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Author: Abbas F.M. Alkarkhi
Publisher: Academic Press
ISBN: 0128142634
Category : Technology & Engineering
Languages : en
Pages : 229
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Book Description
Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. - Contains numerous step-by-step tutorials help the reader to learn quickly - Covers the theory and application of the statistical techniques - Shows how to analyze data using R software - Provides R scripts for all examples and figures
Author: Abbas F.M. Alkarkhi
Publisher: Academic Press
ISBN: 0128142634
Category : Technology & Engineering
Languages : en
Pages : 229
Get Book Here
Book Description
Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. - Contains numerous step-by-step tutorials help the reader to learn quickly - Covers the theory and application of the statistical techniques - Shows how to analyze data using R software - Provides R scripts for all examples and figures
Author: Abbas F. M. Al-Karkhi
Publisher: Elsevier
ISBN: 0128186232
Category : Science
Languages : en
Pages : 242
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Book Description
Applied Statistics for Environmental Science with R presents the theory and application of statistical techniques in environmental science and aids researchers in choosing the appropriate statistical technique for analyzing their data. Focusing on the use of univariate and multivariate statistical methods, this book acts as a step-by-step resource to facilitate understanding in the use of R statistical software for interpreting data in the field of environmental science. Researchers utilizing statistical analysis in environmental science and engineering will find this book to be essential in solving their day-to-day research problems. - Includes step-by-step tutorials to aid in understanding the process and implementation of unique data - Presents statistical theory in a simple way without complex mathematical proofs - Shows how to analyze data using R software and provides R scripts for all examples and figures
Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522
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Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Author: Peter Dalgaard
Publisher: Springer Science & Business Media
ISBN: 0387790543
Category : Mathematics
Languages : en
Pages : 370
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Book Description
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Author: Abbas F.M. Alkarkhi
Publisher: Elsevier
ISBN: 0323851878
Category : Science
Languages : en
Pages : 294
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Book Description
Applications of Hypothesis Testing for Environmental Science presents the theory and application of hypothesis testing in environmental science, allowing researchers to carry out suitable tests for decision-making on a variety of issues. This book works as a step-by-step resource to provide understanding of the concepts and applications of hypothesis testing in the field of environmental science. The tests are presented in simplified form without relying on complex mathematical proofs to allow researchers to easily locate the most appropriate test and apply it to real-world situations. Each example is accompanied by a case study showing the application of the method to realistic data. This book provides step-by-step guidance in analyzing and testing various environmental data for researchers, postgraduates and graduates of environmental sciences, as well as academics looking for a book that includes case studies of the applications of hypothesis testing. It will also be a valuable resource for researchers in other related fields and those who are not familiar with the use of statistics who may need to analyze data or perform hypothesis tests in their research. - Includes step-by-step tutorials to aid in the understanding of procedures and allowing implementation of suitable tests - Presents the theory of hypothesis testing in a simple yet thorough manner without complex mathematical proofs - Describes how to implement hypothesis testing in analyzing and interpretation environmental science data
Author: Prof Cândida Silva
Publisher: Academic Conferences International
ISBN: 191276492X
Category : Travel
Languages : en
Pages :
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Book Description
Conference Proceedings of 4th International Conference on Tourism Research
Author: Peter Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category : Computers
Languages : en
Pages : 322
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Book Description
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Author: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833
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Book Description
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.
Author: Robert Stinerock
Publisher: SAGE
ISBN: 152642147X
Category : Social Science
Languages : en
Pages : 581
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Book Description
***Choice Outstanding Academic Title Award Winner*** The dynamic, student focused textbook provides step-by-step instruction in the use of R and of statistical language as a general research tool. It is ideal for anyone hoping to: Complete an introductory course in statistics Prepare for more advanced statistical courses Gain the transferable analytical skills needed to interpret research from across the social sciences Learn the technical skills needed to present data visually Acquire a basic competence in the use of R. The book provides readers with the conceptual foundation to use applied statistical methods in everyday research. Each statistical method is developed within the context of practical, real-world examples and is supported by carefully developed pedagogy and jargon-free definitions. Theory is introduced as an accessible and adaptable tool and is always contextualized within the pragmatic context of real research projects and definable research questions. Author Robert Stinerock has also created a wide range of online resources, including: R scripts, complete solutions for all exercises, data files for each chapter, video and screen casts, and interactive multiple-choice quizzes.
Author: Robert A. Hanneman
Publisher: John Wiley & Sons
ISBN: 0470587989
Category : Education
Languages : en
Pages : 560
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Book Description
A core statistics text that emphasizes logical inquiry, not math Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to understand (and do) social research. Its use of mathematics and theory are deliberately limited, as the authors focus on the use of concepts and tools of statistics in the analysis of social science data, rather than on the mathematical and computational aspects. Research questions and applications are taken from a wide variety of subfields in sociology, and each chapter is organized around one or more general ideas that are explained at its beginning and then applied in increasing detail in the body of the text. Each chapter contains instructive features to aid students in understanding and mastering the various statistical approaches presented in the book, including: Learning objectives Check quizzes after many sections and an answer key at the end of the chapter Summary Key terms End-of-chapter exercises SPSS exercises (in select chapters) Ancillary materials for both the student and the instructor are available and include a test bank for instructors and downloadable video tutorials for students.
