{"product_id":"beginning-r-the-statistical-programming-language-paperback-softback-9781118164303","title":"Beginning R; The Statistical Programming Language (Paperback \/ softback) 9781118164303","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eBeginning R\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eThe Statistical Programming Language\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eMark Gardener (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781118164303, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePaperback \/ softback, published 1 June 2012\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e504 pages\u003cbr\u003e23.4 x 18.8 x 2.8 cm, 0.885 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eGain better insight into your data using the power of R\u003c\/p\u003e \u003cp\u003eWhile R is very flexible and powerful, it is unlike most of the computer programs you have used. In order to unlock its full potential, this book delves into the language, making it accessible so you can tackle even the most complex of data analysis tasks. Simple data examples are integrated throughout so you can explore the capabilities and versatility of R. Along the way, you'll also learn how to carry out a range of commonly used statistical methods, including Analysis of Variance and Linear Regression. By the end, you'll be able to effectively and efficiently analyze your data and present the results.\u003c\/p\u003e \u003cp\u003eBeginning R:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDiscusses how to implement some basic statistical methods such as the t-test, correlation, and tests of association\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eExplains how to turn your graphs from merely adequate to simply stunning\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eProvides you with the ability to define complex analytical situations\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eDemonstrates ways to make and rearrange your data for easier analysis\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eCovers how to carry out basic regression as well as complex model building and curvilinear regression\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eShows how to produce customized functions and simple scripts that can automate your workflow\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ewrox.com\u003c\/p\u003e \u003cp\u003eProgrammer Forums\u003c\/p\u003e \u003cp\u003eJoin our Programmer to Programmer forums to ask and answer programming questions about this book, join discussions on the hottest topics in the industry, and connect with fellow programmers from around the world.\u003c\/p\u003e \u003cp\u003eCode Downloads\u003c\/p\u003e \u003cp\u003eTake advantage of free code samples from this book, as well as code samples from hundreds of other books, all ready to use.\u003c\/p\u003e \u003cp\u003eRead More\u003c\/p\u003e \u003cp\u003eFind articles, ebooks, sample chapters and tables of contents for hundreds of books, and more reference resources on programming topics that matter to you.\u003c\/p\u003e \u003cp\u003eWrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that guides you through all the techniques involved.\u003c\/p\u003e \u003cp\u003eVisit the Beginning R website at www.wrox.com\/go\/beginningr\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eIntroduction xxi  \u003cp\u003e\u003cb\u003eChapter 1: Introducing R: What It Is and How to Get It 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eGetting the Hang of R 2\u003c\/p\u003e \u003cp\u003eThe R Website 3\u003c\/p\u003e \u003cp\u003eDownloading and Installing R from CRAN 3\u003c\/p\u003e \u003cp\u003eInstalling R on Your Windows Computer 4\u003c\/p\u003e \u003cp\u003eInstalling R on Your Macintosh Computer 7\u003c\/p\u003e \u003cp\u003eInstalling R on Your Linux Computer 7\u003c\/p\u003e \u003cp\u003eRunning the R Program 8\u003c\/p\u003e \u003cp\u003eFinding Your Way with R 10\u003c\/p\u003e \u003cp\u003eGetting Help via the CRAN Website and the Internet 10\u003c\/p\u003e \u003cp\u003eThe Help Command in R 10\u003c\/p\u003e \u003cp\u003eHelp for Windows Users 11\u003c\/p\u003e \u003cp\u003eHelp for Macintosh Users 11\u003c\/p\u003e \u003cp\u003eHelp for Linux Users 13\u003c\/p\u003e \u003cp\u003eHelp For All Users 13\u003c\/p\u003e \u003cp\u003eAnatomy of a Help Item in R 14\u003c\/p\u003e \u003cp\u003eCommand Packages 16\u003c\/p\u003e \u003cp\u003eStandard Command Packages 16\u003c\/p\u003e \u003cp\u003eWhat Extra Packages Can Do for You 16\u003c\/p\u003e \u003cp\u003eHow to Get Extra Packages of R Commands 18\u003c\/p\u003e \u003cp\u003eHow to Install Extra Packages for Windows Users 18\u003c\/p\u003e \u003cp\u003eHow to Install Extra Packages for Macintosh Users 18\u003c\/p\u003e \u003cp\u003eHow to Install Extra Packages for Linux Users 19\u003c\/p\u003e \u003cp\u003eRunning and Manipulating Packages 20\u003c\/p\u003e \u003cp\u003eLoading Packages 21\u003c\/p\u003e \u003cp\u003eWindows-Specific Package Commands 21\u003c\/p\u003e \u003cp\u003eMacintosh-Specific Package Commands 21\u003c\/p\u003e \u003cp\u003eRemoving or Unloading Packages 22\u003c\/p\u003e \u003cp\u003eSummary 22\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2: Starting Out: Becoming Familiar with R 25\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSome Simple Math 26\u003c\/p\u003e \u003cp\u003eUse R Like a Calculator 26\u003c\/p\u003e \u003cp\u003eStoring the Results of Calculations 29\u003c\/p\u003e \u003cp\u003eReading and Getting Data into R 30\u003c\/p\u003e \u003cp\u003eUsing the combine Command for Making Data 30\u003c\/p\u003e \u003cp\u003eEntering Numerical Items as Data 30\u003c\/p\u003e \u003cp\u003eEntering Text Items as Data 31\u003c\/p\u003e \u003cp\u003eUsing the scan Command for Making Data 32\u003c\/p\u003e \u003cp\u003eEntering Text as Data 33\u003c\/p\u003e \u003cp\u003eUsing the Clipboard to Make Data 33\u003c\/p\u003e \u003cp\u003eReading a File of Data from a Disk 35\u003c\/p\u003e \u003cp\u003eReading Bigger Data Files 37\u003c\/p\u003e \u003cp\u003eThe read.csv() Command 37\u003c\/p\u003e \u003cp\u003eAlternative Commands for Reading Data in R 39\u003c\/p\u003e \u003cp\u003eMissing Values in Data Files 40\u003c\/p\u003e \u003cp\u003eViewing Named Objects 41\u003c\/p\u003e \u003cp\u003eViewing Previously Loaded Named-Objects 42\u003c\/p\u003e \u003cp\u003eViewing All Objects 42\u003c\/p\u003e \u003cp\u003eViewing Only Matching Names 42\u003c\/p\u003e \u003cp\u003eRemoving Objects from R 44\u003c\/p\u003e \u003cp\u003eTypes of Data Items 45\u003c\/p\u003e \u003cp\u003eNumber Data 45\u003c\/p\u003e \u003cp\u003eText Items 45\u003c\/p\u003e \u003cp\u003eConverting Between Number and Text Data 46\u003c\/p\u003e \u003cp\u003eThe Structure of Data Items 47\u003c\/p\u003e \u003cp\u003eVector Items 48\u003c\/p\u003e \u003cp\u003eData Frames 48\u003c\/p\u003e \u003cp\u003eMatrix Objects 49\u003c\/p\u003e \u003cp\u003eList Objects 49\u003c\/p\u003e \u003cp\u003eExamining Data Structure 49\u003c\/p\u003e \u003cp\u003eWorking with History Commands 51\u003c\/p\u003e \u003cp\u003eUsing History Files 52\u003c\/p\u003e \u003cp\u003eViewing the Previous Command History 52\u003c\/p\u003e \u003cp\u003eSaving and Recalling Lists of Commands 52\u003c\/p\u003e \u003cp\u003eAlternative History Commands in Macintosh OS 52\u003c\/p\u003e \u003cp\u003eEditing History Files 53\u003c\/p\u003e \u003cp\u003eSaving Your Work in R 54\u003c\/p\u003e \u003cp\u003eSaving the Workspace on Exit 54\u003c\/p\u003e \u003cp\u003eSaving Data Files to Disk 54\u003c\/p\u003e \u003cp\u003eSave Named Objects 54\u003c\/p\u003e \u003cp\u003eSave Everything 55\u003c\/p\u003e \u003cp\u003eReading Data Files from Disk 56\u003c\/p\u003e \u003cp\u003eSaving Data to Disk as Text Files 57\u003c\/p\u003e \u003cp\u003eWriting Vector Objects to Disk 58\u003c\/p\u003e \u003cp\u003eWriting Matrix and Data Frame Objects to Disk 58\u003c\/p\u003e \u003cp\u003eWriting List Objects to Disk 59\u003c\/p\u003e \u003cp\u003eConverting List Objects to Data Frames 60\u003c\/p\u003e \u003cp\u003eSummary 61\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3: Starting Out: Working With Objects 65\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eManipulating Objects 65\u003c\/p\u003e \u003cp\u003eManipulating Vectors 66\u003c\/p\u003e \u003cp\u003eSelecting and Displaying Parts of a Vector 66\u003c\/p\u003e \u003cp\u003eSorting and Rearranging a Vector 68\u003c\/p\u003e \u003cp\u003eReturning Logical Values from a Vector 70\u003c\/p\u003e \u003cp\u003eManipulating Matrix and Data Frames 70\u003c\/p\u003e \u003cp\u003eSelecting and Displaying Parts of a Matrix or Data Frame 71\u003c\/p\u003e \u003cp\u003eSorting and Rearranging a Matrix or Data Frame 74\u003c\/p\u003e \u003cp\u003eManipulating Lists 76\u003c\/p\u003e \u003cp\u003eViewing Objects within Objects 77\u003c\/p\u003e \u003cp\u003eLooking Inside Complicated Data Objects 77\u003c\/p\u003e \u003cp\u003eOpening Complicated Data Objects 78\u003c\/p\u003e \u003cp\u003eQuick Looks at Complicated Data Objects 80\u003c\/p\u003e \u003cp\u003eViewing and Setting Names 82\u003c\/p\u003e \u003cp\u003eRotating Data Tables 86\u003c\/p\u003e \u003cp\u003eConstructing Data Objects 86\u003c\/p\u003e \u003cp\u003eMaking Lists 87\u003c\/p\u003e \u003cp\u003eMaking Data Frames 88\u003c\/p\u003e \u003cp\u003eMaking Matrix Objects 89\u003c\/p\u003e \u003cp\u003eRe-ordering Data Frames and Matrix Objects 92\u003c\/p\u003e \u003cp\u003eForms of Data Objects: Testing and Converting 96\u003c\/p\u003e \u003cp\u003eTesting to See What Type of Object You Have 96\u003c\/p\u003e \u003cp\u003eConverting from One Object Form to Another 97\u003c\/p\u003e \u003cp\u003eConvert a Matrix to a Data Frame 97\u003c\/p\u003e \u003cp\u003eConvert a Data Frame into a Matrix 98\u003c\/p\u003e \u003cp\u003eConvert a Data Frame into a List 99\u003c\/p\u003e \u003cp\u003eConvert a Matrix into a List 100\u003c\/p\u003e \u003cp\u003eConvert a List to Something Else 100\u003c\/p\u003e \u003cp\u003eSummary 104\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4: Data: Descriptive Statistics and Tabulation 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSummary Commands 108\u003c\/p\u003e \u003cp\u003eSummarizing Samples 110\u003c\/p\u003e \u003cp\u003eSummary Statistics for Vectors 110\u003c\/p\u003e \u003cp\u003eSummary Commands With Single Value Results 110\u003c\/p\u003e \u003cp\u003eSummary Commands With Multiple Results 113\u003c\/p\u003e \u003cp\u003eCumulative Statistics 115\u003c\/p\u003e \u003cp\u003eSimple Cumulative Commands 115\u003c\/p\u003e \u003cp\u003eComplex Cumulative Commands 117\u003c\/p\u003e \u003cp\u003eSummary Statistics for Data Frames 118\u003c\/p\u003e \u003cp\u003eGeneric Summary Commands for Data Frames 119\u003c\/p\u003e \u003cp\u003eSpecial Row and Column Summary Commands 119\u003c\/p\u003e \u003cp\u003eThe apply() Command for Summaries on Rows or Columns 120\u003c\/p\u003e \u003cp\u003eSummary Statistics for Matrix Objects 120\u003c\/p\u003e \u003cp\u003eSummary Statistics for Lists 121\u003c\/p\u003e \u003cp\u003eSummary Tables 122\u003c\/p\u003e \u003cp\u003eMaking Contingency Tables 123\u003c\/p\u003e \u003cp\u003eCreating Contingency Tables from Vectors 123\u003c\/p\u003e \u003cp\u003eCreating Contingency Tables from Complicated Data 123\u003c\/p\u003e \u003cp\u003eCreating Custom Contingency Tables 126\u003c\/p\u003e \u003cp\u003eCreating Contingency Tables from Matrix Objects 128\u003c\/p\u003e \u003cp\u003eSelecting Parts of a Table Object 130\u003c\/p\u003e \u003cp\u003eConverting an Object into a Table 132\u003c\/p\u003e \u003cp\u003eTesting for Table Objects 133\u003c\/p\u003e \u003cp\u003eComplex (Flat) Tables 134\u003c\/p\u003e \u003cp\u003eMaking “Flat” Contingency Tables 134\u003c\/p\u003e \u003cp\u003eMaking Selective “Flat” Contingency Tables 138\u003c\/p\u003e \u003cp\u003eTesting “Flat” Table Objects 139\u003c\/p\u003e \u003cp\u003eSummary Commands for Tables 139\u003c\/p\u003e \u003cp\u003eCross Tabulation 142\u003c\/p\u003e \u003cp\u003eTesting Cross-Table (xtabs) Objects 144\u003c\/p\u003e \u003cp\u003eA Better Class Test 144\u003c\/p\u003e \u003cp\u003eRecreating Original Data from a Contingency Table 145\u003c\/p\u003e \u003cp\u003eSwitching Class 146\u003c\/p\u003e \u003cp\u003eSummary 147\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5: Data: Distrib ution 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eLooking at the Distribution of Data 151\u003c\/p\u003e \u003cp\u003eStem and Leaf Plot 152\u003c\/p\u003e \u003cp\u003eHistograms 154\u003c\/p\u003e \u003cp\u003eDensity Function 158\u003c\/p\u003e \u003cp\u003eUsing the Density Function to Draw a Graph 159\u003c\/p\u003e \u003cp\u003eAdding Density Lines to Existing Graphs 160\u003c\/p\u003e \u003cp\u003eTypes of Data Distribution 161\u003c\/p\u003e \u003cp\u003eThe Normal Distribution 161\u003c\/p\u003e \u003cp\u003eOther Distributions 164\u003c\/p\u003e \u003cp\u003eRandom Number Generation and Control 166\u003c\/p\u003e \u003cp\u003eRandom Numbers and Sampling 168\u003c\/p\u003e \u003cp\u003eThe Shapiro-Wilk Test for Normality 171\u003c\/p\u003e \u003cp\u003eThe Kolmogorov-Smirnov Test 172\u003c\/p\u003e \u003cp\u003eQuantile-Quantile Plots 174\u003c\/p\u003e \u003cp\u003eA Basic Normal Quantile-Quantile Plot 174\u003c\/p\u003e \u003cp\u003eAdding a Straight Line to a QQ Plot 174\u003c\/p\u003e \u003cp\u003ePlotting the Distribution of One Sample Against Another 175\u003c\/p\u003e \u003cp\u003eSummary 177\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6: Si mple Hypothesis Testing 181\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eUsing the Student’s t-test 181\u003c\/p\u003e \u003cp\u003eTwo-Sample t-Test with Unequal Variance 182\u003c\/p\u003e \u003cp\u003eTwo-Sample t-Test with Equal Variance 183\u003c\/p\u003e \u003cp\u003eOne-Sample t-Testing 183\u003c\/p\u003e \u003cp\u003eUsing Directional Hypotheses 183\u003c\/p\u003e \u003cp\u003eFormula Syntax and Subsetting Samples in the t-Test 184\u003c\/p\u003e \u003cp\u003eThe Wilcoxon U-Test (Mann-Whitney) 188\u003c\/p\u003e \u003cp\u003eTwo-Sample U-Test 189\u003c\/p\u003e \u003cp\u003eOne-Sample U-Test 189\u003c\/p\u003e \u003cp\u003eUsing Directional Hypotheses 189\u003c\/p\u003e \u003cp\u003eFormula Syntax and Subsetting Samples in the U-test 190\u003c\/p\u003e \u003cp\u003ePaired t- and U-Tests 193\u003c\/p\u003e \u003cp\u003eCorrelation and Covariance 196\u003c\/p\u003e \u003cp\u003eSimple Correlation 197\u003c\/p\u003e \u003cp\u003eCovariance 199\u003c\/p\u003e \u003cp\u003eSignificance Testing in Correlation Tests 199\u003c\/p\u003e \u003cp\u003eFormula Syntax 200\u003c\/p\u003e \u003cp\u003eTests for Association 203\u003c\/p\u003e \u003cp\u003eMultiple Categories: Chi-Squared Tests 204\u003c\/p\u003e \u003cp\u003eMonte Carlo Simulation 205\u003c\/p\u003e \u003cp\u003eYates’ Correction for 2 n 2 Tables 206\u003c\/p\u003e \u003cp\u003eSingle Category: Goodness of Fit Tests 206\u003c\/p\u003e \u003cp\u003eSummary 210\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7: Introduction to Graphical Analysis 215\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBox-whisker Plots 215\u003c\/p\u003e \u003cp\u003eBasic Boxplots 216\u003c\/p\u003e \u003cp\u003eCustomizing Boxplots 217\u003c\/p\u003e \u003cp\u003eHorizontal Boxplots 218\u003c\/p\u003e \u003cp\u003eScatter Plots 222\u003c\/p\u003e \u003cp\u003eBasic Scatter Plots 222\u003c\/p\u003e \u003cp\u003eAdding Axis Labels 223\u003c\/p\u003e \u003cp\u003ePlotting Symbols 223\u003c\/p\u003e \u003cp\u003eSetting Axis Limits 224\u003c\/p\u003e \u003cp\u003eUsing Formula Syntax 225\u003c\/p\u003e \u003cp\u003eAdding Lines of Best-Fit to Scatter Plots 225\u003c\/p\u003e \u003cp\u003ePairs Plots (Multiple Correlation Plots) 229\u003c\/p\u003e \u003cp\u003eLine Charts 232\u003c\/p\u003e \u003cp\u003eLine Charts Using Numeric Data 232\u003c\/p\u003e \u003cp\u003eLine Charts Using Categorical Data 233\u003c\/p\u003e \u003cp\u003ePie Charts 236\u003c\/p\u003e \u003cp\u003eCleveland Dot Charts 239\u003c\/p\u003e \u003cp\u003eBar Charts 245\u003c\/p\u003e \u003cp\u003eSingle-Category Bar Charts 245\u003c\/p\u003e \u003cp\u003eMultiple Category Bar Charts 250\u003c\/p\u003e \u003cp\u003eStacked Bar Charts 250\u003c\/p\u003e \u003cp\u003eGrouped Bar Charts 250\u003c\/p\u003e \u003cp\u003eHorizontal Bars 253\u003c\/p\u003e \u003cp\u003eBar Charts from Summary Data 253\u003c\/p\u003e \u003cp\u003eCopy Graphics to Other Applications 256\u003c\/p\u003e \u003cp\u003eUse Copy\/Paste to Copy Graphs 257\u003c\/p\u003e \u003cp\u003eSave a Graphic to Disk 257\u003c\/p\u003e \u003cp\u003eWindows 257\u003c\/p\u003e \u003cp\u003eMacintosh 258\u003c\/p\u003e \u003cp\u003eLinux 258\u003c\/p\u003e \u003cp\u003eSummary 259\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8: Formula Notation and Complex Statistic s 263\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExamples of Using Formula Syntax for Basic Tests 264\u003c\/p\u003e \u003cp\u003eFormula Notation in Graphics 266\u003c\/p\u003e \u003cp\u003eAnalysis of Variance (ANOVA) 268\u003c\/p\u003e \u003cp\u003eOne-Way ANOVA 268\u003c\/p\u003e \u003cp\u003eStacking the Data before Running Analysis of Variance 269\u003c\/p\u003e \u003cp\u003eRunning aov() Commands 270\u003c\/p\u003e \u003cp\u003eSimple Post-hoc Testing 271\u003c\/p\u003e \u003cp\u003eExtracting Means from aov() Models 271\u003c\/p\u003e \u003cp\u003eTwo-Way ANOVA 273\u003c\/p\u003e \u003cp\u003eMore about Post-hoc Testing 275\u003c\/p\u003e \u003cp\u003eGraphical Summary of ANOVA 277\u003c\/p\u003e \u003cp\u003eGraphical Summary of Post-hoc Testing 278\u003c\/p\u003e \u003cp\u003eExtracting Means and Summary Statistics 281\u003c\/p\u003e \u003cp\u003eModel Tables 281\u003c\/p\u003e \u003cp\u003eTable Commands 283\u003c\/p\u003e \u003cp\u003eInteraction Plots 283\u003c\/p\u003e \u003cp\u003eMore Complex ANOVA Models 289\u003c\/p\u003e \u003cp\u003eOther Options for aov() 290\u003c\/p\u003e \u003cp\u003eReplications and Balance 290\u003c\/p\u003e \u003cp\u003eSummary 292\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9: Manipulating Data and Extracting Components 295\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCreating Data for Complex Analysis 295\u003c\/p\u003e \u003cp\u003eData Frames 296\u003c\/p\u003e \u003cp\u003eMatrix Objects 299\u003c\/p\u003e \u003cp\u003eCreating and Setting Factor Data 300\u003c\/p\u003e \u003cp\u003eMaking Replicate Treatment Factors 304\u003c\/p\u003e \u003cp\u003eAdding Rows or Columns 306\u003c\/p\u003e \u003cp\u003eSummarizing Data 312\u003c\/p\u003e \u003cp\u003eSimple Column and Row Summaries 312\u003c\/p\u003e \u003cp\u003eComplex Summary Functions 313\u003c\/p\u003e \u003cp\u003eThe rowsum() Command 314\u003c\/p\u003e \u003cp\u003eThe apply() Command 315\u003c\/p\u003e \u003cp\u003eUsing tapply() to Summarize Using a Grouping Variable 316\u003c\/p\u003e \u003cp\u003eThe aggregate() Command 319\u003c\/p\u003e \u003cp\u003eSummary 323\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10: Regression (Li near Modeling) 327\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSimple Linear Regression 328\u003c\/p\u003e \u003cp\u003eLinear Model Results Objects 329\u003c\/p\u003e \u003cp\u003eCoefficients 330\u003c\/p\u003e \u003cp\u003eFitted Values 330\u003c\/p\u003e \u003cp\u003eResiduals 330\u003c\/p\u003e \u003cp\u003eFormula 331\u003c\/p\u003e \u003cp\u003eBest-Fit Line 331\u003c\/p\u003e \u003cp\u003eSimilarity between lm() and aov() 334\u003c\/p\u003e \u003cp\u003eMultiple Regression 335\u003c\/p\u003e \u003cp\u003eFormulae and Linear Models 335\u003c\/p\u003e \u003cp\u003eModel Building 337\u003c\/p\u003e \u003cp\u003eAdding Terms with Forward Stepwise Regression 337\u003c\/p\u003e \u003cp\u003eRemoving Terms with Backwards Deletion 339\u003c\/p\u003e \u003cp\u003eComparing Models 341\u003c\/p\u003e \u003cp\u003eCurvilinear Regression 343\u003c\/p\u003e \u003cp\u003eLogarithmic Regression 344\u003c\/p\u003e \u003cp\u003ePolynomial Regression 345\u003c\/p\u003e \u003cp\u003ePlotting Linear Models and Curve Fitting 347\u003c\/p\u003e \u003cp\u003eBest-Fit Lines 348\u003c\/p\u003e \u003cp\u003eAdding Line of Best-Fit with abline() 348\u003c\/p\u003e \u003cp\u003eCalculating Lines with fitted() 348\u003c\/p\u003e \u003cp\u003eProducing Smooth Curves using spline() 350\u003c\/p\u003e \u003cp\u003eConfidence Intervals on Fitted Lines 351\u003c\/p\u003e \u003cp\u003eSummarizing Regression Models 356\u003c\/p\u003e \u003cp\u003eDiagnostic Plots 356\u003c\/p\u003e \u003cp\u003eSummary of Fit 357\u003c\/p\u003e \u003cp\u003eSummary 359\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11: More About Graphs 363\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAdding Elements to Existing Plots 364\u003c\/p\u003e \u003cp\u003eError Bars 364\u003c\/p\u003e \u003cp\u003eUsing the segments() Command for Error Bars 364\u003c\/p\u003e \u003cp\u003eUsing the arrows() Command to Add Error Bars 368\u003c\/p\u003e \u003cp\u003eAdding Legends to Graphs 368\u003c\/p\u003e \u003cp\u003eColor Palettes 370\u003c\/p\u003e \u003cp\u003ePlacing a Legend on an Existing Plot 371\u003c\/p\u003e \u003cp\u003eAdding Text to Graphs 372\u003c\/p\u003e \u003cp\u003eMaking Superscript and Subscript Axis Titles 373\u003c\/p\u003e \u003cp\u003eOrienting the Axis Labels 375\u003c\/p\u003e \u003cp\u003eMaking Extra Space in the Margin for Labels 375\u003c\/p\u003e \u003cp\u003eSetting Text and Label Sizes 375\u003c\/p\u003e \u003cp\u003eAdding Text to the Plot Area 376\u003c\/p\u003e \u003cp\u003eAdding Text in the Plot Margins 378\u003c\/p\u003e \u003cp\u003eCreating Mathematical Expressions 379\u003c\/p\u003e \u003cp\u003eAdding Points to an Existing Graph 382\u003c\/p\u003e \u003cp\u003eAdding Various Sorts of Lines to Graphs 386\u003c\/p\u003e \u003cp\u003eAdding Straight Lines as Gridlines or Best-Fit Lines 386\u003c\/p\u003e \u003cp\u003eMaking Curved Lines to Add to Graphs 388\u003c\/p\u003e \u003cp\u003ePlotting Mathematical Expressions 390\u003c\/p\u003e \u003cp\u003eAdding Short Segments of Lines to an Existing Plot 393\u003c\/p\u003e \u003cp\u003eAdding Arrows to an Existing Graph 394\u003c\/p\u003e \u003cp\u003eMatrix Plots (Multiple Series on One Graph) 396\u003c\/p\u003e \u003cp\u003eMultiple Plots in One Window 399\u003c\/p\u003e \u003cp\u003eSplitting the Plot Window into Equal Sections 399\u003c\/p\u003e \u003cp\u003eSplitting the Plot Window into Unequal Sections 402\u003c\/p\u003e \u003cp\u003eExporting Graphs 405\u003c\/p\u003e \u003cp\u003eUsing Copy and Paste to Move a Graph 406\u003c\/p\u003e \u003cp\u003eSaving a Graph to a File 406\u003c\/p\u003e \u003cp\u003eWindows 406\u003c\/p\u003e \u003cp\u003eMacintosh 406\u003c\/p\u003e \u003cp\u003eLinux 406\u003c\/p\u003e \u003cp\u003eUsing the Device Driver to Save a Graph to Disk 407\u003c\/p\u003e \u003cp\u003ePNG Device Driver 407\u003c\/p\u003e \u003cp\u003ePDF Device Driver 407\u003c\/p\u003e \u003cp\u003eCopying a Graph from Screen to Disk File 408\u003c\/p\u003e \u003cp\u003eMaking a New Graph Directly to a Disk File 408\u003c\/p\u003e \u003cp\u003eSummary 410\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12: Writing Your Own Scripts: Beginning to Program 415\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCopy and Paste Scripts 416\u003c\/p\u003e \u003cp\u003eMake Your Own Help File as Plaintext 416\u003c\/p\u003e \u003cp\u003eUsing Annotations with the # Character 417\u003c\/p\u003e \u003cp\u003eCreating Simple Functions 417\u003c\/p\u003e \u003cp\u003eOne-Line Functions 417\u003c\/p\u003e \u003cp\u003eUsing Default Values in Functions 418\u003c\/p\u003e \u003cp\u003eSimple Customized Functions with Multiple Lines 419\u003c\/p\u003e \u003cp\u003eStoring Customized Functions 420\u003c\/p\u003e \u003cp\u003eMaking Source Code 421\u003c\/p\u003e \u003cp\u003eDisplaying the Results of Customized Functions and Scripts 421\u003c\/p\u003e \u003cp\u003eDisplaying Messages as Part of Script Output 422\u003c\/p\u003e \u003cp\u003eSimple Screen Text 422\u003c\/p\u003e \u003cp\u003eDisplay a Message and Wait for User Intervention 424\u003c\/p\u003e \u003cp\u003eSummary 428\u003c\/p\u003e \u003cp\u003eAppendix: Answers to Exerci ses 433\u003c\/p\u003e \u003cp\u003eIndex 461\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer programming \/ software development [\u003ca title=\"See our other books on Computer programming \/ software development\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20programming%20\/%20software%20development%20%5BUM%5D%22\"\u003eUM\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wrox","offers":[{"title":"Brand New","offer_id":52475056226584,"sku":"9781118164303","price":19.29,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781118164303.jpg?v=1785803738","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/beginning-r-the-statistical-programming-language-paperback-softback-9781118164303","provider":"Freshly Printed Books","version":"1.0","type":"link"}