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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 4. Probability

It's time for us to put descriptive statistics down for the time being. It was fun for a while, but we're no longer content just determining the properties of observed data; now we want to start making deductions about data we haven't observed. This leads us to the realm of inferential statistics.

In data analysis, probability is used to quantify uncertainty of our deductions about unobserved data. In the land of inferential statistics, probability reigns queen. Many regard her as a harsh mistress, but that's just a rumor.

Basic probability

Probability measures the likeliness that a particular event will occur. When mathematicians (us, for now!) speak of an event, we are referring to a set of potential outcomes of an experiment, ...

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