Best Probability & Statistics Books
Here you will get Best Probability & Statistics Books For you.This is an up-to-date list of recommended books.
1. Factfulness: Ten Reasons We're Wrong About the World–and Why Things Are Better Than You Think
Author: by Hans Rosling
Published at: Flatiron Books; Reprint edition (April 7, 2020)
INSTANT NEW YORK TIMES BESTSELLEROne of the most important books I’ve ever readan indispensable guide to thinking clearly about the world. Bill GatesHans Rosling tells the story of the secret silent miracle of human progress’ as only he can. But Factfulness does much more than that.
It also explains why progress is so often secret and silent and teaches readers how to see it clearly. Melinda Gates”Factfulness by Hans Rosling, an outstanding international public health expert, is a hopeful book about the potential for human progress when we work off facts rather than our inherent biases.” – Former U.S.
President Barack ObamaFactfulness: The stress-reducing habit of only carrying opinions for which you have strong supporting facts. When asked simple questions about global trendswhat percentage of the world’s population live in poverty; why the world’s population is increasing; how many girls finish schoolwe systematically get the answers wrong.
So wrong that a chimpanzee choosing answers at random will consistently outguess teachers, journalists, Nobel laureates, and investment bankers. In Factfulness, Professor of International Health and global TED phenomenon Hans Rosling, together with his two long-time collaborators, Anna and Ola, offers a radical new explanation of why this happens.
2. AP Statistics Premium: With 9 Practice Tests (Barron's Test Prep)
Author: by Martin Sternstein Ph.D.
Published at: Barrons Educational Series; Eleventh edition (August 4, 2020)
Barron’s AP Statistics has in-depth content review, practice tests, and expert explanations to help students feel prepared on test day. The College Board has announced that there are May 2021 test dates available are May 3-7 and May 10-14, 2021. This edition includes: Five full-length practice tests in the book Three full-length practice tests online One diagnostic test to identify strengths and weaknesses so students can focus their study on areas for improvement Comprehensive subject review for all test topics Tips on how to select an appropriate procedure for the inference question on the exam Suggestions on how to prepare for the challenging Investigative Task on the exam Thirty-seven quizzes to be used as progress checks Fifty Misconceptions Fifty Common Errors students make on the AP exam Fifty AP Exam Hints, Advice, and Reminders A guide to basic uses of TI, Casio, and HP graphing calculators
3. Princeton Review AP Statistics Prep, 2021: 4 Practice Tests + Complete Content Review + Strategies & Techniques (College Test Preparation)
Author: by The Princeton Review
Published at: Princeton Review (August 4, 2020)
EVERYTHING YOU NEED TO SCORE A PERFECT 5now with 2x the practice of previous editions! Ace the AP Statistics Exam with this comprehensive study guide, including 4 full-length practice tests with answer explanations, content reviews for all topics, strategies for every question type, and access to online extras.
Techniques That Actually Work. Tried-and-true strategies to help you avoid traps and beat the test Tips for pacing yourself and guessing logically Essential tactics to help you work smarter, not harderEverything You Need to Know to Help Achieve a High Score.
Comprehensive content review for all test topics Updated to align with the latest College Board standards Engaging activities to help you critically assess your progress Access to study plans, a handy list of formulas and reference information, helpful pre-college advice, and more via your online Student ToolsPractice Your Way to Excellence.
4 full-length practice tests (2 in the book, 2 online) with detailed answer explanations Practice drills at the end of every content review chapter Step-by-step walk-throughs for how to set up box plots, dot plots, and other statistics graphics
4. Causal Inference: The Mixtape
Author: by Scott Cunningham
Published at: Yale University Press (January 26, 2021)
An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences Causation versus correlation has been the basis of argumentseconomic and otherwisesince the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking.
It’s rare that a book prompts readers to expand their outlook; this one did for me. Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studiedfor example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions.
Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.
5. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Author: by Hadley Wickham
Published at: O'Reilly Media; 1st edition (January 17, 2017)
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun.
Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results.
You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
You’ll learn how to:Wrangletransform your datasets into a form convenient for analysisProgramlearn powerful R tools for solving data problems with greater clarity and easeExploreexamine your data, generate hypotheses, and quickly test themModelprovide a low-dimensional summary that captures true “signals” in your datasetCommunicatelearn R Markdown for integrating prose, code, and results.
6. The Visual Display of Quantitative Information
Author: by Tufte
Published at: Graphics Press; 2nd edition (January 1, 2001)
The classic book on statistical graphics, charts, tables. 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.
7. Freakonomics Revised and Expanded Edition: A Rogue Economist Explores the Hidden Side of Everything
Author: by Steven D. Levitt
Published at: William Morrow Paperbacks; Revised, Expanded ed. edition (May 19, 2020)
The legendary bestseller that made millions look at the world in a radically different way returns in a new edition, now including an exclusive discussion between the authors and bestselling professor of psychology Angela Duckworth. Which is more dangerous, a gun or a swimming pool?
Which should be feared more: snakes or french fries? Why do sumo wrestlers cheat? In this groundbreaking book, leading economist Steven LevittProfessor of Economics at the University of Chicago and winner of the American Economic Association’s John Bates Clark medal for the economist under 40 who has made the greatest contribution to the disciplinereveals that the answers.
Joined by acclaimed author and podcast host Stephen J. Dubner, Levitt presents a brilliantand brilliantly entertainingaccount of how incentives of the most hidden sort drive behavior in ways that turn conventional wisdom on its head.
8. An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Author: by Gareth James
Published at: Springer; 1st ed. 2013, Corr. 7th printing 2017 edition (June 25, 2013)
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 modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented.
Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience.
9. Graph Paper Composition Notebook: Grid Paper Notebook, Quad Ruled, 100 Sheets (Large, 8.5 x 11) (Graph Paper Notebooks)
Author: by Joyful Journals
Published at: CreateSpace Independent Publishing Platform (August 2, 2018)
Graph Paper Composition Notebook, Journal, Diary One Subject 100 PagesMakes a wonderful daily graph/grid notebook to draw, write, journal, take notes, make lists, and much more creativity! This is a simple and durable all-purpose daily graph/grid notebook. There is plenty of room inside for drawing, writing notes, journaling, doodling, list making, creative writing, school notes, and capturing ideas.
It can be used as a notebook, journal, diary, or composition book. This paperback notebook is 8.5 x 11 in / 21.59 x 27. 94 cm with a soft, matte cover and has 100 quad ruled pages. Perfect for all ages – kids or adults! Wonderful as a gift, present, or personal notebook!
About this notebook:100 graph ruled pagesGrid ruled on both sides with thin gray linesPerfect for architects, artists, and any drawing activitiesHigh-quality matte cover for a professional finishPerfect size at 8.5 x 11 in / 21.59 x 27. 94 cm – Larger than mostScroll up and click ‘buy’ to grab one today!
10. How to Lie with Statistics
Author: by Darrell Huff
Published at: W. W. Norton & Company; Reissue edition (October 17, 1993)
Over Half a Million Copies Sold-an Honest-to-Goodness Bestseller 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 full rather than to inform.
11. A Mind for Numbers: How to Excel at Math and Science (Even If You Flunked Algebra)
Author: by Barbara Oakley PhD
Published at: TarcherPerigee; Illustrated edition (July 31, 2014)
The companion book to COURSERA’s wildly popular massive open online course “Learning How to Learn”Whether you are a student struggling to fulfill a math or science requirement, or you are embarking on a career change that requires a new skill set, A Mind for Numbers offers the tools you need to get a better grasp of that intimidating material.
Engineering professor Barbara Oakley knows firsthand how it feels to struggle with math. She flunked her way through high school math and science courses, before enlisting in the army immediately after graduation. When she saw how her lack of mathematical and technical savvy severely limited her optionsboth to rise in the military and to explore other careersshe returned to school with a newfound determination to re-tool her brain to master the very subjects that had given her so much trouble throughout her entire life.
In A Mind for Numbers, Dr. Oakley lets us in on the secrets to learning effectivelysecrets that even dedicated and successful students wish they’d known earlier. Contrary to popular belief, math requires creative, as well as analytical, thinking. Most people think that there’s only one way to do a problem, when in actuality, there are often a number of different solutionsyou just need the creativity to see them.
12. Algebra Part 1 (Quickstudy Reference Guides – Academic)
Author: by Inc. BarCharts
Published at: QuickStudy; Chrt edition (November 11, 2002)
For a subject that is a challenge at all levels of education, this chart covers principles for basic algebra, intermediate algebra and college algebra courses.
13. Naked Statistics: Stripping the Dread from the Data
Author: by Charles Wheelan
Published at: W. W. Norton & Company; 1st edition (January 13, 2014)
A New York Times bestseller “Brilliant, funnythe best math teacher you never had.” San Francisco ChronicleOnce 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 real-world application of statistics continues to grow by leaps and bounds.
How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
14. Statistics for People Who (Think They) Hate Statistics
Author: by Neil J. Salkind
Published at: SAGE Publications, Inc; 7th edition (September 10, 2019)
Now in its Seventh Edition, Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics with new co-author Bruce B. Frey teaches an often intimidating subject with a humorous, personable, and informative approach that reduces statistics anxiety. With instruction in SPSS, the authors guide students through basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more.
The Seventh Edition includes new real-world examples, additional coverage on multiple regression and power and effect size, and a robust interactive eBook with video tutorials and animations of key concepts. In the end, students who (think they) hate statistics will understand how to explain the results of many statistical analyses and won’t be intimidated by basic statistical tasks.
15. Statistics For Dummies (For Dummies (Lifestyle))
Author: by Deborah J. Rumsey
For Dummies; 2nd edition (June 7, 2016)
The fun and easy way to get down to business with statistics Stymied by statistics?No fear? This friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life.
Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today’s students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
16. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
Author: by Trevor Hastie
Published at: Springer; 2nd edition (January 1, 2016)
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics.
It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting-the first comprehensive treatment of this topic in any book.
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates.