LEADER 06323nam 22007695 450 001 9910300462103321 005 20220627135439.0 010 $a9781484201398 010 $a1484201396 024 7 $a10.1007/978-1-4842-0139-8 035 $a(CKB)3710000000199315 035 $a(EBL)1781997 035 $a(SSID)ssj0001298891 035 $a(PQKBManifestationID)11772879 035 $a(PQKBTitleCode)TC0001298891 035 $a(PQKBWorkID)11262280 035 $a(PQKB)10939725 035 $a(MiAaPQ)EBC1781997 035 $a(DE-He213)978-1-4842-0139-8 035 $a(CaSebORM)9781484201398 035 $a(PPN)179923048 035 $a(OCoLC)885593979 035 $a(OCoLC)ocn885593979 035 $a(EXLCZ)993710000000199315 100 $a20140704d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aUsing R for Statistics /$fby Sarah Baldock 205 $a1st ed. 2014. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2014. 215 $a1 online resource (232 p.) 225 1 $aThe expert's voice in R 300 $a"The Expert's Voice in R"--Cover. 300 $aIncludes index. 311 08$a9781322132587 311 08$a1322132585 311 08$a9781484201404 311 08$a148420140X 327 $aContents at a Glance; Introduction; Chapter 1: R Fundamentals; Downloading and Installing R; Getting Orientated; The R Console and Command Prompt; Functions; Objects; Simple Objects; Vectors; Data Frames; The Data Editor; Workspaces; Error Messages; Script Files; Summary; Chapter 2: Working with Data Files; Entering Data Directly; Importing Plain Text Files; CSV and Tab-Delimited Files; DIF Files; Other Plain Text Files; Importing Excel Files; Importing Files from Other Software; Using Relative File Paths; Exporting Datasets; Summary; Chapter 3: Preparing and Manipulating Your Data; Variables 327 $aRearranging and Removing VariablesRenaming Variables; Variable Classes; Calculating New Numeric Variables; Dividing a Continuous Variable into Categories; Working with Factor Variables; Manipulating Character Variables; Concatenating Character Strings; Extracting a Substring; Searching a Character Variable; Working with Dates and Times; Adding and Removing Observations; Adding New Observations; Removing Specific Observations; Removing Duplicate Observations; Selecting a Subset of the Data; Selecting a Subset According to Selection Criteria; Selecting a Random Sample from a Dataset 327 $aSorting a DatasetSummary; Chapter 4: Combining and Restructuring Datasets; Appending Rows; Appending Columns; Merging Datasets by Common Variables; Stacking and Unstacking a Dataset; Stacking Data; Unstacking Data; Reshaping a Dataset; Summary; Chapter 5: Summary Statistics for Continuous Variables; Univariate Statistics; Statistics by Group; Measures of Association; Covariance; Pearson's Correlation Coefficient; Spearman's Rank Correlation Coefficient; Hypothesis Test of Correlation; Comparing a Sample with a Specified Distribution; Shapiro-Wilk Test; Kolmogorov-Smirnov Test 327 $aConfidence Intervals and Prediction IntervalsSummary; Chapter 6: Tabular Data; Frequency Tables; Creating Tables; Displaying Tables; Creating Tables from Count Data; Creating a Table Directly; Chi-Square Goodness-of-Fit Test; Tests of Association Between Categorical Variables; Chi-Square Test of Association; Fisher's Exact Test; Proportions Test; Summary; Chapter 7: Probability Distributions; Probability Distributions in R; Probability Density Functions and Probability Mass Functions; Finding Probabilities; Finding Quantiles; Generating Random Numbers; Summary; Chapter 8: Creating Plots 327 $aSimple PlotsHistograms; Normal Probability Plots; Stem-and-Leaf Plots; Bar Charts; Pie Charts; Scatter Plots; Scatterplot Matrices; Box Plots; Plotting a Function; Exporting and Saving Plots; Summary; Chapter 9: Customizing Your Plots; Titles and Labels; Axes; Colors; Plotting Symbols; Plotting Lines; Shaded Areas; Adding Items to Plots; Adding Straight Lines; Adding a Mathematical Function Curve; Adding Labels and Text; Adding a Grid; Adding Arrows; Overlaying Plots; Adding a Legend; Multiple Plots in the Plotting Area; Changing the Default Plot Settings; Summary 327 $aChapter 10: Hypothesis Testing 330 $aUsing R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background. After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics. 606 $aBig data 606 $aSoftware engineering 606 $aR (Computer program language) 606 $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120 606 $aSoftware Engineering/Programming and Operating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14002 615 0$aBig data. 615 0$aSoftware engineering. 615 0$aR (Computer program language) 615 14$aBig Data. 615 24$aSoftware Engineering/Programming and Operating Systems. 676 $a570.1 676 $a570.1/5195 700 $aBaldock$b Sarah$4aut$4http://id.loc.gov/vocabulary/relators/aut$0943440 801 0$bUMI 801 1$bUMI 906 $aBOOK 912 $a9910300462103321 996 $aUsing R for Statistics$92129292 997 $aUNINA