Beginning R an introduction to statistical programming
Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was de...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Berkeley, Calif.] :
Apress
2012.
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| Edición: | 1st ed. 2012. |
| Colección: | Expert's voice in programming
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628581106719 |
Tabla de Contenidos:
- Title Page; Copyright Page; Contents at a Glance; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Who This Book Is For; How This Book Is Structured; Conventions; Downloading the code; Contacting the Author; CHAPTER 1 Getting R and Getting Started; Getting and Using R; A First R Session; Moving Around in R; Working with Data in R; Vectors; Creating a Vector; Performing Vector Arithmetic; Adding Elements to a Vector; Matrices; Creating a Matrix; Referring to Matrix Rows and Columns; Matrix Manipulation; Data Frames
- Creating a Data Frame from VectorsCreating a Data Frame Using the R Data Editor; Reading a Table into a Data Frame; Dealing With Missing Data in R; Conclusion; CHAPTER 2 Programming in R; What is Programming?; Getting Ready to Program; The Requirements for Learning to Program; Flow Control; Looping; Conditional Statements and Branching; Essentials of R Programming; R Operators; Arithmetic Operators; Comparison Operators; Logical Operators; Input and Output in R; Understanding the R Environment; Implementation of Program Flow in R; For Loops; While and Repeat Loops; The While Loop
- The Repeat LoopAvoiding Explicit Loops: The Apply Function Family; A First R Program; Another Example-Finding Pythagorean Triples; Using R to Solve Quadratic Equations; Why R is Object-Oriented; The S3 and S4 Classes; Generic Functions; Conclusion; CHAPTER 3 Writing Reusable Functions; Examining an R Function from the Base R Code; Creating a Function; Calculating a Confidence Interval for a Mean; Avoiding Loops with Vectorized Operations; Vectorizing If-Else Statements Using ifelse(); Making More Powerful Functions; Any, All, and Which; Making Functions More Useful
- Confidence Intervals RevisitedConclusion; CHAPTER 4 Summary Statistics; Measuring Central Tendency; The Mean; The Median and Other Quantiles; The Mode; Measuring Location via Standard Scores; Measuring Variability; Variance and Standard Deviation; Range; Median and Mean Absolute Deviation; The Interquartile Range; The Coefficient of Variation; Covariance and Correlation; Measuring Symmetry (or Lack Thereof); Conclusion; CHAPTER 5 Creating Tables and Graphs; Frequency Distributions and Tables; Pie Charts and Bar Charts; Pie Charts; Bar Charts; Boxplots; Histograms; Line Graphs; Scatterplots
- Saving and Using GraphicsConclusion; CHAPTER 6 Discrete Probability Distributions; Discrete Probability Distributions; Bernoulli Processes; The Binomial Distribution: The Number of Successes as a Random Variable; The Poisson Distribution; Relating Discrete Probability to Normal Probability; Conclusion; CHAPTER 7 Computing Normal Probabilities; Characteristics of the Normal Distribution; Finding Normal Densities Using the dnorm Function; Converting a Normal Distribution to the Standard Normal Distribution; Finding Probabilities Using the pnorm Function; Finding a Left-tailed Probability
- Finding the Area Between Two z Scores
