Statistics is Easy! 2nd Edition - Dennis Shasha

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Résumé :
Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then system atically presents the standard statistical measures along with programs (in the language Python) to calculate them using resampling, and finally illustrates the use of the measures and programs in a case study. The text uses junior high school algebra and many examples to explain the concepts. Th e ideal reader has mastered at least elementary mathematics, likes to think procedurally, and is comfortable with computers. Table of Contents: The Basic Idea/ Pragmatic Considerations when Using Resampling / Terminology / The Essential Stats / Case Study: New Mexico's 2004 Presidential Ballots / References / Bias Corrected Confidence Intervals / Appendix B

Biographie:
Siddharth Krishna is a post-doctoral researcher at Microsoft Research Cambridge, UK. He completed his Ph.D. in logic and verification at New York University, where he had the good fortune to work with Nisarg, Dennis, and Thomas. He now works on parallel and distributed algorithms for large-scale machine learning workloads. When he is not pleading with computers to do his bidding, he likes to watch comedy panel/news shows and play ultimate frisbee.