Ted uses the quadratic regression model to determine the predictive average unit cost of baseballs produced in his production facility. After determining predictive average costs at multiple unit batch size amounts in millions, he now wants to know what the output level that minimizes his costs would be.
Given b1 = -0.3851 and b2 = 0.0168, what is the level that will maximize his average cost in units?
Multiple Choice
8.0 million units
2.6 million units
21.00 million units
11.46 million units
Ava Diego, a doctoral student, is researching car loans issued at a local bank. She prepared a sample of 200 to determine if there is a relationship between the loan amount, length of the loan, and interest rate provided. The regression results are in the table below. Which model is more suitable for prediction and what is the best fit reason?
Variable Model 1 Model 2
Constant 114.325
110.54
0.000
0.000
Interest Rate 106.505
108.650
(0.000 )
(0.000 )
Loan Length 0.2074
0.3290
(0.000 )
(0.006 )
Interest × Loan NA
-0.1430
(0.0005 )
Adjusted R2 0.2178
0.2089
Multiple Choice
Model 2 is the most suitable because of the p-value variance.
Model 1 is the most suitable because of the higher adjusted R2 value.
Model 2 is the most suitable because of the lower adjusted R2 value.
Neither provide enough results data to predict the model or reasoning.
