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- EXCEL LINEAR REGRESSION IN BASEBALL PREDICTIONS HOW TO
- EXCEL LINEAR REGRESSION IN BASEBALL PREDICTIONS PDF
The first, \(x_1\), is a binary variable such as female gender it takes on values of 0 (males) and 1 (females) only. We can imagine a continuous outcome \(y\), e.g. the income of Hollywood actors, that we predict with two variables. In thinking about interaction terms, it helps to first simplify by working through the prediction of the regression equation for different values of two predictors, \(x_1\) and \(x_2\). Note: You must have read Brambor, Clark & Golder (2006) before working on this tutorial.Įxample 1: one binary, one continuous term The Companion to Applied Regression (see our syllabus) also provides many detailed explanations.Īs always, please note that this tutorial only accompanies the other materials for Day 11 and that you are expected to have worked through the reading for that day before tackling this tutorial. Each of these functions is well-documented either in its help file (which you can access in R by typing ?ifelse, for instance) or on the web. This will help you understand the functions better. Note on R functions discussed in this tutorial: I don’t discuss many functions in detail here and therefore I encourage you to look up the help files for these functions or search the web for them before you use them. To use code from this tutorial, please type it yourself into your R script or you may copy & paste code from the source file for this tutorial which is posted on my website.
EXCEL LINEAR REGRESSION IN BASEBALL PREDICTIONS PDF
When the PDF is created, some characters (for instance, quotation marks or indentations) are converted into non-text characters that R won’t recognize. Note on copying & pasting code from the PDF version of this tutorial: Please note that you may run into trouble if you copy & paste code from the PDF version of this tutorial into your R script.
EXCEL LINEAR REGRESSION IN BASEBALL PREDICTIONS HOW TO