Answer Happy

predicted xi residuals yi xi'yi yi temps xi inches squared temps residuals squared 8 1.3 10.4 1.69 7.589845 0.410155 0.168227 -0.2713 0.073605 6.9 1.8 7.171302 12.42 3.24 0.17532 8.1 0.9 0.81 7.92468 0.030737 7.29 7.33872 -0.33872 0.114731 2.56 7 1.6 11.2 -0.20163 0.040656 2.6 6.76 6.501634 6.3 16.38 -0.92243 0.850874 1.5 2.25 7.422428 6.5 9.75 0.270584 13.44 4.41 6.920177 -0.52018 2.1 6.4 -0.3668 0.134542 3 6.166799 9 5.8 17.4 0.64 8.008389 0.291611 6.64 0.085037 0.8 8.3 6.669051 1.630949 2.659995 5.76 8.3 2.4 19.92 6.25 6.585342 0.014658 0.000215 6.6 16.5 2.5 6.501634 0.098366 0.009676 6.76 6.6 2.6 17.16 4.438879 158.5 50.13 y bar 7.066667 x bar 1.925
Correlation matrix for students xi yi temps inches yi temps 1 -0.68701 xi inches -0.68701 1 The Pulsar Corporation sells a large sterilizer with four extendable shelves for medical tools. Company engineers believe that the time to reach the operating temperature from a cold start ly, measured in minutes) is linearly related to the thickness of the insulation (x, in inches). A random sample of n=12 thicknesses was selected, and the time to reach operating temperature was recorded for each. The data is presented above. Which of the following statements best represents how to interpret the sample coefficient of correlation, r, for the sterilizer regression?
Which of the following statements best represents how to interpret the sample coefficient of correlation, r, for the sterilizer regression? a) a. Based on its value, we can assume that when the insulation thickness goes up, the time to operating temperature goes up b) b. Based on its value, we can assume that when the insulation thickness goes up, the time to operating temperature goes down O c) c. Based on its value, we can clearly say that rising insulation thickness is clearly causing the time to operating temperature to rise d) d. none of the above are correct