Experimental Design and Analysis
by Howard J. Seltman
Publisher: Carnegie Mellon University 2012
Number of pages: 428
This book is intended as required reading material for the course Experimental Design for the Behavioral and Social Sciences, a second level statistics course for undergraduate students in the College of Humanities and Social Sciences at Carnegie Mellon University.
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by Keijo Ruohonen - Tampere University of Technology
Table of contents: Fundamental sampling distributions and data descriptions; One- and two-sample estimation; Tests of hypotheses; X2-tests; Maximum likelihood estimation; Multiple linear regression; Nonparametric statistics; Stochastic simulation.
by David R. Lilja - University of Minnesota
The book presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models.
by Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.
by Christian Akrong Hesse - ResearchGate GmbH
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. Our goal is to introduce the basic theory without getting too involved in mathematical detail.