The predicted value of Y must be between 0 and 1.
A linear probability model (LPM) is a regression model where the outcome variable is a binary variable, and one or more explanatory variables are used to predict the outcome. Explanatory variables can themselves be binary, or continuous.
Suppose, that the linear probability model yields a predicted value of Y that is equal to 1.3.
This is nonsensical because
The predicted value of Y must be between 0 and 1.
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