Vroman's is OPEN for in-store shopping & curbside pick-up seven days a week.
FREE DOMESTIC SHIPPING ON ORDERS OVER $100!

Statistics Is Easy: Case Studies on Real Scientific Datasets (Synthesis Lectures on Mathematics and Statistics) (Paperback)

×

Warning message

Mean Menu style requires jQuery library version 1.7 or higher, but you have opted to provide your own library. Please ensure you have the proper version of jQuery included. (note: this is not an error)
Statistics Is Easy: Case Studies on Real Scientific Datasets (Synthesis Lectures on Mathematics and Statistics) Cover Image
$24.95
Add to Wish List
Usually arrives at our store within 4-7 days

Description


Computational analysis of natural science experiments often confronts noisy data due to natural variability in environment or measurement. Drawing conclusions in the face of such noise entails a statistical analysis.

Parametric statistical methods assume that the data is a sample from a population that can be characterized by a specific distribution (e.g., a normal distribution). When the assumption is true, parametric approaches can lead to high confidence predictions. However, in many cases particular distribution assumptions do not hold. In that case, assuming a distribution may yield false conclusions.

The companion book Statistics is Easy gave a (nearly) equation-free introduction to nonparametric (i.e., no distribution assumption) statistical methods. The present book applies data preparation, machine learning, and nonparametric statistics to three quite different life science datasets. We provide the code as applied to each dataset in both R and Python 3. We also include exercises for self-study or classroom use.

Product Details
ISBN: 9781636390895
ISBN-10: 1636390897
Publisher: Morgan & Claypool
Publication Date: April 8th, 2021
Pages: 74
Language: English
Series: Synthesis Lectures on Mathematics and Statistics