This book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation: Topics were determined by what is most useful for practical statistical work, and the presentation is as non-mathematical as possible. The book contains…Continue
Added by Birger S. Madsen on June 8, 2016 at 10:32pm — No Comments
This is a lesson from one of our Data Science for Lawyers Workshops (Moderately Advanced). It is part of our Quantative Analysis in…Continue
Added by Mkhuseli Mthukwane on February 1, 2016 at 11:04am — No Comments
Recently, I came across with an interesting book on the statistics which has a narration of Ugly Duckling story and correlation of this story with today's DATA or rather BIG DATA ANALYTICS world. This story originally from famous storyteller Hans Christian Andersen
Story goes like this...
The duckling was a big ugly grey bird, so ugly that even a dog would not bite him. The poor duckling…
Added by Manish Bhoge on January 31, 2016 at 12:00pm — No Comments
Added by Damian Mingle on October 28, 2015 at 7:01am — No Comments
Business goals are no doubt important, but in an analytic project it makes sense to balance the organization's goals with…Continue
Added by Damian Mingle on October 13, 2015 at 5:59pm — No Comments
Added by Damian Mingle on October 6, 2015 at 3:27am — No Comments
Ulla B. Mogensen, Hemant Ishwaran, Thomas A. Gerds (2012). Evaluating Random Forests for Survival Analysis Using Prediction Error Curves. Journal of Statistical Software, 50(11), 1-23.
Abstract Prediction error curves are increasingly used to assess and compare predictions in survival analysis. This article surveys the R package pec which provides a set of functions for efficient computation of prediction error…
Added by Diego Marinho de Oliveira on April 10, 2015 at 12:21am — No Comments
As data science evolves into a separate and distinct scientific and business discipline, there is talk about the death of traditional statistics. It is true that today's large data sets are unlike the ones we analyzed in graduate statistics classes. It is also true that big data…Continue
The ‘Bell curve’ or the ‘Gaussian bell curve’ is one of the fundamental concepts on which most of the statistical analysis is based. From social sciences to astronomy to financial services- most of the application of statistics in the real world relies on the assumption that the data being analysed is distributed in the shape of the bell curve.
What does the…Continue
Added by Gaurav Vohra on January 3, 2013 at 8:30pm — No Comments
Educating savvy and business-minded Indians on the importance of numbers and analytics in your business is like teaching the properties of sand to someone in the desert, but here is my effort anyway.
The simplest definition of analytics is "the science of analysis." However, a practical definition would be how an entity, e.g., a business, arrives at an optimal or realistic decision based on existing data. Business managers may choose to make decisions based on past experiences or…Continue
Added by AcademyForDecisionScience&Analyt on October 29, 2012 at 7:30pm — No Comments
There is no question that the USA (in fact, most of the world) would be well-served with more quantitatively capable people to work in business and government. However, the current hysteria over the shortage of data scientists is overblown. To illustrate why, I am going to use an example from air travel.
On a recent trip from Santa Fe, NM to Phoenix, AZ, I tracked the various times:
Added by Neil Raden on June 27, 2012 at 10:00am — No Comments