Power and Method demonstrates that political activism can and should be infused into the research process. Contesting the traditional assumptions that have dominated thinking about the nature and meaning of research--validity, objectivity and the researcher/"subject" relationship--the volume showcases alternative methods, enabling scholars to make a difference in the lives of classed, gendered and raced "subjects" and grapple honestly and openly with the way power is woven into the research process. Committed to the notion that the challenge to redefine the research process faces not only educational researchers, Power and Method includes contributions from scholars in the allied social sciences and the humanities. Responses from researchers working women's studies, anthropology, sociology and literature conclude each section and highlight common and alternative perspectives on the central themes that run throughout the volume.

The Power Trial Method, Second Edition, a unique, easy-to-read trial skills primer, begins with a simple question about jury trials: Who has the power in the courtroom to decide whether you win or lose? David J.F. Gross and Charles F. Webber, two of the nation's most highly regarded trial lawyers, developed this material to introduce new litigators to the trial process and to reduce the anxiety associated with jury trials by emphasizing key methods of persuasion and presentation.

This revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method, and automatic multilevel substructuring.

This volume, newly published in paperback, is part of a comprehensive effort by R. J. Rummel to understand and place in historical perspective the entire subject of genocide and mass murder, or what he calls democide. It is the fifth in a series of volumes in which he offers a detailed analysis of the 120,000,000 people killed as a result of government action or direct intervention. In Power Kills, Rummel offers a realistic and practical solution to war, democide, and other collective violence. As he states it, "The solution...is to foster democratic freedom and to democratize coercive power and force. That is, mass killing and mass murder carried out by government is a result of indiscriminate, irresponsible Power at the center." Rummel observes that well-established democracies do not make war on and rarely commit lesser violence against each other. The more democratic two nations are, the less likely is war or smaller-scale violence between them. The more democratic a nation is, the less severe its overall foreign violence, the less likely it will have domestic collective violence, and the less its democide. Rummel argues that the evidence supports overwhelmingly the most important fact of our time: democracy is a method of nonviolence.

Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30 years, it was not until recently that the probability density function (pdf) and cumulative distribution function (cdf) were derived and made available. Focusing on both univariate and multivariate nonnormal data ge

This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.

The author presents his personally developed Power Index technique showing impressive profit results in a number of different markets.

Elementary Linear Algebra develops and explains in careful detail the computational techniques and fundamental theoretical results central to a first course in linear algebra. This highly acclaimed text focuses on developing the abstract thinking essential for further mathematical study The authors give early, intensive attention to the skills necessary to make students comfortable with mathematical proofs. The text builds a gradual and smooth transition from computational results to general theory of abstract vector spaces. It also provides flexbile coverage of practical applications, exploring a comprehensive range of topics. Ancillary list:* Maple Algorithmic testing- Maple TA- www.maplesoft.com - Includes a wide variety of applications, technology tips and exercises, organized in chart format for easy reference - More than 310 numbered examples in the text at least one for each new concept or application - Exercise sets ordered by increasing difficulty, many with multiple parts for a total of more than 2135 questions - Provides an early introduction to eigenvalues/eigenvectors - A Student solutions manual, containing fully worked out solutions and instructors manual available

Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings. - Includes tips, warnings and "try this" features within each chapter to help the reader develop good programming practice - Summaries at the end of each chapter allow for quick access to important information - Includes code in Jupyter notebook format that can be directly run online