changed filenames; added categories for politics and writing

README.md

@@ -1,4 +1,6 @@
-# Recipes for data analysis: _An attempt to bring structure to an unstructured activity_
+# Recipes for data analysis
+
+_An attempt to bring structure to an unstructured activity._
 
 According to most sources, data-analysis is a _well-defined_ process in which specialists (data-analysts) *clean, transform, model and question data* for *helping businesses make intelligent decisions*.
 
@@ -9,10 +11,14 @@ The lack of documentation leads to large differences in how data-analysts operat
 This project lists a collection of recipes (*do's and don'ts*) for analysts to make them more effective in their data analysis engagements.
 
 Listed recipes are grouped into the following four categories:
-1. [General](https://github.com/srctaha/recipes-for-data-analysis/blob/master/1-general.md)
-1. [Software](https://github.com/srctaha/recipes-for-data-analysis/blob/master/2-software.md)
-1. [Statistics](https://github.com/srctaha/recipes-for-data-analysis/blob/master/3-statistics.md)
-1. [Social](https://github.com/srctaha/recipes-for-data-analysis/blob/master/4-social.md)
+1. [General](https://github.com/srctaha/recipes-for-data-analysis/blob/master/general.md)
+1. [Software](https://github.com/srctaha/recipes-for-data-analysis/blob/master/software.md)
+1. [Statistics](https://github.com/srctaha/recipes-for-data-analysis/blob/master/statistics.md)
+1. [Social](https://github.com/srctaha/recipes-for-data-analysis/blob/master/social.md)
+1. [Writing](https://github.com/srctaha/recipes-for-data-analysis/blob/master/writing.md)
+1. [Politics](https://github.com/srctaha/recipes-for-data-analysis/blob/master/politics.md)
+
+`TODO:` Link references to recipes.
 
 ---
 

1-general.md → general.md

@@ -54,16 +54,6 @@ Define the deliverables of your work as follows:
 
 TODO: explain the purpose of (3)
 
-### Build a solid writing habit
-Data analysts often face with the challenge of demonstrating their sophistication as a communicator, which requires them to develop advanced writing skills. To achieve effectiveness in writing, book 15~30 min everyday in your calendar and practice.
-
-### Be thoughtful while using jargon and acronyms in your documents
-> AGC issues are highly associated with SR churn.
-
-Although such beginnings might be common in presentations and emails reporting analysis findings, and although _some_ clients might not have much difficulty in decoding such abbreviations, it would be wise to spell out terms on their first occurrence.
-
-Please consider _future yourself_ as one of the current clients as well, and prepare documents accordingly.
-
 ### Aim high while defining your role as an analyst
 Say you work for an insurance company, and the property insurance team wants you to take a look at existing policyholder information and publicly available flood risk data to investigate if there are things that they need to reconsider in their operations.
 
@@ -81,4 +71,11 @@ What value do you think you would generate under those 5 scenarios if we would r
 
 Going from *raw data servicing* to *new product proposals*, your value proposition would increase exponentially. Challenges would definitely increase exponentially too, but do not let those challenges define your role.
 
+### Extra
+>* Remember that time management is the key
+>* Establish a weekly day to screen and process requests
+>* Give presentations, but find a way to spread knowledge more deeply and continuously
+>* Draw your processes and find a way to attach value to every project
+>* Try to stay lean and simple as long as you can
+
 [Return to README](https://github.com/srctaha/recipes-for-data-analysis/blob/master/README.md)

politics.md

@@ -0,0 +1,11 @@
+## Politics
+
+### Summary
+>* Find friendly managers and start working with them
+>* Start producing value as soon as possible
+>* Communicate everything you do to as many people as possible at every level
+>* Be nice, explain everything clearly and help everyone
+>* Avoid jerks, for real
+>* Find a lightning rod absorbing damage in your stead
+
+[Return to README](https://github.com/srctaha/recipes-for-data-analysis/blob/master/README.md)

references.md

@@ -10,5 +10,6 @@
 1. Cheng-Tao Chu, 2014, "Machine Learning Done Wrong", [Blog-post](http://ml.posthaven.com/machine-learning-done-wrong)
 1. Arthur Charpentier, 2015, "Variable Importance with Correlated Features", [Blog-post](https://freakonometrics.hypotheses.org/20545)
 1. Claudia Perlich, "All the Data and Still Not Enough!" at Strata + Hadoop World in New York, 2014, [Video](https://www.oreilly.com/learning/all-the-data-and-still-not-enough)
+1. "The most difficult thing in data science: Politics" [Blog-post](https://www.rdisorder.eu/2017/09/13/most-difficult-thing-data-science-politics/)
 
 [Return to README](https://github.com/srctaha/recipes-for-data-analysis/blob/master/README.md)

writing.md

@@ -0,0 +1,24 @@
+## Writing
+
+### Build a solid writing habit
+Data analysts often face with the challenge of demonstrating their sophistication as a communicator, which requires them to develop advanced writing skills. To achieve effectiveness in writing, book 15~30 min everyday in your calendar and practice.
+
+### Be thoughtful while using jargon and acronyms in your documents
+> AGC issues are highly associated with SR churn.
+
+Although such beginnings might be common in presentations and emails reporting analysis findings, and although _some_ clients might not have much difficulty in decoding such abbreviations, it would be wise to spell out terms on their first occurrence.
+
+Please consider _future yourself_ as one of the current clients as well, and prepare documents accordingly.
+
+### Write in a way that your message is _falsifiable_
+TODO: Explain
+
+### Adverbs are often _unnecessary_. Use them wisely
+> Write with _nouns_ and _verbs_, not with adjectives and adverbs. The adjective hasn't been built that can pull a weak or inaccurate noun out of a tight place. — Strunk and White in "The Elements of Style"
+
+> The adverb is not your friend. — Stephen King in "On Writing"
+
+* Intensifying adverbs such as _very_, _quite_, _incredibly_, and _extremely_ are mostly pointless, as they do not alter the argument.
+* Hedging adverbs such as _almost_, _generally_, _sometimes_, and _usually_ indicate uncertainty.
+
+[Return to README](https://github.com/srctaha/recipes-for-data-analysis/blob/master/README.md)