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R Data Analysis Without Programming

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R Data Analysis Without Programming

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Author : David W. Gerbing
language : en
Publisher: Taylor & Francis
Release Date : 2023-01-30

R Data Analysis Without Programming written by David W. Gerbing and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-30 with Psychology categories.

The new edition of this innovative book, R Data Analysis without Programming, prepares the readers to quickly analyze data and interpret statistical results using R. Professor Gerbing has developed lessR, a ground-breaking method in alleviating the challenges of R programming. The lessR extends R, removing the need for programming. This edition expands upon the first edition’s introduction to R through lessR, which enables the readers to learn how to organize data for analysis, read the data into R, and generate output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables with simple function calls. The text reviews and explains basic statistical procedures with the lessR enhancements added to the standard R environment. Using lessR, data analysis with R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights along with content new to this edition include: Explanation and Interpretation of all data analysis techniques; much more than a computer manual, this book shows the reader how to explain and interpret the results. Introduces the concepts and commands reviewed in each chapter. Clear, relaxed writing style more effectively communicates the underlying concepts than more stilted academic writing. Extensive margin notes highlight, define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number for the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input, output, and an interpretation of the results. Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate the analysis and how to interpret results. Two data sets are analyzed multiple times in the book, provide continuity throughout. Comprehensive: A wide range of data analysis techniques are presented throughout the book. Integration with machine learning as regression analysis is presented from both the traditional perspective and from the modern machine learning perspective. End of chapter problems help readers test their understanding of the concepts. A website at www.lessRstats.com that features the data sets referenced in both standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, R/lessR videos to help readers better understand the program, and more. This book is ideal for graduate and undergraduate courses in statistics beyond the introductory course, research methods, and/or any data analysis course, taught in departments of psychology, business, education, and other social and health sciences; this book is also appreciated by researchers doing data analysis. Prerequisites include basic statistical knowledge, though the concepts are explained from the beginning in the book. Previous knowledge of R is not assumed.

R Data Analysis Without Programming

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Author : David W. Gerbing
language : en
Publisher: Taylor & Francis
Release Date : 2023-01-30

R Data Analysis Without Programming

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Author : David W. Gerbing
language : en
Publisher: Routledge
Release Date : 2013-12-13

R Data Analysis Without Programming written by David W. Gerbing and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-13 with Psychology categories.

This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without programming. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights of the book include: Quick Starts that introduce readers to the concepts and commands reviewed in the chapters. Margin notes that highlight,define,illustrate,and cross-reference the key concepts.When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output. Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate how to interpret results. Two data sets provided on the website and analyzed multiple times in the book, provide continuity throughout. End of chapter worked problems help readers test their understanding of the concepts. A website at www.lessRstats.com that features the lessR program, the book’s data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book’s worked problems, links to R/lessR videos to help readers better understand the program, and more. An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used, taught in departments of psychology, business, education, and other social and health sciences, this book is also appreciated by researchers interested in using R for their data analysis. Prerequisites include basic statistical knowledge. Knowledge of R is not assumed.

Data Science With R For Psychologists And Healthcare Professionals

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Author : Christian Ryan
language : en
Publisher: CRC Press
Release Date : 2021-12-22

Data Science With R For Psychologists And Healthcare Professionals written by Christian Ryan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-22 with Business & Economics categories.

This introduction to R for students of psychology and health sciences aims to fast-track the reader through some of the most difficult aspects of learning to do data analysis and statistics. It demonstrates the benefits for reproducibility and reliability of using a programming language over commercial software packages such as SPSS. The early chapters build at a gentle pace, to give the reader confidence in moving from a point-and-click software environment, to the more robust and reliable world of statistical coding. This is a thoroughly modern and up-to-date approach using RStudio and the tidyverse. A range of R packages relevant to psychological research are discussed in detail. A great deal of research in the health sciences concerns questionnaire data, which may require recoding, aggregation and transformation before quantitative techniques and statistical analysis can be applied. R offers many useful and transparent functions to process data and check psychometric properties. These are illustrated in detail, along with a wide range of tools R affords for data visualisation. Many introductory statistics books for the health sciences rely on toy examples - in contrast, this book benefits from utilising open datasets from published psychological studies, to both motivate and demonstrate the transition from data manipulation and analysis to published report. R Markdown is becoming the preferred method for communicating in the open science community. This book also covers the detail of how to integrate the use of R Markdown documents into the research workflow and how to use these in preparing manuscripts for publication, adhering to the latest APA style guidelines.

Becoming A Behavioral Science Researcher

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Author : Rex B. Kline
language : en
Publisher: Guilford Publications
Release Date : 2019-11-12

Becoming A Behavioral Science Researcher written by Rex B. Kline and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-12 with Business & Economics categories.

Students and beginning researchers often discover that their introductory statistics and methods courses have not fully equipped them to plan and execute their own behavioral research studies. This indispensable book bridges the gap between coursework and conducting independent research. With clarity and wit, the author helps the reader build needed skills to formulate a precise, meaningful research question; understand the pros and cons of widely used research designs and analysis options; correctly interpret the outcomes of statistical tests; make informed measurement choices for a particular study; manage the practical aspects of data screening and preparation; and craft effective journal articles, oral presentations, and posters. Including annotated examples and recommended readings, most chapters feature theoretical and computer-based exercises; an answer appendix at the back of the book allows readers to check their work.

Quantitative Social Science

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Author : Kosuke Imai
language : en
Publisher: Princeton University Press
Release Date : 2022-08-02

Quantitative Social Science written by Kosuke Imai and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Social Science categories.

A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior. Emphasizes hands-on learning, not paper-and-pencil statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

Veridical Data Science

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Author : Bin Yu
language : en
Publisher: MIT Press
Release Date : 2024-10-15

Veridical Data Science written by Bin Yu and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-15 with Computers categories.

Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science. Most textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. Veridical Data Science, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs. Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle: the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, Veridical Data Science offers a clear and actionable guide for conducting responsible data science. Requiring little background knowledge, this lucid, self-contained textbook provides a solid foundation and principled framework for future study of advanced methods in machine learning, statistics, and data science. Presents the Predictability, Computability, and Stability (PCS) methodology for producing trustworthy data-driven results Teaches how a data science project should be conducted from beginning to end, including extensive discussion of the data scientist's decision-making process Cultivates critical thinking throughout the entire data science life cycle Provides practical examples and illuminating case studies of real-world data analysis problems with associated code, exercises, and solutions Suitable for advanced undergraduate and graduate students, domain scientists, and practitioners

Auditing

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Author : Raymond N. Johnson
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-16

Auditing written by Raymond N. Johnson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-16 with Business & Economics categories.

The explosion of data analytics in the auditing profession demands a different kind of auditor. Auditing: A Practical Approach with Data Analytics prepares students for the rapidly changing demands of the auditing profession by meeting the data-driven requirements of today's workforce. Because no two audits are alike, this course uses a practical, case-based approach to help students develop professional judgement, think critically about the auditing process, and develop the decision-making skills necessary to perform a real-world audit. To further prepare students for the profession, this course integrates seamless exam review for successful completion of the CPA Exam.

Introduction To Software For Chemical Engineers Second Edition

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Author : Mariano Martín Martín
language : en
Publisher: CRC Press
Release Date : 2019-06-06

Introduction To Software For Chemical Engineers Second Edition written by Mariano Martín Martín and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-06 with Computers categories.

The field of Chemical Engineering and its link to computer science is in constant evolution and new engineers have a variety of tools at their disposal to tackle their everyday problems. Introduction to Software for Chemical Engineers, Second Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications from Excel and general mathematical packages such as MATLAB and MathCAD to process simulators, CHEMCAD and ASPEN, equation-based modeling languages, gProms, optimization software such as GAMS and AIMS, and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, process and equipment design and control. This new edition offers a wider view of packages including open source software such as R, Python and Julia. It also includes complete examples in ASPEN Plus, adds ANSYS Fluent to CFD codes, Lingo to the optimization packages, and discusses Engineering Equation Solver. It offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems. Written by leading experts, this book is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate and master levels.

Introduction To Software For Chemical Engineers

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Author : Mariano Martín Martín
language : en
Publisher: CRC Press
Release Date : 2025-03-24

Introduction To Software For Chemical Engineers written by Mariano Martín Martín and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-24 with Computers categories.

The field of chemical engineering and its link to computer science is in constant evolution, and engineers have an ever-growing variety of tools at their disposal to tackle everyday problems. Introduction to Software for Chemical Engineers, Third Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications, including Excel and general mathematical packages such as MATLAB®, MathCAD, R, and Python. Coverage also extends to process simulators such as CHEMCAD, HYSYS, and Aspen; equation-based modeling languages such as gPROMS; optimization software such as GAMS, AIMS, and Julia; and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, and process and equipment design and control. This new edition is updated throughout to reflect software updates and new packages. It emphasizes the addition of SimaPro due to the importance of life cycle assessment, as well as general statistics software, SPSS, and Minitab that readers can use to analyze lab data. The book also includes new chapters on flowsheeting drawing, process control, and LOOP Pro, as well as updates to include Pyomo as an optimization platform, reflecting current trends. The text offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems. Written by leading experts, this handbook is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization, as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate- and graduate-level readers.

R Data Analysis Without Programming

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