. ." and "The data bear this out. . . ." But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data. Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you canDetermine the odds Calculate a standard score Find the margin of error Recognize the impact of polls Establish criteria for a good survey Make informed decisions about experiments This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, and study guides in the following ways:Practical and intuitive explanations of statistical concepts, ideas, techniques, formulas, and calculations. Clear and concise step-by-step procedures that intuitively explain how to work through statistics problems. Upfront and honest answers to your questions like, "What does this really mean?" and "When and how I will ever use this?" Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.

    This text is highly regarded because of its engaging and understandable introduction to statistics. The author's commitment to providing student-friendly guidance through the material and giving students opportunities to apply their newly learned skills in a real-world context has made Elementary Statistics the #1 best-seller in the market.

    

    But when was young, he was so small that his friends called him Little Leo and coaches worried he wasn't big enough. Yet through bravery, talent and hard work, he proved them wrong. Messi tells the magical story of how the tiniest boy in South America grew up to become the greatest player on earth.Ultimate Football Heroes is a series of biographies telling the life-stories of the biggest and best footballers in the world and their incredible journeys from childhood fan to super-star professional player. Written in fast-paced, action-packed style these books are perfect for all the family to collect and share.

    To reach this unique audience, Whitlock and Schluter motivate learning with interesting biological and medical examples; they emphasize intuitive understanding; and they focus on real data. The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments. It also introduces the principles behind such modern topics as likelihood, linear models, meta-analysis and computer-intensive methods. Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and its variety of fascinating and relevant biological examples.

    By the mid-1990s the old school grizzled traders had been replaced by a new breed of quantitative analysts, applying mathematics to the "art" of trading and making of it a science. A similar phenomenon is happening in poker. The grizzled "road gamblers" are being replaced by a new generation of players who have challenged many of the assumptions that underlie traditional approaches to the game. One of the most important features of this new approach is a reliance on quantitative analysis and the application of mathematics to the game. This book provides an introduction to quantitative techniques as applied to poker and to a branch of mathematics that is particularly applicable to poker, game theory, in a manner that makes seemingly difficult topics accessible to players without a strong mathematical background.

    It is impossible to understand the spread of an epidemic, a computer virus, large-scale blackouts, or massive extinctions without taking into account the network structure that underlies all these phenomena. In this Very Short Introduction, Guido Caldarelli and Michele Catanzaro discuss the nature and variety of networks, using everyday examples from society, technology, nature, and history to explain and understand the science of network theory. They show the ubiquitous role of networks; how networks self-organize; why the rich get richer; and how networks can spontaneously collapse. They conclude by highlighting how the findings of complex network theory have very wide and important applications in genetics, ecology, communications, economics, and sociology.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

    "Devdas: " The young boy Devdas has an ardent follower, a little girl Parvati, who is his neighbor's daughter. They grow up together in a class conscious, tradition bound, rural community. Their friendship turns into love as they mature. Will they be able to have their wish fulfilled and unite with each other for the rest of their lives? Which way their fate will take them?"Good Riddance (Niskriti): " Girish is a successful man and both he and his wife are magnanimous. They allow Girish's incompetent and poor cousin and his family to live with them as a joint family. An atmosphere of great love and understanding prevails over the joint family. But, what happens when Girish's younger brother Harish, who is also a successful man and has a wife with western education, joins the family? What events take place and what are the roles played by different family members?"Pundit (Pundit-moshai): " Brindabon was married at a young age, but was soon made by his father to desert his child bride, because of a rumor of scandal about her mother. He grows up to become a self educated and benevolent well to do man, and she grows up to be a beautiful and educated woman in a poor family. After his second wife dies leaving behind a young son, he offers to take her back. But, how she responds? Brindabon gives free education to children of the poor in the village, by teaching them himself, and is called by them as Pundit. But, does that earn him respect from the diehard snobs in the village ortheir compassion in his moment of crisis?"Chandranath: " A rich man marries a poor young woman, not knowing that her mother had a scandal of living together with a man after she became a widow. The girl, because of her humble background and the scandalous secret about her mother, considers herself much inferior to her husband and treats him with servility. How are the husband's feelings towards her? How the marriage blossoms? A kindly old man comes in their life, and what role he plays?"Debt and Payment (Dena-Paona): " Jibananda, a corrupt scion of a landlord family, marries the child daughter of a widow for dowry money and then disappears. He later inherits a large estate when his uncle dies and becomes an oppressive feudal landlord. The girl by turn of events becomes the custodian of a temple in a village, where the landlord owns some property. She is upright, educated, and a leader of the downtrodden. The landlord visits the village, but does not recognize her. The virtuous woman and the depraved man cross their path, and what does it bring to them?

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Stuck inside a small flat with sole responsibility for his two single-digit children, Tom is plunged into a world of home schooling, supermarket feuds and alfresco workout sessions, not to mention keeping tabs on ageing parents who won’t stay home.Faced with the problems of cash-strapped tooth fairies, buying a rat trap online and an NHS-supporting arms race with an elderly neighbour, Tom realises he must rise to the occasion, but when his girlfriend asks for an erotic photo of his rapidly deteriorating body, it may be one step too far...Join Tom as he navigates lockdown in this hilarious stand-alone novel from the author of The Rebuilding of Tom Cooper.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    

    Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.