A Brill | Sense Bestseller! What if everything you thought you knew about Black people generally, and educating Black children specifically, was based on BS (bad stats)? We often hear things like, “Black boys are a dying breed,” “There are more Black men in prison than college,” “Black children fail because single mothers raise them,” and “Black students don’t read.” In No BS, Ivory A. Toldson uses data analysis, anecdotes, and powerful commentary to dispel common myths and challenge conventional beliefs about educating Black children. With provocative, engaging, and at times humorous prose, Toldson teaches educators, parents, advocates, and students how to avoid BS, raise expectations, and create an educational agenda for Black children that is based on good data, thoughtful analysis, and compassion. No BS helps people understand why Black people need people who believe in Black people enough not to believe every bad thing they hear about Black people.

What if everything you thought you knew about Black people generally, and educating Black children specifically, was based on BS (bad stats)? No BS uses robust analysis, meaningful anecdotes, and powerful commentary to dispel myths and challenge conventional beliefs about educating Black children.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.

BLACK PEOPLE DON'T READ is a comprehensive summary of Data and Statistics from the most recent US Census Bureau, Department of Justice, Department of Education and other agencies around the state Blacks in America.BLACK PEOPLE DON'T READ is a tool to not only refute the plethora of misinformation that exists about Black Identity, but also as a conversation starter around many positive data points, too often missed by the media and seldom discussed at the Barbershop.

This textbook covers the material for an undergraduate linear algebra course: vectors, matrices, linear transformations, computational techniques, geometric constructions, and theoretical foundations. The explanations are given in an informal conversational tone. The book also contains 100+ problems and exercises with answers and solutions. A special feature of this textbook is the prerequisites chapter that covers topics from high school math, which are necessary for learning linear algebra. The presence of this chapter makes the book suitable for beginners and the general audience-readers need not be math experts to read this book. Another unique aspect of the book are the applications chapters (Ch 7, 8, and 9) that discuss applications of linear algebra to engineering, computer science, economics, chemistry, machine learning, and even quantum mechanics.

In Statistics for Social Justice: A Structural Perspective, van de Sande and Byvelds argue that social work research, including statistics, should be taught from a structural perspective and should follow anti-oppressive principles, which view the problems experienced by people as rooted in the social, political and economic structures of society.