A statistical program is recommended. 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 (minutes) 105 172 125 189 135 221 141 323 149 248 171 319 190 372 204 185 206 250 240 177 255 397 277 227 299 228 335 367 371 490 Quantity Total Time (minutes) 388 351 392 428 400 412 421 545 439 443 439 320 455 589 458 483 480 511 486 423 493 403 506 700 586 591 589 458 665 643 #1) Develop the estimated regression equation. (Let x = quantity, and let y = total time (in minutes). Round your numerical values to four decimal places.) ŷ = #2) Find the value of the test statistic (round to two decimal places). Find the p-value (round to three decimal places). #3) Did the estimated regression equation provide a good fit? (Round your numerical answer to four decimal places.) Since r2 =_______. is (less than OR at least .55), the estimated regression equation (did not provide OR did provide) a good fit.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A statistical program is recommended.

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 (minutes)
105	172
125	189
135	221
141	323
149	248
171	319
190	372
204	185
206	250
240	177
255	397
277	227
299	228
335	367
371	490

Quantity	Total Time (minutes)
388	351
392	428
400	412
421	545
439	443
439	320
455	589
458	483
480	511
486	423
493	403
506	700
586	591
589	458
665	643

#1) Develop the estimated regression equation. (Let x = quantity, and let y = total time (in minutes). Round your numerical values to four decimal places.) ŷ =

#2) Find the value of the test statistic (round to two decimal places). Find the p-value (round to three decimal places).

#3) Did the estimated regression equation provide a good fit? (Round your numerical answer to four decimal places.) Since r² =_______. is (less than OR at least .55), the estimated regression equation (did not provide OR did provide) a good fit.

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