There are four questions that pertain to basic stats and model building.
1. A dummy variable:
a. is useless in building models
b. is always given a value of 1
c. is not useful in modeling categorical variables
d. has only two possible values 0 (zero) or 1.
2. A horizontal regression line has a special significance because it represents no relationship between the variables.
3. A model generalizes well if it is still predictive when used beyond the data that was used to create it
4. A model that does not generalize well is a bad model.
1. A dummy variable is (d) has only 2 possible values (0 and 1).
A dummy variable is used when you have a variable that is categorical, with only 2 possible categories. For example, if your variable is gender. This variable is a categorical variable with only 2 categories - male and female. So, if we were to create a dummy variable out of gender you may give 'male' a value of 1 and 'female' a value of 0 (or vice versa). It can be very useful in building models, as it allows one to ...
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