Sherry is a production manager for a small manufacturing shop and is interested in developing a predictive model to estimate the time to produce an order of a given size-that is, the total time to produce a certain quantity of the product. Suppose she has collected data in the following table on the total time (in minutes) to produce 30 different orders of various quantities. Quantity Total Time Total Time (minutes) Quantity (minutes) 105 174 388 351 125 189 392 428 135 223 400 412 14: 323 421 545 149 248 43 441 171 319 43 32 190 372 455 589 204 185 458 483 206 250 480 513 240 177 486 421 255 397 493 403 277 227 506 700 299 228 586 591 335 367 589 458 371 490 665 641 (a) Develop a scatter diagram with quantity as the independent variable. 800 700 800 $ 7 600 700 600 500 600 (minute 500 400 500 400 uantity Quantity 300 300 400 200 200 300 200 9 1 100 100 OL OL 0 100 200 300 400 500 600 700 0 100 200 300 400 500 600 700 800 100 200 300 400 500 600 700 0 100 200 300 400 500 600 700 800 Quantity Total Time (minutes) Quantity Total Time (minutes) (b) What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a negative linear relationship between quantity and total time. The scatter diagram indicates no apparent relationship between quantity and total time. The scatter diagram indicates a nonlinear relationship between quantity and total time. The scatter diagram indicates a positive linear relationship between quantity and total time. (c) Develop the estimated regression equation. (Let x = quantity, and let y = total time (in minutes). Round your numerical values to four decimal places.) y = Interpret the intercept and slope