Two Factorial Value
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A Comprehensive Guide to Factorial Two-Level Experimentation
Author: Robert Mee
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-06-23
Factorial designs enable researchers to experiment with many factors. The 50 published examples re-analyzed in this guide attest to the prolific use of two-level factorial designs. As a testimony to this universal applicability, the examples come from diverse fields: Analytical Chemistry, Animal Science, Automotive Manufacturing, Ceramics and Coatings, Chromatography, Electroplating, Food Technology, Injection Molding, Marketing, Microarray Processing, Modeling and Neural Networks, Organic Chemistry, Product Testing, Quality Improvement, Semiconductor Manufacturing, and Transportation. Focusing on factorial experimentation with two-level factors makes this book unique, allowing the only comprehensive coverage of two-level design construction and analysis. Furthermore, since two-level factorial experiments are easily analyzed using multiple regression models, this focus on two-level designs makes the material understandable to a wide audience. This book is accessible to non-statisticians having a grasp of least squares estimation for multiple regression and exposure to analysis of variance. "This book contains a wealth of information, including recent results on the design of two-level factorials and various aspects of analysis... The examples are particularly clear and insightful." (William Notz, Ohio State University) "One of the strongest points of this book for an audience of practitioners is the excellent collection of published experiments, some of which didn’t ‘come out’ as expected... A statistically literate non-statistician who deals with experimental design will have plenty of motivation to read this book, and the payback for the effort will be substantial." (Max Morris, Iowa State University)
Statistical Methods
Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results. - Includes extensive case studies and exercises drawn from a variety of disciplines - Provides practice problems for each chapter with complete solutions - Offers new and updated data sets available online - Includes recommended data analysis projects with accompanying data sets
Data Structures in Java
Author: Oswald Campesato
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2023-05-24
This book is a fast-paced introduction to using data structures with Java. Numerous code samples and listings are included to support myriad topics. The first chapter contains a quick introduction to Java, along with Java code samples to check for leap years, find divisors of a number, and work with arrays of strings. The second chapter introduces recursion and uses code samples to check if a positive number is prime, to find the prime divisors of a positive integer, to calculate the GCD (greatest common divisor) and LCM (lowest common multiple) of a pair of positive integers. The third chapter contains Java code samples involving strings and arrays, such as finding binary substrings of a number, checking if strings contain unique characters, counting bits in a range of numbers, and how to compute XOR without using the XOR function. Chapters 4 through 6 include Java code samples involving search algorithms, concepts in linked lists, and tasks involving linked lists. Finally, Chapter 7 discusses data structures called queues and stacks, along with additional Java code samples. Features: Extensive topics, code samples, and scripts related to data structures Covers strings, arrays, queues, and stacks, linked lists, computing the XOR function, checking for unique characters, and more Includes companion files with code samples from the book (available for downloading from the publisher)