6)
This joint effect of two variables on response is captured as an interaction effect ( as product of both variables)
True
7)
The Null Hypothesis for Multiple Regression is : The Model does not adequately fits the data and the Alternative Hypothesis is : The Model adequately fits the data.
Now a p-value of zero, approx will lead to the rejection of Null Hypothesis and will lead us to conclude that The Model adequately fits the data which makes the value of R2 closer to 1
False
8)
In selecting independent variables for a regression model, neither the forward selection method nor the backward elimination method guarantee the optimal combination of the independent variables.
False
11)
R2 shows how well terms (data points) fit a curve or line.
Adjusted R2 also indicates how well terms fit a curve or line but adjusts for the number of terms in a model.
In the case when a relevant variable is added, both R**2 and adjusted R**2 tend to increase.
Hence, option B is the right choice here.
12)
The indicator variable(dummy variable) is used to convert a categorical variable to a numeric term so that the machine can understand it. So, option a makes real sense here.
Option b is true.
Indicator variable assume only slopes are different and not the intercept, Hence, option c is wrong here.
a and b are the correct ones.
Option A is the answer.
The multiplication of two variables is used as a predictor if the two variables jointly affect...
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