Indirect Questioning in Sample Surveys

indirectquestioningIndirect Questioning in Sample Surveys written by Arijit Chaudhuri and Tasos C Christofides. Published by Springer 2013

Some topics are extremely important to have information on, but so sensitive and touchy that it is hard to get people to talk about them.

This is a good book to help with gathering information about sensitive characteristics in surveys.

Lots of math proofs to explain the techniques. Such as Item Count Technique and Three Card Method.

Chapter 4.6.2 is about Crossed Model for the case of two stigmatizing characteristics.

Chapter 7 is is on protection of privacy.

This is a good book. I look forward to digging into it and figuring out how to write computer programs for some of the techniques.

Beginning Data Science with R

begindatascience9783319120652

Beginning Data Science with R written by Manas A. Pathak, published by Springer Publishing 2014.
ISBN 978-3-319-12065-2

Code examples at extras.springer.com

This book is written for coders who already know how to code to learn R for data science.

The book covers how to install and use R, but not an IDE like RStudio.

Chapter 2 includes control structures and functions. That functions in R are treated as first class objects. A fundamental property of functional programming languages.

Chapter 3 is on getting data into R. How do get the data into R is a common question. Years ago I was puzzled about getting data into R. I didn’t want to type it all into an array. You don’t have to type in the data, R will read, pull, connect to all sorts of data sources.

Chapter 4 is a nice over view of data visualization.

The book goes on to cover necessary topics and techniques in Data Science. What I want to point out is Chapter 7.3.1 on nearest neighbors uses a package that I haven’t used before kknn. The package is straight forward to use. The author Pathak has written an easy to grasp explanation of the technique.

This is a good book to get you stated coding in R for data science.

R for Cloud Computing

cloud9781493917013

R for Cloud Computing, An Approach for Data Scientists
A Ohri, published by Springer Science Business Media 2014

This is a useful book on how do cloud computing with R. How to set up your accounts and use OAuth to access services.

Chapter 8.1  page 237 shows how to ensure your R code doesn’t contain your login keys.

The book covers the major services available Amazon AWS, Google Cloud and MicroSoft Azure.

AWS needs a credit card even for the free services.

There are nice data visualization services. Google Vis which has an R package googleVis. And Plot.ly  which has an R library that you install with devtools from git hub, package plotly. Direction are on plot.ly site under r/getting started.

Some things change between when a book is published and when you go to use it. Be flexible and search for what is similar and works.

Google code is gone. There is now a package on cran to interface to Google Analytics called RGoogleAnalytics. Information on Google developer site.

In addition to being a good overview of what is out there are interviews that are fun to read and a nice table of my first 25 R commands.