The accompanying data was extracted from the article "Effects of Cold and Warm Temperatures on Springback of Aluminum-Magnesium Alloy 5083- H111" (J. of Engr. Manuf., 2009: 427-431). The response variable is yield strength (MPa), and the predictor is temperature (°C)
Here is Minitab output from fitting the quadratic regression model (a graph in the cited paper suggests that the authors did this):
a. What proportion of observed variation in strength can be attributed to the model relationship?
b. Carry out a test of hypotheses at significance level .05 to decide if the quadratic predictor provides useful information over and above that provided by the linear predictor.
c. For a strength value of 100, y= 134.07, sY = 2.38. Estimate true average strength when temperature is 100, in a way that conveys information about precision and reliability. d. Use the information in (c) to predict strength for a single observation to be made when temperature is 100, and do so in a way that