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Basic Statistics and Functions Using R

In: Applied Linear Regression for Business Analytics with R

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  • Daniel P. McGibney

    (University of Miami)

Abstract

Data science represents a multifaceted discipline, since it requires knowledge from statistics to understand the data, knowledge from programming to manipulate the data, and the know-how to explain the data, which is often best done with one or more visualizations. Beyond statistics as the general subject matter within the branch of mathematics, the word “statistics” carries a second definition referring to the numeric values that summarize a sample, such as the mean, median, standard deviation, and variance. The R programming language signifies a preferred choice among statisticians and data scientists to easily manipulate data and provide useful statistics on that data. R has many popular plots, but here we will focus on three of the most basic ones, which are necessary for the study of linear regression.

Suggested Citation

  • Daniel P. McGibney, 2023. "Basic Statistics and Functions Using R," International Series in Operations Research & Management Science, in: Applied Linear Regression for Business Analytics with R, chapter 0, pages 7-32, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-21480-6_2
    DOI: 10.1007/978-3-031-21480-6_2
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