Upload Cars04-1 Cars04-1 data and use engine size to predict the car’s city gas mileage(City MPG)....

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Upload Cars04-1 Cars04-1 data and use engine size to predict thecar’s city gas mileage(City MPG). Answer the questions.

I) For each additional 2.0 liter in engine size how muchthe MPG will change? (11.11 points)

  • a. It will decrease by 0.21 mpg.
  • b. It will decrease by 8.21 mpg.
  • c. It will be 25.49 mpg.
  • d. For car with zero horse power we expect 33.7 mpg.
  • e. Not applicable.

II) After performing the regression analysis you areasked to pick one number that would best answer the question: Arethese two variables, engine size and city gas mileage, related ornot? What is this number and why?  (11.11points)

  • a. The number is the P-value, which in this case is very lowindicating a strong probability that the two variables arerelated.
  • b. The number is the slope and it clearly indicates therelation: For each additional liter in engine size the mpgdecreases.
  • c. This number is R-square and since it is not close to 1 wecannot claim that these two variables are related.
  • d. None of these.

III) Given a car that has the engine size of 3.0 litersuse regression analysis and all available information in there, inorder to predict this car’s city gas mileage. What is your intervalprediction? (11.11 points)

  • a. ±4.15
  • b. 33.7
  • c. 21.38
  • d. [17.09, 25.68]
  • e. Not applicable
    EngineSizeCityMPG
    1.628
    1.628
    2.226
    2.226
    2.226
    229
    229
    226
    227
    226
    226
    1.732
    1.736
    1.732
    1.629
    1.629
    1.629
    226
    226
    226
    2.423
    1.626
    1.625
    1.824
    1.824
    1.824
    1.628
    1.828
    1.828
    2.224
    2.226
    2.226
    2.226
    2.226
    2.226
    1.532
    2.325
    2.325
    224
    222
    1.832
    1.832
    1.832
    1.535
    1.533
    1.535
    3.120
    3.421
    2.224
    3.522
    3.421
    2.422
    2.422
    2.422
    2.721
    2.721
    2.421
    2.421
    221
    320
    319
    2.426
    2.426
    1.732
    226
    1.446
    260
    2.719
    2.719
    2.720
    2.324
    320
    1.625
    2.521
    2.523
    2.224
    3.420
    3.820
    2.224
    320
    2.522
    2.521
    2.520
    2.424
    321
    2.424
    3.320
    1.559
    224
    1.824
    1.938
    1.824
    224
    2.422
    1.822
    2.520
    3.820
    3.820
    3.818
    3.820
    3.818
    3.523
    3.818
    3.518
    2.721
    3.519
    2.421
    2.422
    3.518
    4.617
    4.617
    321
    321
    3.517
    3.517
    3.518
    3.518
    2.518
    1.822
    3.219
    4.617
    4.617
    319
    3.518
    3.818
    3.521
    3.520
    3.520
    3.420
    3.820
    2.521
    2.520
    319
    321
    321
    3.320
    2.821
    224
    1.822
    1.922
    3.220
    1.823
    320
    317
    318
    320
    318
    2.520
    2.519
    2.519
    320
    320
    320
    2.519
    3.820
    3.820
    3.618
    3.518
    2.721
    4.617
    3.518
    3.519
    318
    3.320
    318
    318
    320
    320
    2.620
    2.619
    3.219
    3.220
    4.617
    4.617
    220
    220
    2.321
    2.321
    319
    321
    2.819
    418
    2.520
    2.320
    2.518
    2.920
    2.520
    3.518
    3.518
    320
    318
    2.718
    4.217
    4.217
    4.214
    319
    320
    4.418
    4.418
    4.418
    3.818
    4.618
    4.618
    4.618
    4.517
    4.517
    318
    4.218
    4.217
    4.218
    4.218
    4.217
    318
    4.318
    4.318
    3.917
    3.917
    4.617
    4.617
    4.617
    3.216
    516
    5.513
    3.220
    517
    3.219
    516
    4.318
    516
    221
    221
    2.421
    2.320
    2.919

Answer & Explanation Solved by verified expert
3.6 Ratings (253 Votes)
Using Excel data data analysis regression SUMMARY OUTPUT Regression Statistics Multiple R 06631 R Square 04397 Adjusted R Square 04373 Standard Error 42997 Observations 234 ANOVA df    See Answer
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