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R All-in-One 2026/2027 | 5 Books in 1 | Data Analysis, Statistics & Visualization Made Easy

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Master R programming with this 5-in-1 complete study guide designed for students, data analysts, and professionals. The R All-in-One 2026/2027 Edition by Academic Hub combines statistics, data visualization, programming, and applied projects into one easy-to-use resource. What You’ll Learn: Statistics with R – Core statistical concepts, hypothesis testing, regression, and data modeling. R Programming Basics – Functions, loops, packages, and efficient coding practices. Data Visualization – Create stunning plots with base R, ggplot2, and advanced graphing libraries. Data Science Applications – Clean, analyze, and transform datasets with hands-on examples. Practical Projects – Apply R to machine learning, finance, research, and academic studies. Whether you are preparing for college coursework, research projects, or professional certifications, this all-in-one guide ensures you gain the practical skills needed to analyze data effectively in 2025 and beyond. R all in one study guide 2025, R programming academic hub, R statistics and data science book, R language beginner to advanced, R for data visualization ggplot2, R for data analysis and research, statistics with R step by step, R coding projects and applications, R machine learning crash course, R programming exam prep, R statistical modeling simplified, learn R for college and university, R for business analytics and data science, data visualization with R made easy, R all in one 5 books in 1, R for beginners and professionals 2025, academic hub R guide pdf, R for machine learning basics, R programming projects book, R coding and visualization for students

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Institution
Data
Course
Data

Content preview

,Contents at a Glance
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Book 1: Introducing R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
CHAPTER 1: R: What It Does and How It Does It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
CHAPTER 2: Working with Packages, Importing, and Exporting . . . . . . . . . . . . . . . . . . 37

Book 2: Describing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
CHAPTER 1: Getting Graphic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
CHAPTER 2: Finding Your Center . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
CHAPTER 3: Deviating from the Average . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
CHAPTER 4: Meeting Standards and Standings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
CHAPTER 5: Summarizing It All . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
CHAPTER 6: What’s Normal? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145

Book 3: Analyzing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
CHAPTER 1: The Confidence Game: Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
CHAPTER 2: One-Sample Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
CHAPTER 3: Two-Sample Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
CHAPTER 4: Testing More than Two Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
CHAPTER 5: More Complicated Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
CHAPTER 6: Regression: Linear, Multiple, and the General Linear Model . . . . . . . . 279
CHAPTER 7: Correlation: The Rise and Fall of Relationships . . . . . . . . . . . . . . . . . . . . 315
CHAPTER 8: Curvilinear Regression: When Relationships
Get Complicated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
CHAPTER 9: In Due Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
CHAPTER 10: Non-Parametric Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
CHAPTER 11: Introducing Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
CHAPTER 12: Probability Meets Regression: Logistic Regression . . . . . . . . . . . . . . . . . 415

Book 4: Learning from Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423
CHAPTER 1: Tools and Data for Machine Learning Projects . . . . . . . . . . . . . . . . . . . . 425
CHAPTER 2: Decisions, Decisions, Decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
CHAPTER 3: Into the Forest, Randomly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467
CHAPTER 4: Support Your Local Vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483
CHAPTER 5: K-Means Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503
CHAPTER 6: Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519
CHAPTER 7: Exploring Marketing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537
CHAPTER 8: From the City That Never Sleeps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557

,Book 5: Harnessing R: Some Projects to
Keep You Busy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573
CHAPTER 1: Working with a Browser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 575
CHAPTER 2: Dashboards — How Dashing! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639

, Table of Contents
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
About This All-in-One . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Book 1: Introducing R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Book 2: Describing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Book 3: Analyzing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Book 4: Learning from Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Book 5: Harnessing R: Some Projects to Keep You Busy . . . . . . . . . . 3
What You Can Safely Skip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Foolish Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Icons Used in This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Beyond This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Where to Go from Here . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

BOOK 1: INTRODUCING R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

CHAPTER 1: R: What It Does and How It Does It . . . . . . . . . . . . . . . . . . . . 7
The Statistical (and Related) Ideas You Just Have to Know . . . . . . . . . . . 7
Samples and populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Variables: Dependent and independent . . . . . . . . . . . . . . . . . . . . . . . 8
Types of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
A little probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
Inferential statistics: Testing hypotheses . . . . . . . . . . . . . . . . . . . . . .12
Null and alternative hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
Two types of error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
Getting R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
Getting RStudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
A Session with R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18
The working directory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18
Getting started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
R Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22
User-Defined Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24
Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25
R Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25
Vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25
Numerical vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26
Matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28
Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31
Data frames . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .32
for Loops and if Statements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35




Table of Contents v

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Data

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