MN3 - MAN4504 Exam 3 Do not open exam until instructed to...

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Unformatted text preview: MAN4504 Exam 3 Do not open exam until instructed to do so, please. 1. This page. la. Print your name and University of Florida ID number in the spaces provided below, and sign your name on the signature line, please. 2. Bubble sheet. 2a. In the left—hand column print and bubble in your name and University of Florida ID number. 2b. In the right-hand column print and bubble in B for Test Form Code. 2c. The boxes marked Special Codes and Section are to be left blank. 3. Exam. 3a. This exam lasts for 1 hour and 50 minutes. 3b. Blank scratch sheets to use as you desire are attached following the exam questions. 30. You may also consult the tables and formulas given at the rear of the exam. 4. When you finish. 4a. Before turning in your exam, check for transcribing errors. Any mistakes you leave in are, most regrettably, there to stay. 4b. Show this exam paper and your picture ID. when you turn in the bubble sheet. 4c. Answers will be posted on the ISOM bulletin board next to room 103 Stuzin and on the WWW after the end of the exam. NAME (Please Print) UNIVERSITY OF FLORIDA ID # SIGNATURE 1. In the field of quality management, six-sigma (a) refers to a set of five, internationally-recognized quality standards. (b) is used to set upper and lower control limits in R—charts. (c) is a name for the concept of continuous incremental improvement towards perfection. (d) is one of three quality management concepts due to Genichi Taguchi. (e) represents producer’s risk in acceptance sampling by variables. Peter Pointman must design an acceptance sampling by attributes plan for inspecting large lots of ball point pens that are produced at his factory in Inkwell, Iowa. The ball point pens are produced in lots of 288 each. Peter’s boss requires that the sampling plan have a type I error of 0.03 and a type 11 error of 0.07. Together, Peter and his boss have decided that the acceptable quality level should be 2% and the lot tolerance percent defective level should be 8%. Based upon this information, which of the following points lie on the operating characteristic curve corresponding to the sampling plan that Peter will choose? (1) (2,0.03) (ii) (2, 0.97) (iii) (8, 0.07) (iv) (8, 0.93) (a) (i) and (iii) (b) (i) and (iv) (e) (ii) and (iii) (d) (ii) and (iv) (e) (iii) and (iv) 3. A machine shop makes drill bits for portable electric drills. Each day for 24 days the diameters of four drill bits that are produced are measured. The average and the range of these four diameters are recorded each day. These data are as follows, where all numbers are in centimeters. m AVERAGE RANGE m AVERAGE RANGE 1 2.0 0.1 13 1.8 0.2 2 1.8 0.2 14 1.7 0.0 3 1.7 0.0 15 2.0 0.1 4 2.2 0.1 16 1.6 0.1 5 2.3 0.3 17 2.2 0.0 6 1.6 0.2 18 2.3 0.0 7 2.0 0.1 19 2.0 0.4 8 2.4 0.0 20 2.4 0.1 9 1.7 0.0 21 1.7 0.0 10 2.1 0.1 22 2.0 0.2 11 2.2 0.1 23 2.1 0.1 12 2.0 0.0 24 2.2 0.0 The goal is to monitor the average diameters of the drill bits with a control chart in which the control limits are approximately three standard deviations from the target value. What is the value, to the nearest ten-thousandths of a centimeter, of the upper control limit in this chart? (a) 2.0000 (b) 2.0854 (c) 2.0729 ((1) 1.9271 (e) Cannot be determined from the data given. 4. Each day, for 25 days, an operations manager at a General Electric factory in Courant, Iowa, has tested four 100—watt light bulbs produced at the factory that day by seeing how long they stay lit. For each sample of four bulbs, he has tabulated the mean total time they stay lit, in hundred of hours. These data are as follows. Day Mean Lighting Day Mean Lighting Time Time 1 16 14 12 2 11 15 19 3 14 16 17 4 15 17 16 5 18 18 16 6 16 19 19 7 18 20 15 8 17 21 16 9 15 22 17 10 17 23 18 ll 19 24 14 12 16 25 16 13 13 The standard deviation of the time a typical 100—watt light bulb produced at the plant stays lit is known to be, in hundreds of hours, 0.25. The operations manager wants to establish a control chart using this data to monitor the variability in the average time these lOOwatt bulbs stay lit. He has been told that the control limits must each be either 2.0, 2.5, 3.0, 3.5, or 4.0 standard deviations from the target. The goal is to maximize the probability that the process is actually out of control when a sample mean is found that lies outside the control limits. What will be the value, to the nearest one— thousandth, of the lower control limit in this control chart, in hundreds of hours? (a) 15.750 (b) 15.625 (0) 15.500 (d) 15.000 (e) None of the above. 5. There are four costs to quality. These are prevention costs, appraisal costs, external costs, and (a) detection costs. (b) liability costs. (c) scrap costs. (d) internal failure costs. (e) inspection costs. 6. The operations manager at Thrifty Airlines has gathered data over several months concerning customer complaints. These complaints have included complaints about flights arriving late at destinations, about lost luggage, about rude ticket counter workers, about damaged luggage, and about other issues. The operations manager draws a frequency diagram that shows these complaints in descending order of frequency. Such a diagram is called (a) a histogram. (b) a Pareto chart. (0) an lshikawa diagram. (d) a scatter diagram. (e) a process chart. 7. Of the four pure process strategies, the one that is the most recent to appear and is the most difficult to attain is the (a) intermittent process. (b) mass customization process. (c) repetitive—focused process. (d) product—focused process. (e) continuous process. 8. Each day for 25 days, the manager of an Amana microwave oven factory in Zappit, Iowa, has sampled 16 microwave ovens built there and tabulated the fraction in the sample that are defective. The results are as follows. Day Fraction Day Fraction Defective Defective 1 0.20 14 0.26 2 0.15 15 0.25 3 0.23 16 0.24 4 0.27 17 0.27 5 0.30 18 0.26 6 0.25 19 0.22 7 0.21 20 0.22 8 0.25 21 0.28 9 0.29 22 0.28 10 0.20 23 0.24 11 0.35 24 0.23 12 0.30 25 0.19 13 0.31 The goal is to establish a control chart for monitoring the fractions of defective microwave ovens in samples of sizes 16 that are produced at the factory. The manager has been told to choose the control limits in this control chart to each be either 2.0, 2.5, 3.0, or 4.0 standard deviations from the target. The manager decides that, within these constraints, he will establish the chart in a way that minimizes producer’s risk. What will be the value, to the nearest ten—thousandth, of the lower control limit in this control chart? (a) -O.1830 (b) 0.0000 (c) 0.0823 (d) 0.1661 (e) 0.2500 9. A local McDonald’s restaurant is trying to decide how many servers to schedule for work during the lunch hour. It is known that the effective capacity of a server is 0.92, the efficiency of a server is 0.95, and, under ideal conditions, the maximum number of people a server can serve per hour is 35 people. What is the minimum number of servers needed to serve an expected volume of 100 customers per hour at lunchtime? (a) 2 (b) 3 (C) 4 (d) 5 (e) Not enough information is given to answer this question. 10. When a firm establishes, via teams, various standards of performance to strive for that relate, for example, to production, to outputs, or to costs, the firm is engaging in (a) benchmarking. (b) JIT inventory management. (0) Pareto optimization. ((1) acceptance sampling. (e) conformance management. 11. In statistical process control, variation in a process is of two types. These two types are (a) attribute variation and assignable variation. (b) random variation and deterministic variation. (c) assignable variation and random variation. ((1) assignable variation and natural variation. (e) characteristic variation and assignable variation. 12. Data has been gathered concerning the daily count of customer complaints at a local car wash for each of the past 30 days. These data are as follows. # Com laints # Com laints # Com laints 1 1 11 0 21 l 2 0 12 3 22 1 3 2 13 3 23 2 4 2 14 1 24 2 5 0 15 1 25 0 6 1 16 1 26 0 7 1 17 1 27 2 8 2 18 1 28 2 9 3 19 2 29 3 10 3 20 2 30 2 13. The goal is to use this data to establish a control chart for monitoring the number of complaints per day. In this chart, the probability that we assess that the number of complaints is unacceptable on a given day when, actually, the number of complaints is due to natural variation, is required to be 0.0027. What is the value of the upper control limit, to the nearest ten—thousandth, in this control chart? (n0 Sample # given? P= (#complaints/sample#)/30? ....not sure how to work this one out) (a) 1.2247 (b) 0.0000 (c) 21742 (d) 3.0027 (e) 5.1742 There are four costs relating to quality that have been discussed, for example, by quality management experts such as Philip Crosby. Two of these costs are the costs of prevention and external costs. The other two are (a) internal failure costs and Pareto costs. (b) internal rework costs and costs of production stoppage. (c) costs of appraisal and costs of detection. (d) internal failure costs and costs of appraisal. (e) costs of inspections and equipment maintenance costs. 14. Arthur is designing a plan for acceptance sampling, where a plan is given by deciding values for n and for c. Here, n is the number of items to sample, and c is the number such that if there are c or fewer defective items in the sample, the entire lot is accepted. Arthur will classify each item in his samples as defective or not defective. Arthur (3) is using acceptance sampling by variables. (b) knows that to pick 11 and 0, he needs only to specify values for producer’s risk and consumer’s risk. (0) knows that to pick n and 0, he needs only to specify values for the acceptable quality level and for the lot tolerance percent defective. (d) knows that to each set of values for n and c, there corresponds a unique producer’s risk and a unique consumer’s risk. (e) knows that to each set of values for n and c, there corresponds a unique operating characteristic curve. 15. Paul’s PC factory manager must choose a production process for its new product, the Proview personal computer. To help to accomplish this, Paul has gathered the following production cost data. Projected Variable Projected Annual Fixed Costs (Per Unit) ($1 Process Type Cost of Plant and Equipment {$1 Labor Material Energy Repetitive 21,000,000 125 175 150 Continuous 26,250,000 100 175 125 Mass Customization 15,000,000 150 175 175 Demand is certain and will be equal to 65,000 units per year. Each new Proview will sell for $750 per unit. Which process type, if any, will maximize the annual profit from producing the Proview personal computer? (a) The repetitive process. (b) The continuous process. (0) The mass customization process. ((1) None of the three processes being considered. (e) Not enough information is given to answer this question. 16. Total quality management’s “14 points” was pioneered by (a) Malcolm Baldrige. (b) W. Edwards Deming. (0) Joseph Juran. ((1) Philip Crosby. (e) Walter Shewhart. 17. 18. 19. In modern quality management, source inspection is frequently used. Source inspection (a) is the empowering of all employees and laborers to inspect outputs for quality at every stage of the production process. (b) is the inspection of inputs by suppliers at their source, before they are shipped for use to a firm or organization for production purposes. (c) is a concept due to Adam Smith. ((1) is the inspection of outputs at the source of their shipment, before they are shipped to wholesalers, retailers, or other customers. (e) is the inspection of workpieces by quality control specialists as they are in the process of being produced. Sam is trying to choose a pure process strategy for producing their new product, a small oak end table. Sam favors producing this table 24 hours per day, six days per week, in high volume in facilities that are organized according to the routing of the oak end table. In Sam’s opinion, these facilities should make the oak tables from scratch, i.e., not from modules produced elsewhere. What is the name of the process that Sam favors? (a) A continuous process. (b) A repetitive process. (c) An intermittent process. ((1) A mass customization process. (e) Ajob shop. Managers who provide laborers and employees things such as a means to communicate with each other and with management, positive reinforcement, and an environment with high morale are (a) engaging in the total quality management practice of employee empowerment. (b) utilizing Taguchi’s concepts of labor management. (c) engaging in Crosby’s idea of continuous, incremental improvement towards perfection. (d) utilizing the idea that it is wiser to pay the costs of prevention and appraisal of poor quality than the external costs of defective outputs. (e) using Ishikawa’s notions of employee empowerment. 10 20. 21. 22. 23. Statistical process control (a) is usually used to monitor some measurable aspect of an output of a production system after it has been produced or delivered. (b) was developed by John and Horace Dodge as a tool of monitoring production processes. (c) has as its goal to detect and signal when a process is showing natural variation. (d) has as its goal to detect and signal statistically when some measurable aspect of a process is displaying assignable variation. (e) is implemented with the aid of process charts. Changing a production system from a process focused system to a repetitive focused system is sometimes worth considering, especially if demand is increasing. But great care must be taken if such a change is made. Among other things, making such a change requires special attention to ensure that (a) quality is maintained. (b) speed of operations is maintained. (0) low output volume is maintained. (d) many alternate routings are maintained. (e) mass customization is maintained. The drastic reduction of stored inputs, including raw materials and supplied parts, and the drastic reduction of stored outputs in a production system (a) is called zero-based inventory. (b) slows down the detection of defective outputs. (c) can aid in the rectification of causes of defective outputs. (d) inhibits the rectification of causes of defective outputs. (e) is called six sigma. The waiting times for cars to pay toll at the Holland Tunnel in New York City have become excessively long. To help pinpoint the reasons for this, a New York City operations manager draws a fish—bone like chart. On certain lines of the chart, he lists various possible causes for these excessive waiting times. These include, for example, too few toll booths being open, absenteeism among toll workers, and poor training of toll workers. This chart is an example of (a) a check sheet. (b) a scatter diagram. (0) a process chart. ((1) a Pareto chart. (e) an Ishikawa diagram. 11 24. At Intel, a precision manufacturing process is used to make computer chips, To help to monitor the lengths of these computer chips, the operations manager has taken 30 samples of seven chips each. For each sample, she has measured the range in the lengths of the chips, in centimeters. The 30 sample ranges, in centimeters (cm), are as follows. Sample No. Range Sample No. Range 1 0.13 16 0.02 2 0.15 17 0.13 3 0.10 18 0.10 4 0.05 19 0.15 5 0.05 20 0.01 6 0.10 21 0.03 7 0.05 22 0.02 8 0.00 23 0.01 9 0.01 24 0.02 10 0.02 25 0.01 11 0.01 26 0.00 12 0.02 27 0.05 13 0.03 28 0.10 14 0.01 29 0.05 15 0.02 30 0.05 The goal is to establish a control chart for monitoring the ranges in the lengths in samples of seven chips each. In this chart, the operations manager would like the control limits to be approximately two standard deviations from the target value. Based upon this information, which of the following statements is M? (a) The target value in this control chart will be 1.50 cm. (b) The lower control limit in this control chart will be 0.00 cm. (0) The upper control limit in this control chart will be 0.0962 cm. ((1) The lower control limit in this control chart will be 0.05 cm. (e) The desired control chart cannot be established. 12 25. A restaurant has recorded the following data for eight recent customers 26. Customer Number i Minutes yi from Time Food No. of Trips to Kitchen xi by Ordered Until Food Arrived Waitress 1 10.50 4 2 12.75 5 3 9.25 3 4 8.00 2 5 9.75 3 6 11.00 4 7 14.00 6 8 10.75 5 The manager of the restaurant graphs the eight points (x, y), i Z 1, 2,. . ., 8, on an x-y axis. She has been concerned because customers have been waiting too long for their food and this graph is intended to contribute to her finding possible causes for this. This graph is an example of (a) a spot diagram. (b) a scatter diagram. (0) an Ishikawa diagram. (d) a cause-and-effect diagram. (e) a Pareto chart. Charts for outputs involving a high service component that show the customer flows, server activities, and customer—server interactions, with poka—yokes, are called (a) (b) (C) (d) (e) time-function mappings. service flow charts. service process matrices. service crossover charts. service blueprints. 13 27 28. 29. . A process chart mainly (a) (b) (C) (d) helps to define sequences of steps in a production process, to focus on the value added time in a process, and to pinpoint key spots to inspect for quality. helps to show the various possible causes of some observed effect in a service system, but not in a product—producing system. helps to detect patterns of poor quality in a system that produces products or provides services. is a vehicle for detecting when assignable variation is present in a given production process. helps to detect when the fraction of defective items being produced by a production system is out of control. In acceptance sampling, the largest percent of defective items in a sample at or below which the sample is still definitely considered to be a “good” sample is called (a) the lot tolerance percent defective level. (b) the acceptable tolerance point. (c) the natural acceptance level. ((1) the maximum acceptance level. (6) the acceptable quality level. Joe’s Jet Skis factory is trying to choose a minimum-cost process for producing its new Wavecruiser model jet skis. Annual demand for this new model is uncertain. It is known that it will vary between 0 and 15,000 units. Joe has gathered the following cost data for the four processes under consideration. Annualized Fixed Cost of Variable Cost Per Jet Ski Production Process Production Produced Intermittent $500,000 $100 Repetitive $580,000 $70 Continuous $540,000 $80 Mass Customization $910,000 $40 Which production process has the widest production volume range over which it is a least—cost process? (a) The intermittent process (b) The repetitive process (0) The continuous process ((1) The mass customization process (e) Not enough information is given to answer this question. 14 30. Joe’s professional trampoline company is trying to pick a minimum—cost process for producing its new Jumporama trampoline. Demand is uncertain. It will range between 0 and 20,000 units per year. Joe has gathered the following cost data. Annualized Fixed Variable Cost Production Process Cost of Production per Unit Produced Intermittent $1,000,000 $1650 Repetitive $3,000,000 $1250 Continuous $7,500,000 $650 For what range of production values, if any, does the repetitive process minimize the annual production cost? (a) For all volumes of production V such that 0 S V S 5000 (b) For all volumes of production V such that 5000 S V S 7500 (c) For all volumes of production V such that 7500 S V S 20,000 (d) For all volumes of production V such that 0 S V S 7500 (e) The repetitive process does not minimize the annual production cost at any volume of production. 15 APPENDIX I. NORMAL CURVE AREAS AND HOW TO USE THE NORMAL DISTRIBUTION TA 8L5 Id. To find the area under the normal curve, you must know how many standard deviations that point is to th'ezrlghtbfthe mean. Then, the area under the normal curve can be read directly from the normal table. For example; the total area under the normal curve for a polnt that Is 1.55 standard deviations to the right of the mean is .93943. .03 . . .51595 .55567 .59483 .63307 .67003 .70540 .73891 .77035 .79955 .82639 .85083 ‘87286 .89251 .90988 .92507 .93822 .94950 .95907 .96712 .9738! .97932 .98382 .98745 .99036 .99266 .99446 .99585 .99693 .99774 .99533 .99882 .99916 .99940 .99958 .99971 .99930 .99986 .99991 .99994 .99996 b d H b m b O N A o 51994 .55962 .5987! .63683 .67364 .70884 .74215 .77337 .80234 .82894 .85314 .87493 .89435 .91149 ‘,92647 193943 .95053 .95994 .96784 .97441 .97932 .98422 .98778 .99061 .99286 .99461 .99598 .99702 .99781 .99841 .99886 .99918 .99942 .99960 .99972 .99981 .9998? .99991 .99994 .99996 .52392 .56356 .60257 .64058 .67724 .71226 .74537 .77637 .80511 .83147 .85543 .87698 .8961? .91309 .92785 .94062 .95154 .96080 .96656 .97500 .98030 .98461 .98809 .99086 199305 .99477 .99609 .99711 .99788 .99846 .99899 .99921 .99944 '39961 .99973 .99981 .99987 .99992 .99994 .99996 It! .52790 456749 .60642 .64431 .68082 .71566 .74857 .77935 .80785 .83398 .85769 .87900 .89796 .91466 .92922 .94179 .95254 .96164 .96926 .97558 .98077 .98500 .98840 .99111 .99324 .99492 .99621 .99720 .99795 .99851 .99893 .99924 .99945 39962,. 499974 .99982 .99988 .99992 .99995 .99996 .09 .53586 .57535 .61409 ‘65173 .68793 .72240 r75490 .78524 .8132? .83891 .86214 .88298 .90147. .91774 .93189 .94408 .95449 .96327 .97062 _.'97670 .98169 .98574, .98899 .99158 .99361 .99520 .99736 .99807 .99861 .99900 .99929 .99950 .99965 .99975 .99963 .99989 .99992 .99995 .99997 Source: Frat-n Quantitative Approaches to Manaéemenl’. 4th ed.. by Richard I. Levin and Chanes A. Kirkpatrick. Capt/right O ‘978. 1975‘ 1971. 1955 I7)’ McGraw-Hlll, Inc. Used with permlsslon 01 McGraw-Hill Book Company. 163 NORMAL CURVE AREAS As an alternative 10 T31b|c 1.1. the numbers in Table 1.2 represent the mean, 72.10 onc sidc. For example, the area between the mean and 1.55 Standard deviations Area shaded Is .43943 A3 proportion of the total area away from the a point that is l.55 standard deviations to its right 17 18.43943. TABLEI.2 z .00 .01 .02 .03 .04 .05 .06 .07 .08 .09 0.0 .00000 .00399 .00798 01197 .01595 01994 .02392 .02790 .03188 .03586 0.1 .03983 .04380 .04776 .05172 .05567 05962 .06356 .06749 .07142 .07535 0.2 .07926 08317 .08706 .09095 .09483 09871 . 10257 . 10642 .11026 .1 1409 03 .11791 .12172 .12552 .12930 .13307 13683 .l4058 .14431 .14803 .15173 0.4 .15542 .15910 .16276 .16640 .17003 17364 .17724 .18082 .18439 .18793 05 .19146 .19497 .19847 .20194 .20540 20884 .21226 .21566 .21904 .22240 0.6 .22575 .22907 23237 .23565 23891 24215 .24537 .24857 25175 .25490 0.7 .25804 .261 15 .26424 .26730 .27035 .27337 .27637 .27935 28230 .28524 0.8 .28814 .29103 .29389 .29673 .29955 .30234 .3051 1 .30785 31057 .31327 0.9 .31594 .31859 32121 .32381 .32639 .32894 33147 .33398 33646 .33891 1.0 .34134 34375 .34614 .34850 35083 35314 .35543 .35769 35993 .362l4 1.1 36433 .36650 .36864 .37076 .37286 37493 .37698 37900 38100 .38298 1.2 .38493 .38686 .38877 39065 .39251 39435 .39617 .39796 39973 40147 1.3 .40320 .40490 .40658 .40824 40988 41 149 .41309 ,41466 941621 .41 174 1.4 .41924 .42073 .42220 .42364 42507' .42647 .42786 .42922 8’42. 5.0. £43189 15 .43319 .43448- .43574 .43699 43822 .43943 .44062 .44179" :14" .44408 1.6 .44520 .44630 .44738 .44845 .44950. ' .45154 .45254 485352 .45449 1.7 45543 .45637 .45728 .45818 .4590? .45ng $515; 6115 2.646327 ‘ ' 1.8 .46407 .46485 .46562 .46638- - .4613» . 131445355 145925 “4705; 1.9 337128 .47193 .47257 47320 r473 '1 47500 475533 51615 .47670 ‘10 $77.25 $47778 247831 {47.8.8.2 337,, . .48030 48077 1.48124 .48169 38214 .48257 .48300 .48341' 12183 g 43431 83506 ' _ .48574 "22 .4_8610 .48645 .48679 .48713 .3487: V; 48809 43340 ' .48899 2.3 .48928 .48956 .48983 .49010 .490 '6" .49086 .49111 .49158 24 .49180 49202 .49224 .49245 49266 49305 .49324 .4936! .325 .49379 .49396 .49413 .49430 .49446 .49477 .49492 .49520 3.:6 .49534 .49547 .49560 .49573 .49585 .49609 .49621 .49643 27 .49653 .49664 .49674 .49683 .49693 .4971 1 .49720 A9736 T28 .49744 .49752 49760 .49767 .49774 .49788 .49795 .49807 2.9 .49813 .49819 .49825 .49831 49836 .49846 .49851 .49861 3.0 49865 .49869 .49874 .49378 .49882 .49889 .49893 .49900 3.1 49903 349906 .49910 .49913 .49916 49921 49924 .49929 71431.5: $6.1 Factors 107 Computing Control Chart Limits. SAMPLE SIZE. n MEAN FACTOR. A2 UPPER RANGE. D‘ LOWER RANGE. 03 2 1.880 3.268 0 3 1.023 2.574 0 4 .729 2.282 0 5 .577 2.114 _ o 6 .433 2.004 0 7 .419 1.924 ' 0.076 3 .373 1.364 , 0.136 9' .337 1.316 0.184 10 .303 1 .777 0.223 12 .266 1.716 0.284 14 .235 1.671 0.329 16 .212 1.636 . 0.364 13 .194 1.608 0.392 20 .180 1.586 0.414 25 .153 1.541 0.459 18 . .. .. ...~.-...—. Statistical Process Control * 7c —Chart Formulas: = 1M_ x:— x_= MEI] # 0' 0;:— 7’1 UCLi = 9:: + AZELCL; = i — A21? * R-Chart Formulas: UCLR = D4§,LCLR = D31? >1< P-Chart Formulas: UCLP =j5+20'fi,LCLp =5—za. [7 * C-Chart Formulas: UCLC =E+z\/E,LCLC =E—z\/€ 19 ANSWER KEY: MAN 4504, EXAM 3 FORM B FORM A 1. C 1. C 2. C 2. C 3. C 3. D 4. C 4. A 5. D 5. C 6. B 6. E 7. B 7. E 8. B 8. B 9. C 9. E 10. A 10. A 11. D 11. E 12. E 12. B 13. D 13. B 14. E 14. A 15. C 15. C 16. B 16. C 17. A 17. D 18. A 18. B 19. A 19. B 20. D 20. B 21. A 21. C 22. C 22. A 23. E 23. D 24. E 24. E 25. B 25. D 26. E 26. E 27. A 27. C 28. E 28. B 29. B 29. A 30. B 30. A ...
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This note was uploaded on 01/28/2011 for the course MAN 4504 taught by Professor Benson during the Spring '08 term at University of Florida.

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MN3 - MAN4504 Exam 3 Do not open exam until instructed to...

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