Question: Does the number of "cylinders" in cars have an effect on their "Combined MPG" ?
I need help performing a regression analysis and evaluation of the relationship between the two variables: cylinders and combined MPG
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"What is the regression analysis on the relationship between the two variables (include analysis and an evaluation of the assumptions displayed by the scatterplot)"
Link for the Data: https://dasl.datadescription.com/datafile/fuel-economy-2016/?_sf_s=Fuel+Economy&_sfm_cases=4+59943
Here are my calculations on Excel:
File Home Insert Draw Page Layout Formulas Data Review View Help Share Comments La lo Queries & Connections P & Clear 20 Data Analysis TIII GH Get Refresh Properties Geography Sort Filter Reapply Stocks Text to What-If Forecast Outline Data v All Edit Links Advanced Columns v Analysis ~ Sheet Get & Transform Data Queries & Connections Data Types Sort & Filter Data Tools Forecast Analysis C4 X V A B C D E F G H K M N O 1 SUMMARY OUTPUT IN W Regression Statistics X Variable 1 Residual Plot Multiple R 0.744046167 40 5 R Square 0.553604699 6 Adjusted R Square 0.553235472 20 7 Standard Error 3.720447941 Residuals 8 Observations 1211 9 10 15 10 ANOVA -20 X Variable 1 11 df 5S MS F Significance F 12 Regression 1 20753.76608 20753.76608 1499.36184 5.5495E-214 13 Residual 1209 16734.65506 13.84173288 14 Total 1210 37488.42114 15 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 95%ower 95.09pper 95.0% 17 Intercept 35.97491323 0.344641277 104.3836465 0 35.29875183 36.65107 35.29875 36.65107 18 X Variable 1 -2.254052219 0.058211762 -38.72159397 5.5495E-214 -2.368259511 -2.13984 -2.36826 -2.13984 19 20 21 22 RESIDUAL OUTPLIT PROBABILITY OUTPLIT DATA Regression + + 100%File Home Insert Draw Page Layout Formulas Data Review View Help 15 Share Comments Queries & Connections 20 ZA Data Analysis IIII Clear Get Refresh Properties Stocks Geography Sort Filter Reapply Text to What-If Forecast Outline Data v All Edit Links Advanced Columns CX v Analysis Sheet Get & Transform Data Queries & Connections Data Types Sort & Filter Data Tools Forecast Analysis C4 X V A B C D E F G H J K L M N O 16 Coefficients Standard Error t Stat P-value Lower 95% Upper 95%ower 95.09pper 95.0% 17 Intercept 35.97491323 0.344641277 104.3836465 0 35.29875183 36.65107 35.29875 36.65107 18 X Variable 1 -2.254052219 0.058211762 -38.72159397 5.5495E-214 -2.368259511 -2.13984 -2.36826 -2.13984 19 20 21 22 RESIDUAL OUTPUT PROBABILITY OUTPUT 23 Normal Probability Plot 24 Observation Predicted Y Residuals Percentile Y 60 25 1 26.95870436 1.041295643 0.041288192 12 40 26 2 8.926286602 5.073713398 0.123864575 12 27 3 17.94249548 -1.94249548 0.206440958 12 20 28 4 17.94249548 -2.94249548 0.289017341 12 29 5 17.94249548 -1.94249548 0.371593724 12 0 20 40 60 80 100 120 30 6 17.94249548 -2.94249548 0.454170107 13 Sample Percentile 31 7 17.94249548 -1.94249548 0.536746491 13 32 8 17.94249548 -2.94249548 0.619322874 13 33 9 26.95870436 -0.958704357 0.701899257 13 34 10 22.45059992 -3.450599918 0.78447564 13 35 11 26.95870436 -0.958704357 0.867052023 13 36 12 26.95870436 -0.958704357 0.949628406 13 37 13 22.45059992 -2.450599918 1.032204789 13 DATA Regression + 100%
