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.

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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am. 13.
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