Statistics

Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to fool rather than to inform....

The Freakonomics of math?a mathworld superstar unveils the hidden beauty and logic of the world and puts its power in our handsThe math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn?t confined t...

To really learn data science, you should not only master the toolsdata science libraries, frameworks, modules, and toolkitsbut also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.If you h...

Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called ?sexy.? From batting averages and political polls to game shows and medical research, the realworld application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on...

Dozens of examples in innumeracy show us how it affects not only personal economics and travel plans, but explains mischosen mates, inappropriate drugtesting, and the allure of pseudoscience....

The thirtyfive chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important social, medical, and political situations as well. Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, ...

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problemsolving with real data across a wide variety of applications will aid practitioners who wish to extend their ...

Discover how empirical researchers today actually think about and apply econometric methods with the practical, professional approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Unlike traditional books on the subject, INTRODUCTORY ECONOMETRICS' unique presentation demonstrates how econometrics has moved beyond just a set of a...

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and Technology, environment, and the learning is supported and...

“Available recommendation signals cluster around MathScience lists, suggesting this book may fit readers looking for reader-fit discovery across adjacent interests. Treat this as discovery context, not a quality guarantee.”

Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thoughtprovoki...

This book is a little gem; it treats in an authoritative and charming manner a number of physiological and morphological adaptations which animals evolved in coping with certain environmental exigencies....I recommend (this book) to fellow biologists of all ages as one of the better buys of its kind....

Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. ...

Make sure you're studying with the most uptodate prep materials! Look for the newest edition of this title, Princeton Review AP Statistics Prep, 2021 (ISBN: 9780525569657, onsale August 2020).Publisher's Note: Products purchased from thirdparty sellers are not guaranteed by the publisher for quality or authenticity, and may not include access t...

Nursing Research & Statistics...

This book introduces the field of data science in a practical and accessible manner, using a handson approach that assumes no prior knowledge of the subject. The foundational ideas and techniques of data science are provided independently from Technology,, allowing students to easily develop a firm understanding of the subject without a strong tech...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modelin...

1986 BILL JAMES SOFTCOVER...

Barron?s AP Statistics has indepth content review, practice tests, and expert explanations to help students feel prepared on test day. This edition includes: Five fulllength practice tests in the bookThree fulllength practice tests onlineOne diagnostic test helps identify strengths and weaknesses so students can focus their study on areas for im...

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. '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...

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first studentfocused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, studentfriendly language to provi...

BOOKS...

Major changes in this edition include the substitution of probabilistic arguments for combinatorial artifices, and the addition of new sections on branching processes, Markov chains, and the De MoivreLaplace theorem....

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R. Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same groundbreaking structure and pedagogical approach. The core material is enhanced by...

This book presents empirical methods for studying complex computer programs: exploratory tools to help find patterns in data, experiment designs and hypothesistesting tools to help data speak convincingly, and modeling tools to help explain data.Computer science and Artificial Intelligence, in particular have no curriculum in research methods, as o...

The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic Programming,, and edgebased flow.Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor an...

Coauthored by four leading scientists from academia and industry, Numerical Recipes Third Edition starts with basic mathematics and computer science and proceeds to complete, working routines. Widely recognized as the most comprehensive, accessible and practical basis for scientific computing, this new edition incorporates more than 400 Numerical ...

Since its publication by Academic Press, tens of thousands of students have taken a probability course using this classic textbook. Chung's A Course in Probability Theory, now in its third edition, has sustained its popularity for nearly 35 years. Originally developed from Dr. Chung's course at Stanford University, this book continues to be a succe...

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate stu...

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied...

Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. A...

An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields. The 2nd edition is a substantial revision of the 1st edition, involving a reorganization of old material and the addition of new material. The length of the book has increased by a...

Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu?themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrat...

Master Bayesian Inference through Practical Examples and ComputationWithout Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a stron...

Remarkable selection of puzzlers, graded in difficulty, that illustrate both elementary and advanced aspects of probability. Selected for originality, general interest, or because they demonstrate valuable techniques, the problems are ideal as a supplement to courses in probability or statistics, or as stimulating recreation for the mathematically ...

Tales of rainmaking, horseracing, and soulsaving boisterously fill these pages, along with the edifying histories of such worthy entities as the U.S. Weather Control Bureau, the Great American Hog Syndicate, and the MidContinental Chinchilla Rabbitry....

The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differencesindifferences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes...

The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. Our inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible. Files for the entire book are f...

ANALYTICS INTRODUCTION TO DATA SCIENCE is the ideal introductory DATA SCIENCE textbook for a wide variety of first year Degree/Diploma students that are looking for a very easy to understand book that has the following features:1. ESSENTIAL THEORY2. SOLVED PROBLEMS3. SUPPLEMENTARY QUESTIONS4. TRIAL EXAMS...

Written by international awardwinning probability expert Henk Tijms, Basic Probability: What Every Math Student Should Know presents the essentials of elementary probability. The book is primarily written for high school and college students learning about probability for the first time. In a highly accessible way, a modern treatment of the subjec...

This textbook will be ideal for any college or university student studying Business Analytics/Data Science/Statistics at first year degree or diploma level. The book contains the following features are: Essential Theory, Solved Problems, Supplementary Questions, Trial Exam Questions and Exam Revision....

While there are books focusing on parametric tests, the domain of nonparametric tests is mostly unexplored. Data Analysis in Business Research: A Step by Step Nonparametric Approach brings under one umbrella all the major nonparametric statistical tools that can be used by undergraduate and postgraduate students of all disciplines, especially stude...

How do we create new ways of looking at the world Join awardwinning data storyteller RJ Andrews as he pushes beyond the usual howto, and takes you on an adventure into the rich art of informing.Creating Info We Trust is a craft that puts the world into forms that are strong and true. It begins with maps, diagrams, and charts but must push fur...

A Cookbook that will help you implement Machine Learning algorithms and techniques bybuilding realworld projects Key FeaturesLearn how to handle an entire Machine Learning Pipeline supported with adequate mathematics. Create Predictive Models and choose the right model for various types of Datasets. Learn the art of tuning a model to improve accur...