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R Cookbook (Proven Recipes for Data Analysis, Statistics, and Graphics) - 9781492040682

List Price: $79.99
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9781492040682
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  • Product Details

    Author:
    JD Long, Paul Teetor
    Format:
    Paperback
    Pages:
    598
    Publisher:
    O'Reilly Media (July 30, 2019)
    Language:
    English
    ISBN-13:
    9781492040682
    ISBN-10:
    1492040681
    Dimensions:
    7" x 9.19"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20251023163248-20251023.xml
    Folder:
    TWO RIVERS
    List Price:
    $79.99
    As low as:
    $68.79
    Publisher Identifier:
    P-PER
    Discount Code:
    C
    Case Pack:
    7
    Country of Origin:
    United States
    Pub Discount:
    60
    Weight:
    33.28oz
    Imprint:
    O'Reilly Media
  • Overview

    With more than 275 practical recipes, this expanded edition helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.

    Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.

    • Create vectors, handle variables, and perform other basic functions
    • Simplify data input and output
    • Tackle data structures such as matrices, lists, factors, and data frames
    • Work with probability, probability distributions, and random variables
    • Calculate statistics and confidence intervals and perform statistical tests
    • Create a variety of graphic displays
    • Build statistical models with linear regressions and analysis of variance (ANOVA)
    • Explore advanced statistical techniques, such as finding clusters in your data