Introduction to R Programming for Data Analysis
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Introduction to R Programming for Data Analysis

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@CheaperBirch

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Questions and Answers

Which of the following attributes is cited as a reason for using R in programming?

  • Availability of many libraries. (correct)
  • Inability to create plots.
  • Limited functionality.
  • Exclusivity to specific sectors.
  • What is the primary purpose of the package 'Tidyverse' in R?

  • Creating complex algorithms.
  • Manipulating large datasets.
  • Basic file management.
  • Data visualization techniques. (correct)
  • Which function is NOT mentioned as a learning outcome within R programming?

  • Load and use R Packages.
  • Write your own R functions.
  • Create quick Plots.
  • Import data from CSV files. (correct)
  • Which platform provides the download for R?

    <p><a href="https://cran.r-project.org/bin/windows/base/">https://cran.r-project.org/bin/windows/base/</a></p> Signup and view all the answers

    What aspect of R programming does Dr. Preethi Ananthachari emphasize?

    <p>R combines desirable attributes for analysis.</p> Signup and view all the answers

    Study Notes

    Why R-Programming?

    • Many tools exist for Business Analysis/Business Intelligence, each with its strengths and weaknesses.
    • R offers a desirable blend of attributes.
    • R has extensive libraries.
    • Tidyverse is a package containing useful tools, including:
      • Dplyr for data manipulation.
      • Ggplot for data visualization.

    What You'll Learn

    • Use R and R Studio Interface.
    • Execute R Commands.
    • Create R Objects.
    • Write custom R functions and scripts.
    • Load and utilize R packages.
    • Create quick plots.

    Downloading R Packages

    Getting Started with R:

    • Concepts like printing values and removing objects are covered.
    • Vectors are introduced:
      • A vector is a collection of elements of the same data type.
      • Elements can be accessed using indexing.

    Basic Statistical Functions

    • Functions such as mean, median, sum, min, and max are explained.
    • Variance, standard deviation, and quantile statistics are introduced.
    • Functions like range and sort are covered.

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    Related Documents

    R- Programming.pptx

    Description

    This quiz covers the basics of R programming, focusing on its application in business analysis and data visualization. Learn to execute commands, create objects, and utilize packages like Tidyverse for effective data manipulation and visualization. Whether you're just getting started or need a refresher, this quiz will help you familiarize yourself with the essential functions of R.

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