About Us Take My Online Class

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 xxxxxxxxxxx Questions xxxxx returning xxxx the xxxxxxxx session xx Hamburger xxxxxxxxxx a xxxxxxxx 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 s xxxxxxxx until xxx customer xxxxxxxx the xxxxx at xxx drive-thru xxxxxx These xxxx are xx the xxxx called xxxxxxxx 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 s xxx different xxxxxxx Breakfast xxxx Lunch xxxx Dinner xxxxxxxxxxxx Waiting xxxx Seconds xxxxxxxx t xxxxxxxxx TimeDinner xxxx Average xxxxxx Max xxx Standard xxxxxxxxx Count xxx Overall xxxxxxx Waiting xxxx in xxxxxxx per xxxxxxxx is xxxxxx minutes xxxxxxx Breakfast xxxxxxxxx TimeDinner xxxx Average xxxxxxxx Waiting xxxx Seconds xxxxxxx Linear xxxxxxx Highlights xxx Average xxxxxxx Time xxx per xxxxxxxx falls xxxxxxxxxx during xxx Lunch xxxx it xxxxxxx remains xxxxxxx to xx around xxxxxxx for xxxx Breakfast xxx Dinner xxxx Also xxx other xxxxxxxxxx have xxxxxxxxx very xxxxx variations xx the xxxxxxx Time xx for xxx the xxxxxxx Standard xxxxxxxxx for xxx WT xxx all xxx periods xx approximately xxxxx to xxxxxx seconds xxxxx reflect xxxx the xxxxxxx follows x consistent xxxxxxx throughout xxx respective xxxxxxx Referring xx question xxxxxxx the xxxxxxx comes xxxx with xxx conclusion xxxx his xxxxx is xxx meeting xxx -second xxxxxxxx service xxxx As x result xx plans xx dig xxxxxx into xxx problem xx collecting xxxx data xxxx the xxxxxxxxxx process xxxxxxx what xxxxx measures xxx would xxxxxxx the xxxxxxx collect xxxxxxx how xxxxx data xxxxx be xx potential xxxxx in xxxxxxx the xxxxx owner xxxxxxxxxx his xxxxxxx a xxx total xxxx from xxxxxxx on xxx property xx departure xxxx the xxxxxxxxxx window x the xxxx from xxxx customers xxxxx the xxxxx until xxxx receive xxxxx order xxx exit xxx drive- xxxx process x the xxxxxx of xxxx in xxx line xxxx the xxxxxxx vehicle xxxxxx the xxxxxxxxxx process x Using xxx data xxxx you xxxx collected xxxxxxxxx appropriate xxxxxx and xxxxxx to xxxxxxxx these xxxx Write x short xxxxxx discussing xxx data xxxxxxxxx PharmaciesSave-More xxx the xxxxxxxxxxx to xxxxxxxx a xxxxxx customer xxxx from xxxxxxx Pharmacy xxxxx on xxxxxxxx acquisitions xxxxx believes xxxx if xx more xx the xxxxxxxxx will xxxx the xxxxxx then xxx deal xx favorable xx Save-More xxxxxxx if xx less xxxx the xxxx to xxxxxxxxx then xxx deal xxxx be x bad xxx and xxx would xxxxxxxxx against xx It xxx been xxxxxxxxx that xx or xxxx of xxx customers xxxxxxxx that xxxx would xxxx the xxxxxx then xxxxxxxxx should xx ahead xxxx the xxxxxxxx Otherwise xx should xxxxxxx the xxxx or xxxxxxxxx a xxxxx purchase xxxxx It xxx agreeable xx long xx only xxxxx customers xxxxx be xxxx about xxx potential xxxx Required xxxxx Compute xxx probability xxxx the xxxxxxxx plan xxxx provide x result xxxx suggests xxxx Save-More xxxxxx reject xxx deal xxxx if xxx true xxxxxxxxxx of xxx customers xxx would xxxxxx is xxxxxxxx Here 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 reject xxx deal x e xxxxx is xxxxx high x probability 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 Here xxxxx 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 accept 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 Write x short xxxxxx to xxxxx outlining xxx sampling xxxx the xxxxxxxxxxx on xxxxx the xxxxxxxxxx of xxx sampling xxxx has xxxx based xxx the xxxxxxxxxxx regarding xxx potential xxxxxxxxxxxxx of xxx sampling xxxx The xxxxxx should xxxx a xxxxxxxxxxxxxx about xxxxxxx Heidi xxxxxx go xxxxxxx with xxx idea xx using xxx sampling xxxx The xxxxxxxx plan xxxxxxx is xxxx different xxxx the xxxxxx belief xxxx Heidi xxx regarding xxx percentage xxxxxx of xxxxxxxxx The xxxxxxxx plan xxxx if xx customers xxxxxx then xxx deal xxxxxx be xxxxxxxx otherwise xxx This xxxxxxxxx of xxxxxxxxx the xxxx is xxxx more xxxxxxxxx than xxx actual xxxxxx to xxxxxx any xxxxxxxx error xxxxx forms xxx basis xx the xxxxxxx sampling xxxx Heidi xxxxxx not xx ahead xxxx the xxxxxxx sampling xxxx as xxx probability xx rejecting xxx deal xxxx in xxxxxx it xxxxxx have xxxx accepted xx or xxxx scenario xx analogous xx Type xxxxx in xxxxxxxxxx where xx tend xx reject xxx null xxxxxxxxxx when xx is xxxxxxxx true xxx we xxxx to xxxxxx it xx maximum xxxxxx possible xxxxxx Data xxx Credit xxxx Inc xxx been xxxxxxxxxx the xxxxxx of xxxx its xxxx collectors xxxxx on xxxxx that xxxxxxx contacts xxxx customers xxxxxxxxxx is xxxxxxxxxx in xxx distribution xx time x collector xxxxxx on xxxx call xx which xx or xxx initiates xxxxxxx informs x consumer xxxxx an xxxxxxxxxxx debt xxxxxxxxx a xxxxxxx plan xxx receives xxxxxxxx by xxxxx Credit xxxx is xxxxxx interested xx how xxxxxxx a xxxxxxxxx can xxxxxxxx and xxx a xxxxxxxxxxxx to xxxx on xx the xxxx call xxx employees xx Credit xxxx time xx money xx the xxxxx that xxx account xxx require xxx call xxx minutes xx collect xxxxxxx another xxxxxxx may xxxx calls xxx minutes xxx call xx collect xxx company xxx discovered xxxx the xxxx collectors xxxxx talking xx consumers xxxxx accounts xx approximately xx a xxxxxx distribution xxxx a xxxx of xxxxxxx and xxxxxxxx deviation xx minutes xxx managers xxxxxxx the xxxx is xxx high xxx should xx reduced xx more xxxxxxxxx phone xxxx methods xxxxxxxxxxxx they xxxx to xxxx no xxxx than xx all xxxxx require xxxx than xxxxxxx Solution xxxxxxxx the xxxx taken xx the xxxxxxxxx over x call xx X xxxxxxx Given xxxx X x where xxxx minutes xxx minutes xxxxxxxx Tasks xxxxxxxx that xxxxxxxx can xxxxxx the xxxxxxx time xxx not xxx standard xxxxxxxxx the xxxxxxxx are xxxxxxxxxx in xxxxxxx to xxxx level xxx mean xxxx time xxxxx to xx reduced xx order xx meet xxx requirement xxxx we xxxx to xxxx the xxx average xxxx 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 x X xx or x X xx So xxx calculating xxx corresponding xxxxxxx for x Z xx Z x P x gt x P x - xxxxx here xx is xxxxx that x X xx the xxxxxxxx becomes x P x - x Z x The xxxxx of xxxxxxx corresponding xx the xxxx under xxx curve xxxxx to xx therefore xx get x - xxxxxxx for xx get xxxxxxx Therefore xxx managers xxxxxx consider xxxxxxxx the xxxx time xx minutes xxxx minutes xx achieve xxx stated xxxxxx Assuming xxxx the xxxxxxxx deviation xxx be xxxxxxxx by xxxxxxxx but xxx mean xxxx will xxxxxx at xxxxxxx to xxxx level xxxx the xxxxxxxx deviation xx reduced xx order xx meet xxx requirement xxxx we xxxx to xxxx the xxx standard xxxxxxxxx time 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 P x gt xx P x gt xx now xxxxxxxxxxx the xxxxxxxxxxxxx Z-score xxx X x X- x - x X xx - x Z x Since xxxx it xx given xxxx P x gt xxx equation xxxxxxx - x Z x P x - xxx value xx Z-score xxxxxxxxxxxxx to xxx area xxxxx the xxxxx equal xx is xxxxxxxxx we xxx Z x Solving xxx we xxx minutes xxxxxxxxx the xxxxxxxx should xxxxxxxx reducing xxx standard xxxxxxxxx time xx minutes xxxx minutes xx achieve xxx requirement xxx If xxxxxxx is xxxx what xxxxxxx of xxx calls xxx be xxxxxxxx to xxxxxxx more xxxx minutes xxxx we xxxx to xxxx P x gt xxxxxxxxxxx the xxxxxxxxxxxxx Z-score xxx X x X- x - x Now xx have xx find xxx probability xxxx P x gt x P x - xxxxx to xxx normal xxxxxx for xxxxxxx value xxxxx to xxxxxxxxx P x gt xxxxx of xxx calls xxx be xxxxxxxx to xxxxxxx more xxxx minutes xxxx the x distribution xx normally xxxxxxxxxxx with x mean xx minutes xxx a xxxxxxxx deviation xx minutes

More Articles From Statistics

TAGLINE HEADING

More Subjects Homework Help