The following output (from MINITAB) is for the least-squares fit of the model ln y = β0 + β1 ln x + ε, where y represents the monthly production of a gas well and x represents the volume of fracture fluid pumped in. (A scatterplot of these data is presented in Figure 7.22.)

a. What is the equation of the least-squares line for predicting ln y from ln x?
b. Predict the production of a well into which 2500 gal/ft of fluid have been pumped.
c. Predict the production of a well into which 1600 gal/ft of fluid have been pumped.
d. Find a 95% prediction interval for the production of a well into which 1600 gal/ft of fluid have been pumped.

Transcribed Image Text:

Regression Analysis: LN PROD versus LN FLUID The regression equation is LN PROD0.4440.798 LN FLUID Predictor Constant LN FLUID Coef 0.4442 0.79833 SE Coef 0.5853 0.08010 0.76 9.97 0.449 0.000 S 0.7459 R-Sq 28.2% R-Sq ( adj) -27.9% - Analysis of Variance Source Regression Residual Error 253 140.756 Total DF MS 55.268 55.268 99.34 0.000 0.556 254 196.024 Predicted Values for New Observations New Obs Fit SE Fit 95.0% CI 95.0% PI 5.4457 0.0473 5.3526. 5.5389) 3.9738. 6.9176) Values of Predictors for New Observations New ObS LN FLUID 7.3778