Real Stats offers an engaging and practical introduction to statistical analysis for upper-level undergraduates and first-year graduate students in political science, public policy, and law. Grounded in contemporary understandings of causal inferences, the text invites students to see how econometric tools can help answer important and interesting questions. This emphasis on practical applications, combined with a lively and conversational narrative, provides students with a solid foundation in the analytical tools they will use throughout their academic and professional careers.

Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.

Real Madrid was a broken club. As Cristiano Ronaldo and Zinedine Zidane walked away from the Estadio Santiago Bernabéu, a full-blown identity crisis emerged. In one humiliating week, losses to Barcelona in the Copa del Rey and La Liga, as well as a UEFA Champions League exit at the hands of Ajax, effectively ended Real Madrid's hope of a 2018/19 trophy. From the highs of Zinedine Zidane's first tenure to the lows of the 2018/19 season, discover how Zizou revitalized a broken Real Madrid squad. "Revitalizing Real Madrid - The Tactics and Stats behind Zinedine Zidane's Success" takes an in-depth look at the ideas fueling Real Madrid's 2019/20 La Liga title run. Once a high-scoring team with a leaky defense, Zidane reshaped the team's approach, transforming them into Europe's top defensive side. Through tactical visualizations and contextualized statistics from Scott Martin, a senior analyst for Total Football Analysis, experience the revitalization of world soccer's greatest heavyweight, Real Madrid.

An essential handbook of eye-opening—and frequently myth-busting—facts and figures about the real lives of Black Americans today There’s no defeating white supremacist myths without data—real data. Black Stats is a compact and useful guide that offers up-to-date figures on Black life in the United States today, avoiding jargon and assumptions and providing critical analyses and information. Monique Couvson, author of the acclaimed Pushout, has compiled statistics from a broad spectrum of telling categories that illustrate the quality of life and the possibility of (and barriers to) advancement for a group at the heart of American society. With fascinating information on everything from disease trends, incarceration rates, and lending practices to voting habits, green jobs, and educational achievement, the material in this book will enrich and inform a range of public debates while challenging commonly held yet often misguided perceptions. Black Stats simultaneously highlights measures of incredible progress, conveys the disparate impacts of social policies and practices, and surprises with revelations that span subjects including the entertainment industry, military service, and marriage trends. An essential tool for advocates, educators, and anyone seeking racial justice, Black Stats is an affordable guidebook for anyone seeking to understand the complex state of our nation.

Based on Neil J. Salkind’s bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students uncomfortable with the analysis portion of their work will appreciate the book′s unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques and then walks them through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. New to the Fourth Edition: A new chapter 20 dealing with large data sets using Excel functions and pivot tables, and illustrating how certain databases and other categories of functions and formulas can help make the data in big data sets easier to work with and the results more understandable. New chapter-ending exercises are included and contain a variety of levels of application. Additional TechTalks have been added to help students master Excel 2016. A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world. Basic maths instruction and practice exercises for those who need to brush up on their math skills are included in the appendix.

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.

If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.

The Joy of Stats offers a reader-friendly introduction to applied statistics and quantitative analysis in the social sciences and public policy. Perfect as an undergraduate text or self-study manual, it emphasizes how to understand concepts, interpret algorithms and formulas, analyze data, and answer research questions. This brand new edition offers examples and visualizations using real-life data, a revised discussion of statistical inference, and introductory examples in R and SPSS. The third edition has been extensively reorganized with shorter chapters and closer links between concepts and formulas, while retaining useful pedagogical features including key terms, practice exercises, a math refresher, and playful inserts on "the mathematical imagination." The Joy of Stats also places a strong emphasis on learning how to write and speak clearly about data results. Supported by a companion website with data sets and additional resources, The Joy of Stats is a superb choice for introducing students to applied statistics and for refreshing and reviewing stats as a social scientist, public policy professional, or community activist.

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data