Group Practice Problems An airline company expects a linear relationship between Flight Hours (X) and the...

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Group Practice Problems An airline company expects a linear relationship between Flight Hours (X) and the total maintenance costs (Y). The following data has been collected: X: Independent Variable Y: Dependent Variable Month January Flight Hours Maintenance Costs 21,000 $84,000 February 22,000 $90,000 March 14,000 $71,000 April 17,000 $75,000 May 10,000 $45,000 June 19,000 $78,000 July 15,000 $64,000 August 16,000 $68,000 September 20,000 $85,000 October 14,000 $60,000 November 18,000 $77,000 December 12,000 $51,000 Total 198,000 $848,000 Q1: Using the high-low method, estimate the linear relationship Y = a + bx Note: for the high-low method, we only use two data points, one with the highest value of X and one with the lowest value of X Q2: Using the linear cost function you estimated from Q1, what is the expected maintenance costs for 20,000 flight hours? Q3: Using all the data points and run a regression model Part 1: Your regression output: Regression output example from class: SUMMARY OUTPUT Regression Statistics Multiple R 0.980995276 R Square 0.96235173 Adjusted R Square 0.958586904 Standard Error 1447.996847 Observations 12 ANOVA df SS MS F Regression 1 535949718 535949718 Residual 10 Total 20966948.69 2096694.869 11 556916666.7 Intercept Labor Hours 255.616459 Significance F 1.89126E-08 Coefficients Standard Error t Stat P-value 48270.6181 1248.716188 38.6561963 3.20356E-12 0.245567266 15.9880099 1.89126E-08 3.92613187 Lower 95% Upper 95% Lower 95.0% Upper 95.0% 45488.30507 51052.93118 45488.30507 51052.93118 3.378973903 4.473289836 3.378973903 4.473289836 Part 2: based on the regression output, what is the linear relationship Y = a + bx? Group Practice Problems An airline company expects a linear relationship between Flight Hours (X) and the total maintenance costs (Y). The following data has been collected: X: Independent Variable Y: Dependent Variable Month January Flight Hours Maintenance Costs 21,000 $84,000 February 22,000 $90,000 March 14,000 $71,000 April 17,000 $75,000 May 10,000 $45,000 June 19,000 $78,000 July 15,000 $64,000 August 16,000 $68,000 September 20,000 $85,000 October 14,000 $60,000 November 18,000 $77,000 December 12,000 $51,000 Total 198,000 $848,000 Q1: Using the high-low method, estimate the linear relationship Y = a + bx Note: for the high-low method, we only use two data points, one with the highest value of X and one with the lowest value of X Q2: Using the linear cost function you estimated from Q1, what is the expected maintenance costs for 20,000 flight hours? Q3: Using all the data points and run a regression model Part 1: Your regression output: Regression output example from class: SUMMARY OUTPUT Regression Statistics Multiple R 0.980995276 R Square 0.96235173 Adjusted R Square 0.958586904 Standard Error 1447.996847 Observations 12 ANOVA df SS MS F Regression 1 535949718 535949718 Residual 10 Total 20966948.69 2096694.869 11 556916666.7 Intercept Labor Hours 255.616459 Significance F 1.89126E-08 Coefficients Standard Error t Stat P-value 48270.6181 1248.716188 38.6561963 3.20356E-12 0.245567266 15.9880099 1.89126E-08 3.92613187 Lower 95% Upper 95% Lower 95.0% Upper 95.0% 45488.30507 51052.93118 45488.30507 51052.93118 3.378973903 4.473289836 3.378973903 4.473289836 Part 2: based on the regression output, what is the linear relationship Y = a + bx?