03727nam 22006015 450 991042704880332120230804154213.01-4842-6053-810.1007/978-1-4842-6053-1(CKB)4100000011513197(DE-He213)978-1-4842-6053-1(MiAaPQ)EBC6381185(CaSebORM)9781484260531(PPN)26151735X(EXLCZ)99410000001151319720201017d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierBeginning R 4 From Beginner to Pro /by Matt Wiley, Joshua F. Wiley1st ed. 2020.Berkeley, CA :Apress :Imprint: Apress,2020.1 online resource (XX, 467 p. 110 illus., 66 illus. in color.) 1-4842-6052-X Includes bibliographical references and index.1: Installing R -- 2: Installing Packages and Using Libraries -- 3: Data Input and Output -- 4: Working with Data -- 5: Data and Samples -- 6: Descriptive Statistics -- 7: Understanding Probability and Distribution -- 8: Correlation and Regression -- 9: Confidence Intervals -- 10: Hypothesis Testing -- 11: Multiple Regression -- 12: Moderated Regression -- 13: Analysts of Variance -- Bibliography.Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data). Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, along with exercises to test your new knowledge. The text opens with a hands-on installation of R and CRAN packages for both Windows and macOS. The bulk of the book is an introduction to statistical methods (non-proof-based, applied statistics) that relies heavily on R (and R visualizations) to understand, motivate, and conduct statistical tests and modeling. Beginning R 4 shows the use of R in specific cases such as ANOVA analysis, multiple and moderated regression, data visualization, hypothesis testing, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. You will: Acquire and install R and RStudio Import and export data from multiple file formats Analyze data and generate graphics (including confidence intervals) Interactively conduct hypothesis testing Code multiple and moderated regression solutions.Compilers (Computer programs)Computer programmingComputer science—MathematicsMathematical statisticsCompilers and InterpretersProgramming TechniquesProbability and Statistics in Computer ScienceCompilers (Computer programs).Computer programming.Computer science—Mathematics.Mathematical statistics.Compilers and Interpreters.Programming Techniques.Probability and Statistics in Computer Science.005.262Wiley Matt897297Wiley Joshua F.MiAaPQMiAaPQMiAaPQBOOK9910427048803321Beginning R 42499649UNINA