The vapor pressure of water at various temperatures follows: Observation Vapor pressure Number, i Temperature (K) (mm Hg) 1 273 4.6 2 283 9.2 3 293 17.5 4 303 31.8 5 313 55.3 6 323 92.5 7 333 149.4 8 343 233.7 9 353 355.1 10 363 525.8 11 373 760.0 (a) Draw a scatter diagram of these data. What type of rela tionship seems appropriate in relating y to x? (b) Fit a simple linear regression model to these data. (c) Test for significance of regression using0.05. What conclusions can you draw? (d) Plot the residuals from the simple linear regression model versus . What do you conclude about model adequacy? (e) The Clausis-Clapeyron equation states that ln where is the vapor pressure of water. Repeat parts(a)"(d). using an appropriate transformation. 11-67. An electric utility is interested in developing a model relating peak hour demand ( y in kilowatts) to total monthly en ergy usage during the month (x, in kilowatt hours). Data for 50 residential customers are shown in the following table. (a) Draw a scatter diagram of y versus x. (b) Fit the simple linear regression model. (c) Test for significance of regression using0.05. (d) Plot the residuals versus and comment on the underly ing regression assumptions. Specifically, does it seem that the equality of variance assumption is satisfied? (e) Find a simple linear regression model using as the response. Does this transformation on y stabilize the in equality of variance problem noted in part (d) above? 1y yi Pv 1Pv2 1T ,