An analyst fitted a regression model to predict city MPG using as predictors Len
ID: 3230917 • Letter: A
Question
An analyst fitted a regression model to predict city MPG using as predictors Length (of car in inches), Width (of car in inches) and Weight (of car in pounds). a. Intuitively, what association do you expect between the explanatory variables and MPG? b. Do you see anything of concern about these variables being used as explanatory variables? Explain c. What does the matrix plot done in class show you? Explain d. Write the null and alternative hypothesis that checks the regression model on all explanatory variables e. According to the output shown below, was the regression fit statistically significant? (was the null rejected?) Analysis of Variance f. Which would be your final model (regression equation) to predict city MPG? Explain g. Using your FINAL model, what would be the MPG if the length of the car is 80 inches, the width is 60 inches and the weight is 3600 pounds? h. What would be the effect on MPG of increasing the weight by 1 pound? What about increasing the length by 1 inch? i. According to the diagnostics do you see anything to be concerned about?Explanation / Answer
Answer to the question)
Answer to part a)
Intuititvely we consider as the length width and weight of car increases, the value of MPG must go on decreasing . Similarly if the length , width and weight of car decreases, he value of MPG increases.
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Answer to part b)
Yes, the city MPG is being predicted by the variables length , width and weight of not all the vehicles but only cars, this may lead to a biased outcome
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Answer to part c)
The matrix plot tells us about the regression model , it simplifies the model and makes it easy to interpret
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Answer to part d)
The null and alternate hypothesis for this model would be :
Null hypothesis: all the slopes of all the explanatory variables are equal to Zero
Ho: 1 = 2 = 3 = ...n = 0
Alternate hypothesis: atleast one slope of the expalnatory variables is not equal to zero
Ha: at least one 0
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