Q. In the context of linear regression, what does 'residual' refer to?
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A.
The predicted value of the dependent variable
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B.
The difference between the observed and predicted values
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C.
The slope of the regression line
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D.
The variance of the independent variable
Solution
A residual is the difference between the observed value of the dependent variable and the value predicted by the regression model.
Correct Answer:
B
— The difference between the observed and predicted values
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Q. What is the purpose of the intercept in a linear regression equation?
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A.
To represent the predicted value when all independent variables are zero
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B.
To indicate the strength of the relationship
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C.
To adjust for multicollinearity
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D.
To minimize the residuals
Solution
The intercept represents the predicted value of the dependent variable when all independent variables are equal to zero.
Correct Answer:
A
— To represent the predicted value when all independent variables are zero
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Q. Which of the following techniques can be used to assess the linearity assumption in linear regression?
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A.
Residual plots
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B.
Box plots
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C.
Heat maps
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D.
Pie charts
Solution
Residual plots are used to assess the linearity assumption by showing the relationship between the residuals and the independent variable.
Correct Answer:
A
— Residual plots
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