All of Statistics

All of Statistics
Author: Larry Wasserman
Publsiher: Springer Science & Business Media
Total Pages: 442
Release: 2013-12-11
ISBN 10: 0387217363
ISBN 13: 9780387217369
Language: EN, FR, DE, ES & NL

All of Statistics Book Review:

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 students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

All of Statistics

All of Statistics
Author: Larry Wasserman,Larry Alan Wasserman
Publsiher: Springer Science & Business Media
Total Pages: 442
Release: 2004-09-17
ISBN 10: 9780387402727
ISBN 13: 0387402721
Language: EN, FR, DE, ES & NL

All of Statistics Book Review:

This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate level. Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.

All of Statistics

All of Statistics
Author: Larry Wasserman
Publsiher: Unknown
Total Pages: 468
Release: 2014-09-01
ISBN 10: 9781468495522
ISBN 13: 1468495526
Language: EN, FR, DE, ES & NL

All of Statistics Book Review:

All of Statistics

All of Statistics
Author: Larry Wasserman
Publsiher: Springer
Total Pages: 442
Release: 2010-12-01
ISBN 10: 9781441923226
ISBN 13: 1441923225
Language: EN, FR, DE, ES & NL

All of Statistics Book Review:

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 students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con ducted in statistics departments while data mining and machine learning re search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo rithms are more scalable than statisticians ever thought possible. Formal sta tistical theory is more pervasive than computer scientists had realized.

All of Nonparametric Statistics

All of Nonparametric Statistics
Author: Larry Wasserman
Publsiher: Springer Science & Business Media
Total Pages: 270
Release: 2006-09-10
ISBN 10: 0387306234
ISBN 13: 9780387306230
Language: EN, FR, DE, ES & NL

All of Nonparametric Statistics Book Review:

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.

How to Tell the Truth with Statistics

How to Tell the Truth with Statistics
Author: David Spiegelhalter
Publsiher: Penguin UK
Total Pages: 256
Release: 2019-03-28
ISBN 10: 0241258758
ISBN 13: 9780241258750
Language: EN, FR, DE, ES & NL

How to Tell the Truth with Statistics Book Review:

Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way statistical claims can be sensationalised, particularly in the media. In the age of big data, as data science becomes established as a discipline, a basic grasp of statistical literacy is more important than ever. In How to Tell the Truth with Statistics, David Spiegelhalter guides the reader through the essential principles we need in order to derive knowledge from data. Drawing on real world problems to introduce conceptual issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether serial killer Harold Shipman could have been caught earlier, and if screening for ovarian cancer is beneficial. How many trees are there on the planet? Do busier hospitals have higher survival rates? Why do old men have big ears? Spiegelhalter reveals the answers to these and many other questions - questions that can only be addressed using statistical science.

The Humongous Book of Statistics Problems

The Humongous Book of Statistics Problems
Author: Robert Donnelly,W. Michael Kelley
Publsiher: Penguin
Total Pages: 560
Release: 2009-12-01
ISBN 10: 1101151390
ISBN 13: 9781101151396
Language: EN, FR, DE, ES & NL

The Humongous Book of Statistics Problems Book Review:

Following the successful, 'The Humongous Books', in calculus and algebra, bestselling author Mike Kelley takes a typical statistics workbook, full of solved problems, and writes notes in the margins, adding missing steps and simplifying concepts and solutions. By learning how to interpret and solve problems as they are presented in statistics courses, students prepare to solve those difficult problems that were never discussed in class but are always on exams. - With annotated notes and explanations of missing steps throughout, like no other statistics workbook on the market - An award-winning former math teacher whose website (calculus-help.com) reaches thousands every month, providing exposure for all his books

Introductory Statistics

Introductory Statistics
Author: Barbara Illowsky,Susan Dean
Publsiher: Unknown
Total Pages: 906
Release: 2017-12-19
ISBN 10: 9789888407309
ISBN 13: 9888407309
Language: EN, FR, DE, ES & NL

Introductory Statistics Book Review:

Introductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them. Coverage and Scope Chapter 1 Sampling and Data Chapter 2 Descriptive Statistics Chapter 3 Probability Topics Chapter 4 Discrete Random Variables Chapter 5 Continuous Random Variables Chapter 6 The Normal Distribution Chapter 7 The Central Limit Theorem Chapter 8 Confidence Intervals Chapter 9 Hypothesis Testing with One Sample Chapter 10 Hypothesis Testing with Two Samples Chapter 11 The Chi-Square Distribution Chapter 12 Linear Regression and Correlation Chapter 13 F Distribution and One-Way ANOVA

An Introduction to Statistical Learning

An Introduction to Statistical Learning
Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publsiher: Springer Science & Business Media
Total Pages: 426
Release: 2013-06-24
ISBN 10: 1461471389
ISBN 13: 9781461471387
Language: EN, FR, DE, ES & NL

An Introduction to Statistical Learning Book Review:

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. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

How to Lie with Statistics

How to Lie with Statistics
Author: Darrell Huff
Publsiher: W. W. Norton & Company
Total Pages: 144
Release: 2010-12-07
ISBN 10: 0393070875
ISBN 13: 9780393070873
Language: EN, FR, DE, ES & NL

How to Lie with Statistics Book Review:

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.

OpenIntro Statistics

OpenIntro Statistics
Author: David Diez,Christopher Barr,Mine Çetinkaya-Rundel
Publsiher: Unknown
Total Pages: 135
Release: 2015-07-02
ISBN 10: 9781943450046
ISBN 13: 1943450048
Language: EN, FR, DE, ES & NL

OpenIntro Statistics Book Review:

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. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Theory of Statistics

Theory of Statistics
Author: Mark J. Schervish
Publsiher: Springer Science & Business Media
Total Pages: 716
Release: 2012-12-06
ISBN 10: 1461242509
ISBN 13: 9781461242505
Language: EN, FR, DE, ES & NL

Theory of Statistics Book Review:

The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.

The Concise Encyclopedia of Statistics

The Concise Encyclopedia of Statistics
Author: Yadolah Dodge
Publsiher: Springer Science & Business Media
Total Pages: 622
Release: 2008-04-15
ISBN 10: 0387317422
ISBN 13: 9780387317427
Language: EN, FR, DE, ES & NL

The Concise Encyclopedia of Statistics Book Review:

The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics. The reference is alphabetically arranged to provide quick access to the fundamental tools of statistical methodology and biographies of famous statisticians. The more than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions. This reference will be an enduring resource for locating convenient overviews about this essential field of study.

Introduction to Probability

Introduction to Probability
Author: Joseph K. Blitzstein,Jessica Hwang
Publsiher: CRC Press
Total Pages: 596
Release: 2014-07-24
ISBN 10: 1498759769
ISBN 13: 9781498759762
Language: EN, FR, DE, ES & NL

Introduction to Probability Book Review:

Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional

Statistical Inference

Statistical Inference
Author: George Casella,Roger L. Berger
Publsiher: Cengage Learning
Total Pages: 688
Release: 2021-01-26
ISBN 10: 0357753135
ISBN 13: 9780357753132
Language: EN, FR, DE, ES & NL

Statistical Inference Book Review:

This book builds theoretical statistics from the first principles of probability theory. 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. Intended for first-year graduate students, this book can be used for students majoring in statistics 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. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Introduction to Statistics

Introduction to Statistics
Author: Wolfgang Karl Härdle,Sigbert Klinke,Bernd Rönz
Publsiher: Springer
Total Pages: 516
Release: 2015-12-25
ISBN 10: 3319177044
ISBN 13: 9783319177045
Language: EN, FR, DE, ES & NL

Introduction to Statistics Book Review:

This book covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students’ knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and the practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc.

The Book of R

The Book of R
Author: Tilman M. Davies
Publsiher: No Starch Press
Total Pages: 832
Release: 2016-07-16
ISBN 10: 1593277792
ISBN 13: 9781593277796
Language: EN, FR, DE, ES & NL

The Book of R Book Review:

The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

The Basic Practice of Statistics

The Basic Practice of Statistics
Author: David S. Moore
Publsiher: Palgrave Macmillan
Total Pages: 730
Release: 2010
ISBN 10: 1429224266
ISBN 13: 9781429224260
Language: EN, FR, DE, ES & NL

The Basic Practice of Statistics Book Review:

The Basic Practice of Statistics has become a bestselling textbook by focusing on how statistics are gathered, analyzed, and applied to real problems and situations—and by confronting student anxieties about the course's relevance and difficulties head on. With David Moore's pioneering "data analysis" approach (emphasizing statistical thinking over computation), engaging narrative and case studies, current problems and exercises, and an accessible level of mathematics, there is no more effective textbook for showing students what working statisticians do and what accurate interpretations of data can reveal about the world we live in. In the new edition, you will once again see how everything fits together. As always, Moore's text offers balanced content, beginning with data analysis, then covering probability and inference in the context of statistics as a whole. It provides a wealth of opportunities for students to work with data from a wide range of disciplines and real-world settings, emphasizing the big ideas of statistics in the context of learning specific skills used by professional statisticians. Thoroughly updated throughout, the new edition offers new content, features, cases, data sources, and exercises, plus new media support for instructors and students—including the latest version of the widely-adopted StatsPortal. The full picture of the contemporary practice of statistics has never been so captivatingly presented to an uninitiated audience.

Asymptotic Theory of Statistics and Probability

Asymptotic Theory of Statistics and Probability
Author: Anirban DasGupta
Publsiher: Springer Science & Business Media
Total Pages: 722
Release: 2008-03-07
ISBN 10: 0387759700
ISBN 13: 9780387759708
Language: EN, FR, DE, ES & NL

Asymptotic Theory of Statistics and Probability Book Review:

This unique book delivers an encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. The book is unique in its detailed coverage of fundamental topics. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. There is no other book in large sample theory that matches this book in coverage, exercises and examples, bibliography, and lucid conceptual discussion of issues and theorems.

Learning Spark

Learning Spark
Author: Jules S. Damji,Brooke Wenig,Tathagata Das,Denny Lee
Publsiher: O'Reilly Media
Total Pages: 400
Release: 2020-07-16
ISBN 10: 1492050016
ISBN 13: 9781492050018
Language: EN, FR, DE, ES & NL

Learning Spark Book Review:

Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow