This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

     In this book you’ll find: • 9 steps to build a portfolio that will survive the Perfect Financial Storm, so you can stop worrying about the economy, the latest financial catastrophe, or what the market did today • 2 questions you must answer before you invest another dime • Why investing after you retire is radically different from investing while you’re still working • The life expectancy of 6 key types of investments—and what you can do to make them last as long as you do • The 10 essential questions you must ask a financial advisor—before you hire one • The exact amount of money you can withdraw without worry or guilt, knowing you’ve applied the best available research to ensure you’ll never run out of money “Thurman takes a subject that is often misunderstood, and provides you the reasons, the methods, and an understanding of what you can expect to achieve, so you can invest with confidence.” –Jimmy J. Williams, CFP®, CPA/PFS CEO/President of Compass Capital Management, LLC “A must for anyone thinking of retiring or recently retired!” –Stan Toler, bestselling author of The Secret Blend

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    What began more than sixty years ago as a modest proposal that a mathematician and an economist write a short paper together blossomed, in 1944, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences.This sixtieth anniversary edition includes not only the original text but also an introduction by Harold Kuhn, an afterword by Ariel Rubinstein, and reviews and articles on the book that appeared at the time of its original publication in the New York Times, tthe American Economic Review, and a variety of other publications. Together, these writings provide readers a matchless opportunity to more fully appreciate a work whose influence will yet resound for generations to come.

    The complexity of nature's shapes differs in kind, not merely degree, from that of the shapes of ordinary geometry, the geometry of fractal shapes.Now that the field has expanded greatly with many active researchers, Mandelbrot presents the definitive overview of the origins of his ideas and their new applications. The Fractal Geometry of Nature is based on his highly acclaimed earlier work, but has much broader and deeper coverage and more extensive illustrations.

    Erin recounts her path of achievement starting as a promising young student and athlete and, ultimately, how she allowed her career and its demands to become the center of her life. She sacrificed all other priorities and relationships along the way, throwing work-life balance to the wind. The story reveals the subtleties of the everyday decisions that led collectively to a work-centric existence over a twenty-year career. Set against the backdrop of the dramatic circumstances at Lehman Brothers in 2008, Erin discloses her own struggle as events spiraled out of control. Ultimately, her resignation from her executive role prior to the Lehman bankruptcy resulted in a devastating personal crisis as her career crumbled revealing no foundation beneath it. We learn of the journey back to change her life with a semblance of present day peace and happiness. Full Circle provides a unique inside and emotional perspective of the sacrifices Erin made to achieve extreme career success and the self-awareness required to return to being the fundamentally grounded person she was as a child.

    Google Hacking teaches people how to get the most out of this revolutionary search engine. Not only will this book teach readers how Google works, but it will also empower them with the necessary skills to make their everyday searches easier, more efficient, and more productive. Google Hacking also demonstrates how Google can be used for negative means. It's immense searching power, means that everyone, including cyber criminals, can feasibly access confidential data, such as company presentations, budgets, blueprints, even credit card numbers, with just the click of a mouse. Using numerous examples, case studies, and screenshots, this book explains the art of ethical Google Hacking -- it not only teaches readers how Google works, but it provides them with the knowledge they need to protect their data and systems from getting Google Hacked. This is the only book you need to maximize (and protect yourself) from Google searches!

    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    Goodman & Robert A. Spicer from an original story by George S. Clason ; illustrated by Joseph Feher.-WorldCat

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    When John Hargrave first invested in cryptocurrency, the price of a single bitcoin was about $125; a few years later, that same bitcoin was worth $20,000. He wasn’t alone: this flood of new money is like the early days of the Internet, creating a new breed of “blockchain billionaires.” Sir John has unlocked their secrets. In Blockchain for Everyone, Sir John reveals the formula for investing in bitcoin and blockchain, using real-life stories, easy-to-understand examples, and a healthy helping of humor. Packed with illustrations, Blockchain for Everyone explains how (and when) to buy bitcoin, cryptocurrencies, and other blockchain assets, with step-by-step instructions. Blockchain for Everyone is the first blockchain investing book written for the layperson: a guide that helps everyone understand how to build wealth wisely. It’s the new investing manifesto!

    In addition to general advice on basic numeracy, the guide points out common errors and explains the recognized techniques for solving financial problems, analysing information of any kind, and effective decision making. Over one hundred charts, graphs, tables, and feature boxes highlight key points. Also included is an A-Z dictionary of terms covering everything from amortization to zero-sum game. Whatever your business, The Economist Numbers Guide will prove invaluable.