Statistical Analysis with R Essentials For Dummies 9781394263431, 9781394263424, 9781394263448
The easy way to get started coding and analyzing data in the R programming language Statistical Analysis with R Essentia
147 12 2MB
English Pages 192 Year 2024
Table of contents :
Cover
Table of Contents
Title Page
Copyright
Introduction
About This Book
Foolish Assumptions
Icons Used in This Book
Where to Go from Here
Chapter 1: Data, Statistics, and Decisions
The Statistical (and Related) Notions You Just Have to Know
Inferential Statistics: Testing Hypotheses
Chapter 2: Introducing R
Downloading R and RStudio
A Session with R
R Functions
User-Defined Functions
R Structures
for Loops and if Statements
Chapter 3: Digging Deeper Into R
Packages
More on Packages
R Formulas
Reading and Writing
Chapter 4: Finding Your Center
Means: The Lure of Averages
The Average in R: mean()
Medians: Caught in the Middle
The Median in R: median()
Statistics à la Mode
The Mode in R
Chapter 5: Deviating from the Average
Measuring Variation
Back to the Roots: Standard Deviation
Standard Deviation in R
Conditions, Conditions, Conditions …
Chapter 6: Standards, Standings, and Summaries
Catching Some Zs
Standard Scores in R
Where Do You Stand?
Creating Summaries
How Many?
The High and the Low
Summarizing a Data Frame
Chapter 7: What’s Normal?
Hitting the Curve
Distributions in R
A Distinguished Member of the Family
Chapter 8: The Confidence Game: Estimation
Understanding Sampling Distributions
An EXTREMELY Important Idea: The Central Limit Theorem
Confidence: It Has its Limits!
Fit to a t
Chapter 9: One-Sample Hypothesis Testing
Hypotheses, Tests, and Errors
Hypothesis Tests and Sampling Distributions
Catching Some Z's Again
Z Testing in R
t for One
t Testing in R
Working with t-Distributions
Chapter 10: Two-Sample Hypothesis Testing
Hypotheses Built for Two
Sampling Distributions Revisited
t for Two
Like Peas in a Pod: Equal Variances
t-Testing in R
A Matched Set: Hypothesis Testing for Paired Samples
Paired Sample t-testing in R
Chapter 11: Testing More Than Two Samples
Testing More Than Two
ANOVA in R
Another Kind of Hypothesis, Another Kind of Test
Getting Trendy
Trend Analysis in R
Chapter 12: Linear Regression
The Plot of Scatter
Regression: What a Line!
Testing Hypotheses about Regression
Linear Regression in R
Making Predictions
Chapter 13: Correlation: The Rise and Fall of Relationships
Understanding Correlation
Correlation and Regression
Testing Hypotheses About Correlation
Analyzing Correlation in R
Chapter 14: Ten Valuable Online Resources
R-bloggers
Posit
Quick-R
Stack Overflow
R Manuals
R Documentation
RDocumentation
YOU CANanalytics
Geocomputation with R
The R Journal
Index
About the Author
Connect with Dummies
End User License Agreement
Cover
Table of Contents
Title Page
Copyright
Introduction
About This Book
Foolish Assumptions
Icons Used in This Book
Where to Go from Here
Chapter 1: Data, Statistics, and Decisions
The Statistical (and Related) Notions You Just Have to Know
Inferential Statistics: Testing Hypotheses
Chapter 2: Introducing R
Downloading R and RStudio
A Session with R
R Functions
User-Defined Functions
R Structures
for Loops and if Statements
Chapter 3: Digging Deeper Into R
Packages
More on Packages
R Formulas
Reading and Writing
Chapter 4: Finding Your Center
Means: The Lure of Averages
The Average in R: mean()
Medians: Caught in the Middle
The Median in R: median()
Statistics à la Mode
The Mode in R
Chapter 5: Deviating from the Average
Measuring Variation
Back to the Roots: Standard Deviation
Standard Deviation in R
Conditions, Conditions, Conditions …
Chapter 6: Standards, Standings, and Summaries
Catching Some Zs
Standard Scores in R
Where Do You Stand?
Creating Summaries
How Many?
The High and the Low
Summarizing a Data Frame
Chapter 7: What’s Normal?
Hitting the Curve
Distributions in R
A Distinguished Member of the Family
Chapter 8: The Confidence Game: Estimation
Understanding Sampling Distributions
An EXTREMELY Important Idea: The Central Limit Theorem
Confidence: It Has its Limits!
Fit to a t
Chapter 9: One-Sample Hypothesis Testing
Hypotheses, Tests, and Errors
Hypothesis Tests and Sampling Distributions
Catching Some Z's Again
Z Testing in R
t for One
t Testing in R
Working with t-Distributions
Chapter 10: Two-Sample Hypothesis Testing
Hypotheses Built for Two
Sampling Distributions Revisited
t for Two
Like Peas in a Pod: Equal Variances
t-Testing in R
A Matched Set: Hypothesis Testing for Paired Samples
Paired Sample t-testing in R
Chapter 11: Testing More Than Two Samples
Testing More Than Two
ANOVA in R
Another Kind of Hypothesis, Another Kind of Test
Getting Trendy
Trend Analysis in R
Chapter 12: Linear Regression
The Plot of Scatter
Regression: What a Line!
Testing Hypotheses about Regression
Linear Regression in R
Making Predictions
Chapter 13: Correlation: The Rise and Fall of Relationships
Understanding Correlation
Correlation and Regression
Testing Hypotheses About Correlation
Analyzing Correlation in R
Chapter 14: Ten Valuable Online Resources
R-bloggers
Posit
Quick-R
Stack Overflow
R Manuals
R Documentation
RDocumentation
YOU CANanalytics
Geocomputation with R
The R Journal
Index
About the Author
Connect with Dummies
End User License Agreement
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