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Concept explainers
- (a) List two limitations of simple regression.
- (b) Why is estimating a multiple regression model just as easy as simple regression?
(a)
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Mention two limitations of simple regression.
Answer to Problem 1CR
The two limitations of simple regression are “multiple relationships exist between the variables” and “estimates are biased if the relevant predictors are deleted”.
Explanation of Solution
Justification: The simple regression is used for predicting the response variable based on one independent variable. The two limitations of the simple regression are,
- The response variable might have relation with many predictor variables. That is multiple relationships exist between the variables.
- If the proper predictor variable is removed in the study the estimates would be biased.
(b)
![Check Mark](/static/check-mark.png)
Explain why estimating a multiple regression model is as easy as simple regression.
Explanation of Solution
Justification: The extension of the simple regression is the multiple regression. The multiple regression is used when one predictor variable is not appropriate for predicting the response variable. The multiple regression includes many predictors or explanatory variables in the model. The use of multiple regression models is as easy as simple regression because the same procedures are used in both regression. The only difference is that in simple regression one predictor variable is used but in multiple regression more than one predictor variables are used.
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Chapter 13 Solutions
Loose-leaf For Applied Statistics In Business And Economics
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