R in Action: Data Analysis
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Questions and Answers

Who is the author of 'R in Action'?

Robert I. Kabacoff

Which publisher published 'R in Action'?

  • Springer
  • O'Reilly
  • Packt
  • Manning Publications (correct)

    • The book 'R in Action' was published in 2011.

    True

    Manning books are printed on paper that is at least __ percent recycled.

    <p>15</p> Signup and view all the answers

    What is the email address for orders at Manning Publications?

    <p><a href="mailto:[email protected]">[email protected]</a></p> Signup and view all the answers

    What is the purpose of the introduction to R?

    <p>To provide a basic understanding of R</p> Signup and view all the answers

    What are the four graphic systems in R?

    <p>Base R, Lattice, ggplot2, and other interactive graphics systems.</p> Signup and view all the answers

    The pwr package is used for implementing power analysis.

    <p>True</p> Signup and view all the answers

    In regression, the ______ function is commonly used to fit a model.

    <p>lm()</p> Signup and view all the answers

    Which section covers advanced methods for missing data?

    <p>Part IV</p> Signup and view all the answers

    What is the purpose of generalized linear models?

    <p>To extend linear regression to model response variables that have different distributions.</p> Signup and view all the answers

    What is a significant feature of R?

    <p>It offers over 50,000 analytic and graphic functions.</p> Signup and view all the answers

    R is an open-source project.

    <p>True</p> Signup and view all the answers

    What approach did the author take to learn R?

    <p>The author approached R as a data scientist.</p> Signup and view all the answers

    R is supported by a large and diverse __________ of data scientists and programmers.

    <p>community</p> Signup and view all the answers

    Who asked the author to write the book?

    <p>Marjan Bace</p> Signup and view all the answers

    What did the author do when he was offered a job related to R?

    <p>The author was offered the job but didn’t take it.</p> Signup and view all the answers

    R in Action is suitable for users with a statistical background only.

    <p>False</p> Signup and view all the answers

    The book contains __________ chapters divided into several parts.

    <p>16</p> Signup and view all the answers

    What does Chapter 1 cover?

    <p>An introduction to R and the features that make it useful for data analysis.</p> Signup and view all the answers

    What does Chapter 10 focus on?

    <p>Hypothesis testing and sample size determination</p> Signup and view all the answers

    What is R primarily used for?

    <p>Statistical Analysis</p> Signup and view all the answers

    R is a case-sensitive programming language.

    <p>True</p> Signup and view all the answers

    What is the purpose of the setwd() function in R?

    <p>To set the current working directory.</p> Signup and view all the answers

    The function used to obtain help on a specific function in R is called ______.

    <p>help()</p> Signup and view all the answers

    Match the R functions with their descriptions:

    <p>getwd() = List the current working directory. ls() = List the objects in the current workspace. rm() = Remove one or more objects from the workspace. q() = Quit R and prompt to save the workspace.</p> Signup and view all the answers

    What is the output of mean(weight) if the weight data for infants is 7.06 kilograms?

    <p>7.06</p> Signup and view all the answers

    What type of data structure is a data frame in R?

    <p>A collection of objects organized in columns and rows.</p> Signup and view all the answers

    R allows you to create graphs easily.

    <p>True</p> Signup and view all the answers

    What does the command plot(age, weight) do?

    <p>Creates a scatter plot of age versus weight.</p> Signup and view all the answers

    What function can you use to search for help on a specific topic online?

    <p>RSiteSearch()</p> Signup and view all the answers

    Which method is NOT mentioned as a way to test independence of categorical variables?

    <p>T-test</p> Signup and view all the answers

    What function is used to perform a chi-square test of independence in R?

    <p>chisq.test()</p> Signup and view all the answers

    The p-value indicates the probability of obtaining the sampled results assuming independence of the variables.

    <p>True</p> Signup and view all the answers

    To produce Fisher’s exact test, you use the function ______

    <p>fisher.test()</p> Signup and view all the answers

    When might the chi-square test approximation be invalid?

    <p>When one of the expected values is less than five.</p> Signup and view all the answers

    In the given example, what was the p-value for the relationship between treatment and improvement?

    <p>0.001463</p> Signup and view all the answers

    What does the fisher.test() function evaluate?

    <p>The null hypothesis of independence of rows and columns in a contingency table.</p> Signup and view all the answers

    What is R?

    <p>A language and environment for statistical computing and graphics.</p> Signup and view all the answers

    Which of the following features recommend R as a statistical tool? (Select all that apply)

    <p>R is free</p> Signup and view all the answers

    R can import data from a wide variety of sources.

    <p>True</p> Signup and view all the answers

    Match the following terms with their descriptions:

    <p>R = A language for statistical computing Open-source = Software that is free to use and modify Statistical analysis = The process of analyzing data to derive insights Graphics capabilities = The ability to create visual data representations</p> Signup and view all the answers

    What does R allow you to do with the results of any analytic step?

    <p>Save, manipulate, and use as input for additional analyses.</p> Signup and view all the answers

    R is an interactive language that indicates readiness for the next line of user input with a prompt (______ by default).

    <blockquote> </blockquote> Signup and view all the answers

    Which operating systems have versions of R available? (Select all that apply)

    <p>Linux</p> Signup and view all the answers

    What function is used to calculate row means of a matrix?

    <p>apply()</p> Signup and view all the answers

    What is the output of apply(mydata, 1, mean)?

    <p>-0.155 -0.504 -0.511 0.154 -0.310 0.165</p> Signup and view all the answers

    What does the trim parameter in apply(mydata, 2, mean, trim=0.2) do?

    <p>It calculates trimmed column means by discarding the top and bottom percentages of values.</p> Signup and view all the answers

    How does the ‘grade’ variable get created in the roster?

    <p>Using logical operators to recode students’ percentile ranks.</p> Signup and view all the answers

    Which function is used to standardize variables before combining them?

    <p>scale()</p> Signup and view all the answers

    The for loop executes a statement repetitively until the condition is no longer true.

    <p>True</p> Signup and view all the answers

    What is the purpose of the order() function?

    <p>To sort the dataset by specified variables.</p> Signup and view all the answers

    You can recode students’ percentile ranks into a categorical grade variable using _____ operators.

    <p>logical</p> Signup and view all the answers

    The sapply() function is less user-friendly than lapply().

    <p>False</p> Signup and view all the answers

    Study Notes

    Publication Information

    • Title: "R in Action: Data Analysis and Graphics with R"
    • Author: Robert I. Kabacoff
    • Publisher: Manning Publications Co.
    • Year of Publication: 2011
    • Location: Shelter Island, NY
    • All rights reserved by Manning Publications Co.
    • Prohibits reproduction, storage, or transmission without prior written permission.
    • Designations used by manufacturers may be trademarks and are printed in caps when applicable.

    Environmental Commitment

    • Books printed on acid-free paper.
    • Commitment to using paper that is at least 15% recycled.
    • Processed without the use of elemental chlorine to conserve resources.

    Contact Information

    • Website: www.manning.com for further information and ordering
    • Special Sales Department contact available for quantity discounts and inquiries.### Development Team and Publication Information
    • Development editor: Sebastian Stirling
    • Copyeditor: Liz Welch
    • Typesetter: Composure Graphics
    • Cover designer: Marija Tudor
    • ISBN: 9781935182399
    • Printed in the United States

    Structure of the Book

    • Organized into four main parts: Getting Started, Basic Methods, Intermediate Methods, and Advanced Methods
    • Each part contains a varied number of chapters focusing on different aspects of using R for data analysis

    Part I: Getting Started

    • Introduction to R: Reasons for using R and installation procedures
    • Working with datasets: Understanding data structures like vectors, matrices, data frames, and factors
    • Data management basics: Creating, recoding, and merging datasets

    Part II: Basic Methods

    • Basic Graphs: Techniques for creating bar plots, histograms, and pie charts
    • Statistical Concepts: Overview of descriptive statistics, frequency tables, and correlations

    Part III: Intermediate Methods

    • Regression Analysis: Detailed exploration of Ordinary Least Squares (OLS) regression, diagnostics, and model selection
    • Analysis of Variance (ANOVA): Concepts around one-way and two-way ANOVA, plus MANOVA
    • Resampling techniques: Permutation tests and bootstrapping methods

    Part IV: Advanced Methods

    • Generalized Linear Models: Techniques for logistic and Poisson regression with in-depth diagnostics
    • Principal Components and Factor Analysis: Methods for extracting and interpreting components and factors
    • Handling Missing Data: Strategies for identification, analysis, and imputation
    • Advanced Graphics: Introduction to graphic systems in R and detailed exploration of ggplot2 and lattice packages

    Additional Information

    • Includes appendices for GUI interfaces, exporting data, creating publication-quality output, and matrix algebra in R
    • Includes references and an index for quick navigation through topics ### Introduction to R
    • R is a flexible platform for exploring, visualizing, and understanding data with more than 50,000 analytic and graphic functions.
    • R is perceived as difficult to learn, but with proper guidance, it can be approachable for users of all experience levels.

    Learning R

    • The author's initial encounter with R occurred during a job application, prompting a fast-paced self-study approach.
    • Learning resources often focused on either the structure of the language or advanced statistical methods, but lacked practical tutorials for beginners.
    • Experiential learning through teaching led to the creation of a supportive website for R learners.

    Book Overview

    • The book aims to serve as a comprehensive guide to R, designed to ease the learning curve associated with the platform.
    • Key components include methods for accessing, cleaning, annotating, summarizing, visualizing, and modeling data effectively.

    Target Audience

    • Suitable for individuals dealing with data, regardless of their programming or statistical background.
    • Accessible chapters cater to novices, while advanced topics satisfy experienced R users.

    Structure of the Book

    • Organized into four parts: "Getting Started," "Basic Methods," "Intermediate Methods," and "Advanced Methods."
    • Includes 16 chapters and 8 appendices, covering a broad range of data analysis techniques and graphical methods.

    Topics Covered

    • Initial chapters focus on obtaining R, data structures, and importing data from various sources.
    • Visualization techniques are emphasized early, along with basic data management functions like sorting and subsetting.
    • Advanced statistical methods include regression analysis, analysis of variance (ANOVA), and approaches for handling missing data.

    Practical Applications

    • Real-world examples across various fields such as psychology, medicine, and business enhance applicability.
    • Enhanced understanding through smaller datasets allows a focus on techniques rather than domain-specific knowledge.

    Additional Resources

    • Access to code examples and supplementary materials online supports ongoing learning.
    • Encouragement to actively experiment with R to foster comprehension and skill development.

    Acknowledgments

    • Many individuals contributed to the book's development, including editors, reviewers, and family support.
    • Recognition of the broader R community and software authors who enhance R's capabilities through package development.

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    Related Documents

    R_in_Action data analysis.pdf

    Description

    This quiz explores the key concepts and techniques from 'R in Action' by Robert I. Kabacoff, focusing on data analysis and graphics using R. Test your knowledge on the practical applications of R for statistical analysis and data visualization.

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