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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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Simple linear regression

On to a substantially less trivial example, let's say No Scone Unturned has been keeping careful records of how many raisins (in grams) they have been using for their famous oatmeal raisin cookies. They want to construct a linear model describing the relationship between the area of a cookie (in centimeters squared) and how many raisins they use, on average.

In particular, they want to use linear regression to predict how many grams of raisins they will need for a 1-meter long oatmeal raisin cookie. Predicting a continuous variable (grams of raisins) from other variables sounds like a job for regression! In particular, when we use just a single predictor variable (the area of the cookies), the technique is called simple ...

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