Beginning R 4 from beginner to pro

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...

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1. Verfasser:	Wiley, Matt (VerfasserIn)
Weitere Verfasser:	Wiley, Joshua F. (VerfasserIn)
Format:	UnknownFormat
Sprache:	eng
Veröffentlicht:	New York, NY Apress 2020
Schlagworte:	Programming languages (Electronic computers). > Computer programming. > Mathematical statistics. > Programmiersprache > R > Data Science > Big Data
Online Zugang:	Inhaltsverzeichnis
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

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Beschreibung
Zusammenfassung:	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.
Beschreibung:	Literaturverzeichnis: Seite 459-460
Beschreibung:	xx, 467 Seiten Illustrationen, Diagramme
ISBN:	9781484260524 978-1-4842-6052-4