Beginning R the statistical programming language
Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates...
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| Hlavný autor: | |
|---|---|
| Médium: | E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Newark
Wiley
2012
John Wiley & Sons, Incorporated Wrox |
| Vydanie: | 1st ed. |
| Edícia: | Wrox programmer to programmer |
| Predmet: | |
| ISBN: | 9781118226162, 9781118164303, 111816430X, 111822616X, 9781118239377, 1118239377 |
| On-line prístup: | Získať plný text |
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- Summary Statistics for Vectors -- Summary Commands With Single Value Results -- Summary Commands With Multiple Results -- Cumulative Statistics -- Simple Cumulative Commands -- Complex Cumulative Commands -- Summary Statistics for Data Frames -- Generic Summary Commands for Data Frames -- Special Row and Column Summary Commands -- The apply() Command for Summaries on Rows or Columns -- Summary Statistics for Matrix Objects -- Summary Statistics for Lists -- Summary Tables -- Making Contingency Tables -- Creating Contingency Tables from Vectors -- Creating Contingency Tables from Complicated Data -- Creating Custom Contingency Tables -- Creating Contingency Tables from Matrix Objects -- Selecting Parts of a Table Object -- Converting an Object into a Table -- Testing for Table Objects -- Complex (Flat) Tables -- Making "Flat" Contingency Tables -- Making Selective "Flat" Contingency Tables -- Testing "Flat" Table Objects -- Summary Commands for Tables -- Cross Tabulation -- Testing Cross-Table (xtabs) Objects -- A Better Class Test -- Recreating Original Data from a Contingency Table -- Switching Class -- Summary -- Chapter 5 Data: Distribution -- Looking at the Distribution of Data -- Stem and Leaf Plot -- Histograms -- Density Function -- Using the Density Function to Draw a Graph -- Adding Density Lines to Existing Graphs -- Types of Data Distribution -- The Normal Distribution -- Other Distributions -- Random Number Generation and Control -- Random Numbers and Sampling -- The Shapiro-Wilk Test for Normality -- The Kolmogorov-Smirnov Test -- Quantile-Quantile Plots -- A Basic Normal Quantile-Quantile Plot -- Adding a Straight Line to a QQ Plot -- Plotting the Distribution of One Sample Against Another -- Summary -- Chapter 6 Simple Hypothesis Testing -- Using the Student's t-test -- Two-Sample t-Test with Unequal Variance
- Graphical Summary of Post-hoc Testing -- Extracting Means and Summary Statistics -- Model Tables -- Table Commands -- Interaction Plots -- More Complex ANOVA Models -- Other Options for aov() -- Replications and Balance -- Summary -- Chapter 9 Manipulating Data and Extracting Components -- Creating Data for Complex Analysis -- Data Frames -- Matrix Objects -- Creating and Setting Factor Data -- Making Replicate Treatment Factors -- Adding Rows or Columns -- Summarizing Data -- Simple Column and Row Summaries -- Complex Summary Functions -- The rowsum() Command -- The apply() Command -- Using tapply() to Summarize Using a Grouping Variable -- The aggregate() Command -- Summary -- Chapter 10 Regression (Linear Modeling) -- Simple Linear Regression -- Linear Model Results Objects -- Coefficients -- Fitted Values -- Residuals -- Formula -- Best-Fit Line -- Similarity between lm() and aov() -- Multiple Regression -- Formulae and Linear Models -- Model Building -- Adding Terms with Forward Stepwise Regression -- Removing Terms with Backwards Deletion -- Comparing Models -- Curvilinear Regression -- Logarithmic Regression -- Polynomial Regression -- Plotting Linear Models and Curve Fitting -- Best-Fit Lines -- Adding Line of Best-Fit with abline() -- Calculating Lines with fitted() -- Producing Smooth Curves using spline() -- Confidence Intervals on Fitted Lines -- Summarizing Regression Models -- Diagnostic Plots -- Summary of Fit -- Summary -- Chapter 11 More About Graphs -- Adding Elements to Existing Plots -- Error Bars -- Using the segments() Command for Error Bars -- Using the arrows() Command to Add Error Bars -- Adding Legends to Graphs -- Color Palettes -- Placing a Legend on an Existing Plot -- Adding Text to Graphs -- Making Superscript and Subscript Axis Titles -- Orienting the Axis Labels -- Making Extra Space in the Margin for Labels
- Cover -- Title Page -- Copyright -- Contents -- Introduction -- Chapter 1 Introducing R: What It Is and How to Get It -- Getting the Hang of R -- The R Website -- Downloading and Installing R from CRAN -- Installing R on Your Windows Computer -- Installing R on Your Macintosh Computer -- Installing R on Your Linux Computer -- Running the R Program -- Finding Your Way with R -- Getting Help via the CRAN Website and the Internet -- The Help Command in R -- Help for Windows Users -- Help for Macintosh Users -- Help for Linux Users -- Help For All Users -- Anatomy of a Help Item in R -- Command Packages -- Standard Command Packages -- What Extra Packages Can Do for You -- How to Get Extra Packages of R Commands -- How to Install Extra Packages for Windows Users -- How to Install Extra Packages for Macintosh Users -- How to Install Extra Packages for Linux Users -- Running and Manipulating Packages -- Loading Packages -- Windows-Specific Package Commands -- Macintosh-Specific Package Commands -- Removing or Unloading Packages -- Summary -- Chapter 2 Starting Out: Becoming Familiar with R -- Some Simple Math -- Use R Like a Calculator -- Storing the Results of Calculations -- Reading and Getting Data into R -- Using the combine Command for Making Data -- Entering Numerical Items as Data -- Entering Text Items as Data -- Using the scan Command for Making Data -- Entering Text as Data -- Using the Clipboard to Make Data -- Reading a File of Data from a Disk -- Reading Bigger Data Files -- The read.csv() Command -- Alternative Commands for Reading Data in R -- Missing Values in Data Files -- Viewing Named Objects -- Viewing Previously Loaded Named-Objects -- Viewing All Objects -- Viewing Only Matching Names -- Removing Objects from R -- Types of Data Items -- Number Data -- Text Items -- Converting Between Number and Text Data
- The Structure of Data Items -- Vector Items -- Data Frames -- Matrix Objects -- List Objects -- Examining Data Structure -- Working with History Commands -- Using History Files -- Viewing the Previous Command History -- Saving and Recalling Lists of Commands -- Alternative History Commands in Macintosh OS -- Editing History Files -- Saving Your Work in R -- Saving the Workspace on Exit -- Saving Data Files to Disk -- Save Named Objects -- Save Everything -- Reading Data Files from Disk -- Saving Data to Disk as Text Files -- Writing Vector Objects to Disk -- Writing Matrix and Data Frame Objects to Disk -- Writing List Objects to Disk -- Converting List Objects to Data Frames -- Summary -- Chapter 3 Starting Out: Working With Objects -- Manipulating Objects -- Manipulating Vectors -- Selecting and Displaying Parts of a Vector -- Sorting and Rearranging a Vector -- Returning Logical Values from a Vector -- Manipulating Matrix and Data Frames -- Selecting and Displaying Parts of a Matrix or Data Frame -- Sorting and Rearranging a Matrix or Data Frame -- Manipulating Lists -- Viewing Objects within Objects -- Looking Inside Complicated Data Objects -- Opening Complicated Data Objects -- Quick Looks at Complicated Data Objects -- Viewing and Setting Names -- Rotating Data Tables -- Constructing Data Objects -- Making Lists -- Making Data Frames -- Making Matrix Objects -- Re-ordering Data Frames and Matrix Objects -- Forms of Data Objects: Testing and Converting -- Testing to See What Type of Object You Have -- Converting from One Object Form to Another -- Convert a Matrix to a Data Frame -- Convert a Data Frame into a Matrix -- Convert a Data Frame into a List -- Convert a Matrix into a List -- Convert a List to Something Else -- Summary -- Chapter 4 Data: Descriptive Statistics and Tabulation -- Summary Commands -- Summarizing Samples
- Two-Sample t-Test with Equal Variance -- One-Sample t-Testing -- Using Directional Hypotheses -- Formula Syntax and Subsetting Samples in the t-Test -- The Wilcoxon U-Test (Mann-Whitney) -- Two-Sample U-Test -- One-Sample U-Test -- Using Directional Hypotheses -- Formula Syntax and Subsetting Samples in the U-test -- Paired t- and U-Tests -- Correlation and Covariance -- Simple Correlation -- Covariance -- Significance Testing in Correlation Tests -- Formula Syntax -- Tests for Association -- Multiple Categories: Chi-Squared Tests -- Monte Carlo Simulation -- Yates' Correction for 2 x 2 Tables -- Single Category: Goodness of Fit Tests -- Summary -- Chapter 7 Introduction to Graphical Analysis -- Box-whisker Plots -- Basic Boxplots -- Customizing Boxplots -- Horizontal Boxplots -- Scatter Plots -- Basic Scatter Plots -- Adding Axis Labels -- Plotting Symbols -- Setting Axis Limits -- Using Formula Syntax -- Adding Lines of Best-Fit to Scatter Plots -- Pairs Plots (Multiple Correlation Plots) -- Line Charts -- Line Charts Using Numeric Data -- Line Charts Using Categorical Data -- Pie Charts -- Cleveland Dot Charts -- Bar Charts -- Single-Category Bar Charts -- Multiple Category Bar Charts -- Stacked Bar Charts -- Grouped Bar Charts -- Horizontal Bars -- Bar Charts from Summary Data -- Copy Graphics to Other Applications -- Use Copy/Paste to Copy Graphs -- Save a Graphic to Disk -- Windows -- Macintosh -- Linux -- Summary -- Chapter 8 Formula Notation and Complex Statistics -- Examples of Using Formula Syntax for Basic Tests -- Formula Notation in Graphics -- Analysis of Variance (ANOVA) -- One-Way ANOVA -- Stacking the Data before Running Analysis of Variance -- Running aov() Commands -- Simple Post-hoc Testing -- Extracting Means from aov() Models -- Two-Way ANOVA -- More about Post-hoc Testing -- Graphical Summary of ANOVA