non-mutually exclusive and exhaustive categories."
+
+================================================
+
+\cite{SanFish1994}
+
+citing Tukey 1977 on Exploratory Data Analysis (EDA):
+"EDA is a simple, visual, but still quantitative approach to data that
+allows an investigator to achieve a richer qualitative understanding by
+"looking at data to see what it seems to say" (Tukey, 1977, p. v)."
+
+"EDA helps
+researchers to generate hypotheses about what might be happening in a
+data set-rather than to test hypotheses, which is confirmatory data analy-
+sis."
+
+3 principles
+
+1) Continual openness and reexpression.
+2) Initial skepticism.
+3) Exploration versus confirmation.
+
+1)
+"Instead of immediately imposing
+a model on the data, which might conceal important details, EDA analysts
+try to find patterns in the data and to describe them with simple summary
+statistics."
+
+"It may take several iterations before the analyst achieves a
+satisfactory summary or "smoothing" of the data. The so-called smooth
+part of a data set is the variability that the analyst has accounted for so far,
+whereas the "rough" part is the vadability that remains unexplained."
+
+2)
+"Because EDA analysts assume that there is no
+uniquely correct numerical summary of a data set, they are very skeptical
+of initial numerical summaries."
+
+"To help detect patterns and search for data points that do
+not fit the smooth part (outliers), EDA analysts rely heavily on visualiza-
+tion."
+
+3)
+"EDA distinguishes exploratory from
+confirmatory data analysis but always maintains a productive interplay
+between them that is complementary rather than antagonistic."
+
+generates hypotheses that can later be tested
+
+--------------------------------
+
+