Statistical Analysis with R Essentials for Dummies
Statistical Analysis with R Essentials For Dummies is your reference to all the core concepts about R—the widely used, open-source programming language and data analysis tool. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff. Understand all yo...
| Autor principal: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated
2024.
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| Edición: | 1st ed |
| Colección: | --For dummies.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009811315806719 |
Tabla de Contenidos:
- Intro
- Title Page
- Copyright Page
- Table of Contents
- 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
- Samples and populations
- Variables: Dependent and independent
- Types of data
- A little probability
- Inferential Statistics: Testing Hypotheses
- Null and alternative hypotheses
- Two types of error
- Chapter 2 Introducing R
- Downloading R and RStudio
- A Session with R
- The working directory
- So let's get started, already
- Missing data
- R Functions
- User-Defined Functions
- R Structures
- Vectors
- Numerical vectors
- Matrices
- Factors
- Lists
- Lists and statistics
- Data frames
- Extracting data from a data frame
- for Loops and if Statements
- Chapter 3 Digging Deeper Into R
- Packages
- More on Packages
- R Formulas
- Reading and Writing
- Spreadsheets
- CSV files
- Text files
- Chapter 4 Finding Your Center
- Means: The Lure of Averages
- The Average in R: mean()
- What's your condition?
- Eliminate signs forthwith()
- 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
- Averaging squared deviations: Variance and how to calculate it
- Sample variance
- Variance in R
- Back to the Roots: Standard Deviation
- Population standard deviation
- Sample 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?
- Ranking in R
- Tied scores
- Nth smallest, Nth largest
- Percentiles
- Percent ranks
- Creating Summaries
- How Many?
- The High and the Low.
- Summarizing a Data Frame
- Chapter 7 What's Normal?
- Hitting the Curve
- Digging deeper
- Parameters of a normal distribution
- Distributions in R
- Normal density function
- Cumulative density function
- Quantiles of normal distributions
- Random sampling
- 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
- Applying the central limit theorem
- Zs once more
- Z-testing for two samples in R
- t for Two
- Like Peas in a Pod: Equal Variances
- t-Testing in R
- Working with two vectors
- Working with a data frame and a formula
- Like p's and q's: Unequal variances
- 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
- After the ANOVA
- Another word about contrasts
- Contrasts 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!
- Using regression for forecasting
- Variation around the regression 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
- EULA.
