Starting making notes on 'intro to datascience' course.

intro-to-data-science.md

+# Missing data
+
+approaches:
+
+- partial deletion
+- imputation
+
+## Partial deletion
+
+- **listwise deletion**: *entire record* is excluded from analysis if any single value is missing
+- **pairwise deletion**: *only specific missing values* excluded
+
+## Imputation
+
+**imputation**
+
+- = making an educated guess at missing data
+- = approximating missing values
+- different techniques; hard to get right
+
+## Imputation using linear regression
+
+= create an equation for finding missing values using available data
+
+disadvantages:
+
+- overemphasizes existing trends
+- will produce exact values for the missing entries, which would suggest a greater certainty in the missing values than we actually have

python.md

+- http://hyperpolyglot.org/scripting
+- http://www.marinamele.com/install-and-configure-atom-editor-for-python