Operations managers often use work sampling to estimate how much time workers spend on each operation. Work sampling-which involves observing workers at random points in time-was applied to the sta the catalog sales department of a clothing manufacturer. The department applied regression to data collected for 40 randomly selected working days. The simple linear model E( y) = Bo+ B1x was fit to the data. The printouts for analysis are given below: TIME: ORDERS: X= Number of telephone orders received during the day y = Time spent (in hours) taking telephone orders during the day UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF TIME PREDICTOR| VARIABLES COEFFICIENT STD ERROR STUDENT'S T CONSTANT 10.1639 0.05836 1.77844 0.00586 0.0000 0.000 5.72 ORDERS 9.96 R-SQUARED 0.7229 RESID. MEANSQUARE (MSE) 11.6175 ADJ US TED R-SQUARED 0.7156 STANDARD DE VIATION 3.40844 FI P | DF 1151.55 SOURCE MS REGRESSION 1151.55 99. 12 0.0000 RESIDUAL 38 441.464 11.6175 TOTAL 39 1593.01 CASES INCLUDED 40 MISSING CASES O Conduct a test of hypothesis to determine if time spent (in hours) taking telephone orders during the day and the number of telephone orders received during the day are positively linearly related. Use a = .01.

Operations managers often use work sampling to estimate how much time workers spend on each operation. Work sampling-which involves observing workers at random points in time-was applied to the sta the catalog sales department of a clothing manufacturer. The department applied regression to data collected for 40 randomly selected working days. The simple linear model E( y) = Bo+ B1x was fit to the data. The printouts for analysis are given below: TIME: ORDERS: X= Number of telephone orders received during the day y = Time spent (in hours) taking telephone orders during the day UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF TIME PREDICTOR| VARIABLES COEFFICIENT STD ERROR STUDENT'S T CONSTANT 10.1639 0.05836 1.77844 0.00586 0.0000 0.000 5.72 ORDERS 9.96 R-SQUARED 0.7229 RESID. MEANSQUARE (MSE) 11.6175 ADJ US TED R-SQUARED 0.7156 STANDARD DE VIATION 3.40844 FI P | DF 1151.55 SOURCE MS REGRESSION 1151.55 99. 12 0.0000 RESIDUAL 38 441.464 11.6175 TOTAL 39 1593.01 CASES INCLUDED 40 MISSING CASES O Conduct a test of hypothesis to determine if time spent (in hours) taking telephone orders during the day and the number of telephone orders received during the day are positively linearly related. Use a = .01.

Algebra and Trigonometry (MindTap Course List)

4th Edition

ISBN:9781305071742

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section1.FOM: Focus On Modeling: Fitting Lines To Data

Problem 6P

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