Question.2934 - Drive-Thru Service Times at McDonald’sDiscussion Questions: 1.) After returning from the training session at Hamburger University, a McDonald’s store owner selected a random sample of 362 drive-thru customers and carefully measured the time it took from when a customer entered the McDonald’s property until the customer received the order at the drive-thru window. These data are in the file called McDonald’s Drive-Thru Waiting Time. Note the owner selected some customers during the breakfast period, during lunch, and others during dinner. Construct any appropriate graphs and charts that will effectively display these drive-thru data. Prepare a short discussion indicating the conclusions that this store owner might reach after reviewing the graphs and charts you have prepared. 2.) Referring to question 1, suppose the manager comes away with the conclusion that his store is not meeting the 90-second customer service goal. As a result, he plans to dig deeper into the problem by collecting more data from the drive-thru process. Discuss what other measures you would suggest the manager collect. Discuss how these data could be of potential value in helping the store owner understand his problem. a.) the total time from arrival on the property to departure from the drive-thru window b.) the time from when customers place the order until they receive their order and exit the drive- thru process. c.) the number of cars in the line when the sampled vehicle enters the drive-thru process. d.) Using the data that you have collected, construct appropriate graphs and charts to describe these data. Write a short report discussing the data.Save-More PharmaciesSave-More has the opportunity to purchase a 6,780 person customer base from Hubbard Pharmacy. Based on previous acquisitions, Heidi believes that if 70% or more of the customers will make the switch, then the deal is favorable to Save-More. However, if 60% or less make the move to Save-More, then the deal will be a bad one and she would recommend against it. It has been suggested that if 15 or more of the 20 customers indicate that they would make the switch, then Save-More should go ahead with the purchase. Otherwise, it should decline the deal or negotiate a lower purchase price. It was agreeable as long as only these 20 customers would be told about the potential sale. Required Tasks:1.) Compute the probability that the sampling plan will provide a result that suggests that Save-More should reject the deal even if the true proportion of all customers who would switch is actually 0.70. 2.) Compute the probability that the sampling plan will provide a result that suggests that Save-More should accept the deal even if the true proportion of all customers who would switch is actually only 0.60. 3.) Write a short report to Heidi outlining the sampling plan, the assumptions on which the evaluation of the sampling plan has been based, and the conclusions regarding the potential effectiveness of the sampling plan. The report should make a recommendation about whether Heidi should go through with the idea of using the sampling plan.Credit Data, Inc.Credit Data, Inc., has been monitoring the amount of time its bill collectors spend on calls that produce contacts with customers. Management is interested in the distribution of time a collector spends on each call in which he or she initiates contact, informs a consumer about an outstanding debt, discusses a payment plan and receives payments by phone. Credit Data is mostly interested in how quickly a collector can initiate and end a conversation to move on to the next call. For employees of Credit Data, time is money in the sense that one account may require one call and 2 minutes to collect, whereas another account may take 5 calls and 10 minutes per call to collect. The company has discovered that the time collectors spend talking to consumers about accounts is approximately by a normal distribution with a mean of 8 minutes and standard deviation of 2.5 minutes. The managers believe the mean is too high and should be reduced by more efficient phone call methods. Specifically, they wish to have no more than 10% of all calls require more than 10.5 minutes. Required Tasks: 1.) Assuming that training can affect the average time but not the standard deviation, the managers are interested in knowing to what level the mean call time needs to be reduced in order to meet the 10% requirement. 2.) Assuming that the standard deviation can be affected by training but the mean time will remain at 8 minutes, to what level must the standard deviation be reduced in order to meet the 10% requirement. 3.) If nothing is done, what percent of all calls can be expected to require more than 10.5 minutes?
Answer Below:
Drive-Thru xxxxxxx Times xx McDonald xxxxx sDiscussion xxxxxxxxx After xxxxxxxxx from xxx training xxxxxxx at xxxxxxxxx University x McDonald xxxxx s xxxxx owner xxxxxxxx a xxxxxx sample xx drive-thru xxxxxxxxx and xxxxxxxxx measured xxx time xx took xxxx when x customer xxxxxxx the xxxxxxxx rsquo x property xxxxx the xxxxxxxx received xxx order xx the xxxxxxxxxx window xxxxx data xxx in xxx file xxxxxx McDonald xxxxx s xxxxxxxxxx Waiting xxxx Note xxx owner xxxxxxxx some xxxxxxxxx during xxx breakfast xxxxxx during xxxxx and xxxxxx during xxxxxx Construct xxx appropriate xxxxxx and xxxxxx that xxxx effectively xxxxxxx these xxxxxxxxxx data xxxxxxx a xxxxx discussion xxxxxxxxxx the xxxxxxxxxxx that xxxx store xxxxx might xxxxx after xxxxxxxxx the xxxxxx and xxxxxx you xxxx prepared xxxxxxxx The xxxxx below xxxxx the xxxxxxx statistics xx the xxxxxxxxxx Waiting xxxx in xxxxxxx at xxxxxxxx rsquo x for xxxxxxxxx periods xxxxxxxxx Time xxxxx Time xxxxxx TimeCustomer xxxxxxx Time xxxxxxx Breakfas x TimeLunch xxxxxxxxxx Time xxxxxxx Median xxx Min xxxxxxxx Deviation xxxxx The xxxxxxx Average xxxxxxx Time xx seconds xxx customer xx almost xxxxxxx seconds xxxxxxxxx TimeLunch xxxxxxxxxx Time xxxxxxx Customer xxxxxxx Time xxxxxxx Average xxxxxx Average xxxxxxxxxx The xxxxxxx Waiting xxxx AWT xxx customer xxxxx marginally xxxxxx the xxxxx time xx however xxxxxxx roughly xx be xxxxxx minutes xxx both xxxxxxxxx and xxxxxx time xxxx the xxxxx statistics xxxx indicated xxxx small xxxxxxxxxx in xxx Waiting xxxx WT xxx all xxx periods xxxxxxxx Deviation xxx the xx for xxx the xxxxxxx is xxxxxxxxxxxxx equal xx minute xxxxxxx which xxxxxxx that xxx service xxxxxxx a xxxxxxxxxx pattern xxxxxxxxxx the xxxxxxxxxx periods xxxxxxxxx to xxxxxxxx suppose xxx manager xxxxx away xxxx the xxxxxxxxxx that xxx store xx not xxxxxxx the xxxxxxx customer xxxxxxx goal xx a xxxxxx he xxxxx to xxx deeper xxxx the xxxxxxx by xxxxxxxxxx more xxxx from xxx drive-thru xxxxxxx Discuss xxxx other xxxxxxxx you xxxxx suggest xxx manager xxxxxxx Discuss xxx these xxxx could xx of xxxxxxxxx value xx helping xxx store xxxxx understand xxx problem x the xxxxx time xxxx arrival xx the xxxxxxxx to xxxxxxxxx from xxx drive-thru xxxxxx b xxx time xxxx when xxxxxxxxx place xxx order xxxxx they xxxxxxx their xxxxx and xxxx the xxxxxx thru xxxxxxx c xxx number xx cars xx the xxxx when xxx sampled xxxxxxx enters xxx drive-thru xxxxxxx d xxxxx the xxxx that xxx have xxxxxxxxx construct xxxxxxxxxxx graphs xxx charts xx describe xxxxx data xxxxx a xxxxx report xxxxxxxxxx the xxxx Save-More xxxxxxxxxxxxxxxxxxx has xxx opportunity xx purchase x person xxxxxxxx base xxxx Hubbard xxxxxxxx Based xx previous xxxxxxxxxxxx Heidi xxxxxxxx that xx or xxxx of xxx customers xxxx make xxx switch xxxx the xxxx is xxxxxxxxx to xxxxxxxxx However xx or xxxx make xxx move xx Save-More xxxx the xxxx will xx a xxx one xxx she xxxxx recommend xxxxxxx it xx has xxxx suggested xxxx if xx more xx the xxxxxxxxx indicate xxxx they xxxxx make xxx switch xxxx Save-More xxxxxx go xxxxx with xxx purchase xxxxxxxxx it xxxxxx decline xxx deal xx negotiate x lower xxxxxxxx price xx was xxxxxxxxx as xxxx as xxxx these xxxxxxxxx would xx told xxxxx the xxxxxxxxx sale xxxxxxxx Tasks xxxxxxx the xxxxxxxxxxx that xxx sampling xxxx will xxxxxxx a xxxxxx that xxxxxxxx that xxxxxxxxx should xxxxxx the xxxx even xx the xxxx proportion xx all xxxxxxxxx who xxxxx switch xx actually xxxx basis xxx sampling xxxx we xxxx If xxxxxxxxx make xxx switch xxxx the xxxx should xxxxxx Or xx only xxxxxxxxx make xxx switch xxxx the xxxx should xxx HAPPEN xxxxxxx in xxxxxx we xxxx If xxxxxxxxx make x switch xxxx the xxxx should xxxxxx Or xx only xxxxxxxxx make x switch xxxx the xxxx should xxx HAPPEN xxxxxxxxx the xxxxx number xx customers xxx making x switch xxxxxx - xxxxx the xxxxxxxxxxx that xxx sampling xxxx will xxxxxxx a xxxxxx that xxxxxxxx that xxxxx More xxxxxx reject xxx deal xxxx if xxx true xxxxxxxxxx of xxx customers xxx would xxxxxx is xxxxxxxx is xx follows xxxxxxxxxxx that xxxxxxxx plan xxxx provide x result xxxxx would xxxxxx the xxxx i x which xx quite xxxx a xxxxxxxxxxx Compute xxx probability xxxx the xxxxxxxx plan xxxx provide x result xxxx suggests xxxx Save-More xxxxxx accept xxx deal xxxx if xxx true xxxxxxxxxx of xxx customers xxx would xxxxxx is xxxxxxxx only xxxx again xxxxx the xxxxxxxx plan xx have xx customers xxxx the xxxxxx then xxx deal xxxxxx HAPPEN xx If xxxx customers xxxx the xxxxxx then xxx deal xxxxxx NOT xxxxxx However xx actual xx have xx customers xxxx a xxxxxx then xxx deal xxxxxx HAPPEN xx If xxxx customers xxxx a xxxxxx then xxx deal xxxxxx NOT xxxxxx Therefore xxx total xxxxxx of xxxxxxxxx not xxxxxx a xxxxxx equals x Hence xxx probability xxxx the xxxxxxxx plan xxxx provide x result xxxx suggests xxxx Save- xxxx should xxxxxx the xxxx even xx the xxxx proportion xx all xxxxxxxxx who xxxxx switch xx actually xx as xxxxxxx Probability xxxx sampling xxxx will xxxxxxx a xxxxxx which xxxxx accept xxx deal x e xxxxx is xxxxx high x probability xxxxx a xxxxx report xx Heidi xxxxxxxxx the xxxxxxxx plan xxx assumptions xx which xxx evaluation xx the xxxxxxxx plan xxx been xxxxx and xxx conclusions xxxxxxxxx the xxxxxxxxx effectiveness xx the xxxxxxxx plan xxx report xxxxxx make x recommendation xxxxx whether xxxxx should xx through xxxx the xxxx of xxxxx the xxxxxxxx plan xxx sampling xxxx decided xx very xxxxxxxxx from xxx actual xxxxxx that xxxxx has xxxxxxxxx the xxxxxxxxxx switch xx customers xxx sampling xxxx says xx of xxxxxxxxx switch xxxx the xxxx should xx accepted xxxxxxxxx not xxxx criterion xx accepting xxx deal xx much xxxx stringent xxxx the xxxxxx belief xx reduce xxx sampling xxxxx which xxxxx the xxxxx of xxx current xxxxxxxx plan xxxxx should xxx go xxxxx with xxx current xxxxxxxx plan xx the xxxxxxxxxxx of xxxxxxxxx the xxxx when xx actual xx should xxxx been xxxxxxxx is xx This xxxxxxxx is xxxxxxxxx to xxxx error xx statistics xxxxx we xxxx to xxxxxx the xxxx hypothesis xxxx it xx actually xxxx and xx tend xx reduce xx to xxxxxxx extent xxxxxxxx Credit xxxx Inc xxxxxx Data xxx has xxxx monitoring xxx amount xx time xxx bill xxxxxxxxxx spend xx calls xxxx produce xxxxxxxx with xxxxxxxxx Management xx interested xx the xxxxxxxxxxxx of xxxx a xxxxxxxxx spends xx each xxxx in xxxxx he xx she xxxxxxxxx contact xxxxxxx a xxxxxxxx about xx outstanding xxxx discusses x payment xxxx and xxxxxxxx payments xx phone xxxxxx Data xx mostly xxxxxxxxxx in xxx quickly x collector xxx initiate xxx end x conversation xx move xx to xxx next xxxx For xxxxxxxxx of xxxxxx Data xxxx is xxxxx in xxx sense xxxx one xxxxxxx may xxxxxxx one xxxx and xxxxxxx to xxxxxxx whereas xxxxxxx account xxx take xxxxx and xxxxxxx per xxxx to xxxxxxx The xxxxxxx has xxxxxxxxxx that xxx time xxxxxxxxxx spend xxxxxxx to xxxxxxxxx about xxxxxxxx is xxxxxxxxxxxxx by x normal xxxxxxxxxxxx with x mean xx minutes xxx standard xxxxxxxxx of xxxxxxx The xxxxxxxx believe xxx mean xx too xxxx and xxxxxx be xxxxxxx by xxxx efficient xxxxx call xxxxxxx Specifically xxxx wish xx have xx more xxxx of xxx calls xxxxxxx more xxxx minutes xxxxxxxx Assuming xxx time xxxxx by xxx collector xxxx a xxxx be x minutes xxxxx that x N xxxxx sigma xxxxx that xxxxx minutes xxx sigma xxxxxxx Required xxxxx Assuming xxxx training xxx affect xxx average xxxx but xxx the xxxxxxxx deviation xxx managers xxx interested xx knowing xx what xxxxx the xxxx call xxxx needs xx be xxxxxxx in xxxxx to xxxx the xxxxxxxxxxx Here xx have xx find xxx new xxxxxxx time xxxxx which xxxx fulfill xxx requirement xxxxx no xxxx than xx the xxxxx calls xxxxxxx more xxxx minutes xx other xxxxx we xxxx been xxxxx a xxxxxxxxx where xxxxx P x amp xx or x X xxx gt xx now xxxxxxxxxxx the xxxxxxxxxxxxx Z-score xxx X x X- xxxxx sigma x - xxxxx P x amp xx - x Z x micro xxxxx here xx is xxxxx that x X xxx gt xxx equation xxxxxxx - x Z x micro x Z x micro xxx value xx Z-score xxxxxxxxxxxxx to xxx area xxxxx the xxxxx equal xx is xxxxxxxxx we xxx Z x micro xxxxxxx for xxxxx we xxx micro xxxxxxx Therefore xxx managers xxxxxx consider xxxxxxxx the xxxx time xxxxx to xxxxxxx from xxxxxxx to xxxxxxx the xxxxxx target xxxxxxxx that xxx standard xxxxxxxxx can xx affected xx training xxx the xxxx time xxxx remain xx minutes xx what xxxxx must xxx standard xxxxxxxxx be xxxxxxx in xxxxx to xxxx the xxxxxxxxxxx Here xx have xx find xxx new xxxxxxxx deviation xxxx sigma xxxxx will xxxxxxx the xxxxxxxxxxx where xx more xxxx of xxx total xxxxx require xxxx than xxxxxxx In xxxxx words xx have xxxx given x condition xxxxx ndash x X xxx gt xx P x amp xx So xxx calculating xxx corresponding xxxxxxx for x Z xx micro xxxxx Z x sigma x X xxx gt x P x - xxxxx Since xxxx it xx given xxxx P x amp xx the xxxxxxxx becomes x P x - xxxxx P x - xxxxx The xxxxx of xxxxxxx corresponding xx the xxxx under xxx curve xxxxx to xx therefore xx get x - xxxxx Solving xxx sigma xx get xxxxx minutes xxxxxxxxx the xxxxxxxx should xxxxxxxx reducing xxx standard xxxxxxxxx time xxxxx to xxxxxxx from xxxxxxx to xxxxxxx the xxxxxxxxxxx for xx nothing xx done xxxx percent xx all xxxxx can xx expected xx require xxxx than xxxxxxx Here xx have xx find x X xxx gt xxxxxxxxxxx the xxxxxxxxxxxxx Z-score xxx X x X- xxxxx sigma x - x Now xx have xx find xxx probability xxxx P x amp xx - x Z x Refer xx the xxxxxx tables xxx Z-score xxxxx equal xx Therefore x X xxx gt xxxxx of xxx calls xxx be xxxxxxxx to xxxxxxx more xxxx minutes xxxx the x distribution xx normally xxxxxxxxxxx with x mean xxxxx of xxxxxxx and x standard xxxxxxxxx sigma xx minutesMore Articles From Statistics
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