A student creates a regression to forecast the price of a freighter that was 10 years...

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A student creates a regression to forecast the price of a freighter that was 10 years old and had a capacity of 300 tons. This regression would yield a predicted price of: A 1 SUMMARY OUTPUT 2 3 4 Multiple R SR Square B Regression Statistics 6 Adjusted R Square 7 Standard Error 8 Observations 9 10 11 Intercept 12 Ship's Age (yrs) 13 Capacity (tons) 95.8% 91.8% 87.6% 57,4% C Coefficients Standard Error 1.178 0.124 0.014 7.500 -0.800 0.060 D t Stat 6.436 -6.559 4.265 E P-value < 16 million dollars Between 16 and 17 million dollars Between 17 and 18 million dollars Between 18 and 19 million dollars > 19 million dollars 0.003 0.003 0.013 A student creates a regression to forecast the price of a freighter that was 10 years old and had a capacity of 300 tons. This regression would yield a predicted price of: A 1 SUMMARY OUTPUT 2 3 4 Multiple R SR Square B Regression Statistics 6 Adjusted R Square 7 Standard Error 8 Observations 9 10 11 Intercept 12 Ship's Age (yrs) 13 Capacity (tons) 95.8% 91.8% 87.6% 57,4% C Coefficients Standard Error 1.178 0.124 0.014 7.500 -0.800 0.060 D t Stat 6.436 -6.559 4.265 E P-value < 16 million dollars Between 16 and 17 million dollars Between 17 and 18 million dollars Between 18 and 19 million dollars > 19 million dollars 0.003 0.003 0.013 A student creates a regression to forecast the price of a freighter that was 10 years old and had a capacity of 300 tons. This regression would yield a predicted price of: A 1 SUMMARY OUTPUT 2 3 4 Multiple R SR Square B Regression Statistics 6 Adjusted R Square 7 Standard Error 8 Observations 9 10 11 Intercept 12 Ship's Age (yrs) 13 Capacity (tons) 95.8% 91.8% 87.6% 57,4% C Coefficients Standard Error 1.178 0.124 0.014 7.500 -0.800 0.060 D t Stat 6.436 -6.559 4.265 E P-value < 16 million dollars Between 16 and 17 million dollars Between 17 and 18 million dollars Between 18 and 19 million dollars > 19 million dollars 0.003 0.003 0.013 A student creates a regression to forecast the price of a freighter that was 10 years old and had a capacity of 300 tons. This regression would yield a predicted price of: A 1 SUMMARY OUTPUT 2 3 4 Multiple R SR Square B Regression Statistics 6 Adjusted R Square 7 Standard Error 8 Observations 9 10 11 Intercept 12 Ship's Age (yrs) 13 Capacity (tons) 95.8% 91.8% 87.6% 57,4% C Coefficients Standard Error 1.178 0.124 0.014 7.500 -0.800 0.060 D t Stat 6.436 -6.559 4.265 E P-value < 16 million dollars Between 16 and 17 million dollars Between 17 and 18 million dollars Between 18 and 19 million dollars > 19 million dollars 0.003 0.003 0.013

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