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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Chapter 8. Predicting Continuous Variables

Now that we've fully covered introductory inferential statistics, we're now going to shift our attention to one of the most exciting and practically useful topics in data analysis: predictive analytics. Throughout this chapter, we are going to introduce concepts and terminology from a closely related field called statistical learning or, as it's (somehow) more commonly referred to, machine learning.

Whereas in the last unit, we were using data to make inferences about the world, this unit is primarily about using data to make inferences (or predictions) about other data. On the surface, this might not sound more appealing, but consider the fruits of this area of study: if you've ever received a call from ...

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