Statistical Inference Via Data Science A Moderndive Into R And The Tidyverse

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Chester Ismay,Albert Y. Kim
Statistical Inference via Data Science A ModernDive into R and the Tidyverse Book PDF

Author : Chester Ismay,Albert Y. Kim
Publisher : CRC Press
Page : 430 pages
File Size : 51,8 Mb
Release : 2019-12-23
Category : Mathematics
ISBN : 9781000763461

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse by Chester Ismay,Albert Y. Kim Pdf

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.

Introduction to Mechanical Engineering

Michael Clifford
Introduction to Mechanical Engineering Book PDF

Author : Michael Clifford
Publisher : CRC Press
Page : 0 pages
File Size : 40,5 Mb
Release : 2022-12-27
Category : Science
ISBN : 100076351X

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Introduction to Mechanical Engineering by Michael Clifford Pdf

Updated throughout for the second edition, Introduction to Mechanical Engineering: Part 1 continues to be the essential text for all first-year undergraduate students, alongside those studying for foundation degrees and HNDs. Written by an experienced team of lecturers at the internationally renowned University of Nottingham, this book provides a comprehensive grounding in the following core engineering topics: thermodynamics, fluid mechanics, solid mechanics, dynamics, electrical and electronic systems and material science. It includes questions and answers for instructors and for self-guided learning. As well as mechanical engineers, this book is highly relevant to civil, automotive and aerospace engineering students.

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Chester Ismay,Albert Y. Kim
Statistical Inference via Data Science A ModernDive into R and the Tidyverse Book PDF

Author : Chester Ismay,Albert Y. Kim
Publisher : CRC Press
Page : 377 pages
File Size : 43,7 Mb
Release : 2019-12-23
Category : Mathematics
ISBN : 9781000763560

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse by Chester Ismay,Albert Y. Kim Pdf

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.

R for Data Science

Hadley Wickham,Garrett Grolemund
R for Data Science Book PDF

Author : Hadley Wickham,Garrett Grolemund
Publisher : "O'Reilly Media, Inc."
Page : 521 pages
File Size : 47,6 Mb
Release : 2016-12-12
Category : Computers
ISBN : 9781491910368

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R for Data Science by Hadley Wickham,Garrett Grolemund Pdf

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: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Data Science in R

Deborah Nolan,Duncan Temple Lang
Data Science in R Book PDF

Author : Deborah Nolan,Duncan Temple Lang
Publisher : CRC Press
Page : 539 pages
File Size : 50,7 Mb
Release : 2015-04-21
Category : Business & Economics
ISBN : 9781482234824

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Data Science in R by Deborah Nolan,Duncan Temple Lang Pdf

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book’s collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standard, complex data formats, such as robot logs and email messages Text processing and regular expressions Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth Statistical methods, such as classification trees, k-nearest neighbors, and naïve Bayes Visualization and exploratory data analysis Relational databases and Structured Query Language (SQL) Simulation Algorithm implementation Large data and efficiency Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data. Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers’ computational reasoning of real-world data analyses.

Learning Statistics with R

Daniel Navarro
Learning Statistics with R Book PDF

Author : Daniel Navarro
Publisher : Lulu.com
Page : 617 pages
File Size : 49,6 Mb
Release : 2013-01-13
Category : Psychology
ISBN : 9781326189723

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Learning Statistics with R by Daniel Navarro Pdf

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Computer Age Statistical Inference

Bradley Efron,Trevor Hastie
Computer Age Statistical Inference Book PDF

Author : Bradley Efron,Trevor Hastie
Publisher : Cambridge University Press
Page : 496 pages
File Size : 44,8 Mb
Release : 2016-07-21
Category : Business & Economics
ISBN : 9781107149892

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Computer Age Statistical Inference by Bradley Efron,Trevor Hastie Pdf

Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

Modern Statistics with R

Måns Thulin
Modern Statistics with R Book PDF

Author : Måns Thulin
Publisher : BoD - Books on Demand
Page : 598 pages
File Size : 48,7 Mb
Release : 2021-07-28
Category : Mathematics
ISBN : 9789152701515

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Modern Statistics with R by Måns Thulin Pdf

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.

The Grammar of Graphics

Leland Wilkinson
The Grammar of Graphics Book PDF

Author : Leland Wilkinson
Publisher : Springer Science & Business Media
Page : 415 pages
File Size : 41,7 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9781475731002

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The Grammar of Graphics by Leland Wilkinson Pdf

Written for statisticians, computer scientists, geographers, research and applied scientists, and others interested in visualizing data, this book presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systems. It was designed for a distributed computing environment, with special attention given to conserving computer code and system resources. While the tangible result of this work is a Java production graphics library, the text focuses on the deep structures involved in producing quantitative graphics from data. It investigates the rules that underlie pie charts, bar charts, scatterplots, function plots, maps, mosaics, and radar charts. These rules are abstracted from the work of Bertin, Cleveland, Kosslyn, MacEachren, Pinker, Tufte, Tukey, Tobler, and other theorists of quantitative graphics.

Data Science in Education Using R

Ryan A. Estrellado,Emily A. Freer,Jesse Mostipak,Joshua M. Rosenberg,Isabella C. Velásquez
Data Science in Education Using R Book PDF

Author : Ryan A. Estrellado,Emily A. Freer,Jesse Mostipak,Joshua M. Rosenberg,Isabella C. Velásquez
Publisher : Routledge
Page : 315 pages
File Size : 42,8 Mb
Release : 2020-10-26
Category : Education
ISBN : 9781000200904

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Data Science in Education Using R by Ryan A. Estrellado,Emily A. Freer,Jesse Mostipak,Joshua M. Rosenberg,Isabella C. Velásquez Pdf

Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.

Statistics With R

Jenine K. Harris
Statistics With R Book PDF

Author : Jenine K. Harris
Publisher : SAGE Publications
Page : 821 pages
File Size : 50,6 Mb
Release : 2019-12-19
Category : Social Science
ISBN : 9781506388137

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Statistics With R by Jenine K. Harris Pdf

Recipient of a 2021 Most Promising New Textbook Award from the Textbook & Academic Authors Association (TAA) "Statistics with R is easily the most accessible and almost fun introduction to statistics and R that I have read. Even the most hesitant student is likely to embrace the material with this text." —David A.M. Peterson, Department of Political Science, Iowa State University Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world’s tricky problems faced by the "R Team" characters. Inspired by the programming group "R Ladies," the R Team works together to master the skills of statistical analysis and data visualization to untangle real-world, messy data using R. The storylines draw students into investigating contemporary issues such as marijuana legalization, voter registration, and the opioid epidemic, and lead them step-by-step through full-color illustrations of R statistics and interactive exercises. Included with this title: The password-protected Instructor Resource Site (formally known as SAGE Edge) offers access to all text-specific resources, including a test bank and editable, chapter-specific PowerPoint® slides.

Handbook of Regression Modeling in People Analytics

Keith McNulty
Handbook of Regression Modeling in People Analytics Book PDF

Author : Keith McNulty
Publisher : CRC Press
Page : 272 pages
File Size : 55,9 Mb
Release : 2021-07-29
Category : Business & Economics
ISBN : 9781000427899

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Handbook of Regression Modeling in People Analytics by Keith McNulty Pdf

Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: • 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) • Clear step-by-step instructions on executing the analyses. • Clear guidance on how to interpret results. • Primary instruction in R but added sections for Python coders. • Discussion exercises and data exercises for each of the main chapters. • Final chapter of practice material and datasets ideal for class homework or project work.

Computer Age Statistical Inference, Student Edition

Bradley Efron,Trevor Hastie
Computer Age Statistical Inference Student Edition Book PDF

Author : Bradley Efron,Trevor Hastie
Publisher : Cambridge University Press
Page : 513 pages
File Size : 53,8 Mb
Release : 2021-06-17
Category : Computers
ISBN : 9781108823418

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Computer Age Statistical Inference, Student Edition by Bradley Efron,Trevor Hastie Pdf

Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.

OpenIntro Statistics

David Diez,Christopher Barr,Mine Çetinkaya-Rundel
OpenIntro Statistics Book PDF

Author : David Diez,Christopher Barr,Mine Çetinkaya-Rundel
Publisher : Unknown
Page : 128 pages
File Size : 40,8 Mb
Release : 2015-07-02
Category : Electronic
ISBN : 1943450048

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OpenIntro Statistics by David Diez,Christopher Barr,Mine Çetinkaya-Rundel Pdf

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.

Statistics Done Wrong

Alex Reinhart
Statistics Done Wrong Book PDF

Author : Alex Reinhart
Publisher : No Starch Press
Page : 177 pages
File Size : 47,5 Mb
Release : 2015-03-01
Category : Mathematics
ISBN : 9781593276201

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Statistics Done Wrong by Alex Reinhart Pdf

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.