One Sample Hypothesis Testing Cases

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Question description

Purpose of Assignment

The purpose of this assignment is to develop students' abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will learn how statistical analysis is used in predicting an election winner in the first case. In the second case, students will conduct a hypothesis test to decide whether or not a shipping plan will be profitable.

Assignment Steps

Resources: Microsoft Excel®, Case Study Scenarios, SpeedX Payment Times

Develop a 700- to 1,050-word statistical analysis based on the Case Study Scenarios and SpeedX Payment Times.

Include answers to the following:

Case 1: Election Results

  • Use 0.10 as the significance level (α).
  • Conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state.

Case 2: SpeedX

  • Use 0.10 and the significance level (α).
  • Conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude the plan will be profitable.

Format your assignment consistent with APA format.

Click the Assignment Files tab to submit your assignment.


TEAM WORK ASSIGNMENT - Spicy Wings Case

Purpose of Assignment

The purpose of this assignment is to develop students' abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will develop the ability to use statistical analysis and verify whether or not a claim is valid before advertising it.

Assignment Steps

Resources: Microsoft Excel®, Spicy Wings Case Study, Spicy Wings Data Set

Develop a 150-word statistical analysis.

- What percent of the Saturday deliveries will result in a customer receiving a free order.


o One-Sample Hypothesis Testing Cases Grading Guide QNT/561 Version 9 Applied Business Research and Statistics Copyright Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved. University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries. Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation. One-Sample Hypothesis Testing Cases Grading Guide QNT/561 Version 9 Edited in accordance with University of Phoenix® editorial standards and practices. 2 One-Sample Hypothesis Testing Cases Grading Guide QNT/561 Version 9 Individual Assignment: One-Sample Hypothesis Testing Cases Purpose of Assignment The purpose of this assignment is to develop students’ abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will learn how statistical analysis is used in predicting an election winner in the first case. In the second case, students will conduct a hypothesis test to decide whether or not a shipping plan will be profitable. Resources Required • • • Microsoft Excel® Case Study Scenarios SpeedX Payment Times Grading Guide Content Met Partially Met Not Met Total Available Total Earned 3 #/3 Develop a 700- to 1,050-word statistical analysis based on the Case Study Scenarios and SpeedX Payment Times. Include answers to the following: Case 1: Election Results • • Use 0.10 as the significance level (α). Conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state. Case 2: SpeedX • • Use 0.10 and the significance level (α). Conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude the plan will be profitable. Comments: 3 One-Sample Hypothesis Testing Cases Grading Guide QNT/561 Version 9 Writing Guidelines Met Partially Met Not Met Total Available Total Earned 2 #/2 5 #/5 The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements. Intellectual property is recognized with in-text citations and a reference page. Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper. Sentences are complete, clear, and concise. Rules of grammar and usage are followed including spelling and punctuation. Assignment Total Additional comments: # Comments: 4
Case Study – Election Results and SppedX QNT/561 Version 9 University of Phoenix Material Case Study – Election Results When an election for political office takes place, the television networks cancel regular programming and instead, provide election coverage. When the ballots are counted, the results are reported. However, for important offices such as president or senator in large states, the networks actively compete to see which will be the first to predict a winner. This is done through exit polls, wherein a random sample of voters who exit the polling booth is asked for whom they voted. From the data, the sample proportion of voters supporting the candidates is computed. Hypothesis testing is applied to determine whether there is enough evidence to infer the leading candidate will garner enough votes to win. Suppose in the exit poll from the state of Florida during the 2000 year elections, the pollsters recorded only the votes of the two candidates who had any chance of winning: Democrat Al Gore and Republican George W. Bush. In a sample of 765 voters, the number of votes cast for Al Gore was 358 and the number of votes cast for George W. Bush was 407. The network predicts the candidate as a winner if he wins more than 50% of the votes. The polls close at 8:00 P.M. Based on the sample results, conduct a one-sample hypothesis test to determine if the networks should announce at 8:01 P.M. the Republican candidate George W. Bush will win the state. Use 0.10 as the significance level (α). Case Study – SpeedX SpeedX, a large courier company, sends invoices to customers requesting payment within 30 days. The bill lists an address, and customers are expected to use their own envelopes to return their payments. Currently, the mean and standard deviation of the amount of time taken to pay bills are 24 days and 6 days, respectively. The chief financial officer (CFO) believes including a stamped self-addressed envelope would decrease the amount of time. She calculates the improved cash flow from a 2-day decrease in the payment period would pay for the costs of the envelopes and stamps. You have an MBA from the University of Phoenix, and work for SpeedX as a business analyst. One of your job duties is to run analytics and present the results to the senior management for critical decision-making. You see this as an opportunity to utilize some of the skills you gained in the Statistics course. Because of your strong understanding and background in inferential statistics, you decide to take up this important assignment. You have learned any analysis in inferential statistics starts with sampling. To test the CFO’s belief, you decide to randomly select 220 customers and propose to include a stamped self-addressed envelope with their invoices. The CFO accepts your proposal and allows you to run a pilot study. You then record the numbers of days until payment is received. Using your statistical expertise and skills you gained in the class, conduct a one-sample hypothesis test and determine if you can convince the CFO to conclude that the plan will be profitable. Use 0.10 and the significance level (α). Copyright © 2017 by University of Phoenix. All rights reserved. 1
Payment 27 24 14 39 13 31 26 33 13 23 17 24 18 34 13 23 16 32 30 29 21 19 22 14 27 20 11 20 30 24 18 21 24 18 27 27 27 21 22 23 18 17 23 26 20 20 22 21 13 36 18 25 26 19 16 28 16 20 16 14 25 14 35 17 16 19 19 17 18 22 23 22 27 23 23 21 20 18 29 32 27 15 21 26 32 20 29 25 15 21 30 24 23 14 18 22 37 24 35 29 24 17 27 15 19 12 19 21 19 21 15 17 20 21 31 19 27 19 26 26 26 23 12 20 34 21 24 20 21 16 23 13 19 18 31 29 23 28 19 19 22 24 21 23 14 25 17 22 21 18 22 15 27 14 23 25 24 24 17 16 30 24 17 27 24 17 10 25 15 13 29 21 22 11 25 30 23 18 19 18 14 21 22 17 19 23 31 26 25 15 16 28 27 22 12 25 12 21 19 26 16 21 30 16 25 13 11 13 22 28 14 21 30 19 14 31 9 14 21 28
Case Study – Spicy Wings Case Study QNT/561 Version 9 University of Phoenix Material Case Study – Spicy Wings Case Study Following his graduation from the MBA program at the University of Phoenix, John Tyler wanted to live and work in the little town of Hood. However, the community was small and there were not a lot of readily available opportunities for college graduates. Fortunately, John had some experience working in the food service industry gained in summers and throughout high school at his uncle’s restaurant in Franklin, a few miles away from the town of Hood. When John decided to leverage his experience into a small delivery and take-out restaurant located close to his home, he thought he had hit on a great idea. John would offer a limited fare consisting of the buffalo wings his uncle had perfected at his restaurant. John called his restaurant, Spicy Wings. Although success came slowly, the uniqueness of John’s offering coupled with the growth of the community made Spicy Wings a success. John’s business was pretty simple. John purchased wings locally. The wings were then seasoned and prepared in John’s restaurant. Once an order was received, John cooked the wings, which were then delivered or picked up by the customer. John’s establishment was small, and there was no place for customers to dine in the restaurant. However, his wings proved so popular that over time, John hired several employees, including three delivery drivers. Business was steady and predictable during the week, with the biggest days being home-game football Saturdays. A little over a year ago, the little town of Hood began to grow and expand. John noticed his business was beginning to suffer when other fast-food delivery restaurants opened around the town. Some of these restaurants were offering guarantees such as “30 minutes or it’s free.” John’s Spicy Wings now had to compete with fish tacos, specialty pizzas, and gourmet burgers. Most of these new restaurants, however, were dine-in establishments providing carry-out and delivery as a customer convenience. However, John was certain he would need to offer a delivery guarantee to remain competitive with the newer establishments. John was certain a delivery guarantee of “30 minutes or it’s free” could easily be accomplished every day except on football Saturdays. John thought if he could offer a 30-minute guarantee on his busiest day, he would be able to hold onto and perhaps even recover market share from the competition. However, before he was willing to commit to such a guarantee, John wanted to ensure that it was possible to meet the 30-minute promise. John knew it would be no problem for customers to pick up orders within 30 minutes of phoning them in. However, he was less confident about delivering orders to customers in 30 minutes or less. Not only would the wings need to be cooked and packaged, but the delivery time might be affected by the availability of drivers. John decided he needed to analyze the opportunity further. As a part of his analysis, John decided to take a random sample of deliveries over five different football weekends. Cooking time and packaging time were not considered in his analysis because wings were not cooked for individual orders. Rather, large numbers of wings were cooked at a single time and then packaged in boxes of 12. John decided to focus his analysis on the time required to deliver cooked and packaged wings. He collected information on the amount of time an order had to wait for a driver (the pick-up time), as well as the amount of time required to transport the wings to the customer (the drive time). The sampled information is in the Excel® file, Spicy Wings Data Set. John is not willing to offer the guarantee on football Saturdays, unless he can be reasonably sure the total time to deliver a customer’s order is less than 30 minutes, on average. John would also like to have an estimate of the actual time required to deliver a customer’s order on football Saturdays. Finally, John would like to know how likely it is the total time to make a delivery would take more than 30 minutes. Based on the sampled data, should John offer the guarantee? What percent of the Saturday deliveries would result in a customer receiving a free order? What recommendations might help John improve his Saturday delivery times? Copyright © 2017 by University of Phoenix. All rights reserved. 1
Pick-up Time 4,94 0 4,98 5,03 4,15 4,67 5,01 3,88 2,8 2,71 2,79 4,73 5,2 4,18 5,57 2,73 4,4 0 3,41 4,16 3,6 5,45 0 3,96 4,54 0 4,21 3,22 0 5,55 6,35 5,14 6,11 3,95 4,54 2,23 4,99 4,83 5,03 3,56 5,15 5,69 3,59 3,39 2,77 Drive Time Total Time 26,96 31,9 21,73 21,73 19,74 24,72 20,08 25,11 19,04 23,19 16,17 20,84 14,93 19,94 23,92 27,8 17,15 19,95 20,97 23,68 25,83 28,62 15,41 20,14 15,53 20,73 17,02 21,2 23,2 28,77 18,19 20,92 20,94 25,34 17,46 17,46 16,33 19,74 22,54 26,7 23,52 27,12 3,3 8,75 22,87 22,87 18,31 22,27 24,82 29,36 13,22 13,22 19,64 23,85 14,11 17,33 23,69 23,69 15,04 20,59 21,59 27,94 10,81 15,95 20,46 26,57 15,56 19,51 22,54 27,08 25,29 27,52 22,81 27,8 23,45 28,28 21,01 26,04 21,94 25,5 24,63 29,78 24,13 29,82 15,52 19,11 28,15 31,54 22 24,77 Column A, Pick-up Time, is the amount of time (in minutes) a packaged order had to wait to be picke up by a delivery driver. Column B, Drive Time, is the amount of time (in minutes) required to deliver the packaged order t the customer after it has been picked up by the driver. Column C, Total Time, is the total amount of time Pick-upTime + Drive Time. 0 4,25 3,97 3,1 4,13 3,81 0 3,95 5,97 4,1 4,21 3,83 3,93 4,74 0 5,61 3,8 4,46 3,7 6,06 4,83 3,16 2,5 5,63 4,41 5,26 0 3,26 5,12 5,07 0 4,14 4,75 3,67 3,02 3,47 3,3 2,77 3,2 0 0 6,27 6,4 4,67 3,41 0 4,25 15,34 20,36 13,7 21,92 22,73 16,73 21,96 16,91 22,25 18,49 14,76 24,01 8,64 20,57 17,59 20,93 17 23,17 13,58 14 17,44 21,92 20,87 7,43 13,93 20,01 19,71 19,72 17,72 19,5 16,47 18,78 15,99 24,15 24,52 18,5 18,96 17,92 11,21 22,32 15,2 17,14 16,06 24,99 12,83 20,75 19,33 15,34 24,61 17,67 25,02 26,86 20,54 21,96 20,86 28,22 22,59 18,97 27,84 12,57 25,31 17,59 26,54 20,8 27,63 17,28 20,06 22,27 25,08 23,37 13,06 18,34 25,27 19,71 22,98 22,84 24,57 16,47 22,92 20,74 27,82 27,54 21,97 22,26 20,69 14,41 22,32 15,2 23,41 22,46 29,66 16,24 20,75 23,58 4,61 4,41 5,31 2,76 4,64 4,31 4,39 0 4,93 5,14 0 6,36 2,99 3,11 3,52 2,97 2,62 5,59 5,08 4,02 0 4,93 0 0 6,44 5,01 4,41 7,63 0 5,53 4,87 0 0 3,83 5,63 0 0 4,7 0 3,68 5,36 0 0 5,59 5,93 2,86 3,6 17,87 18,95 23,54 15,15 23,23 21,95 22,47 11,58 20,03 13,06 17,48 19,89 17,26 14,13 21,42 24,67 26,47 21,36 21,29 17,99 25,58 14,15 16,34 12,29 21,97 24,75 13,92 19,18 17,15 11,83 21,49 10,82 18,62 8,91 23,38 17,37 8,9 12,29 27,79 18,96 21,22 19,49 19,52 21,25 16,09 19,37 17,12 22,48 23,36 28,85 17,91 27,87 26,26 26,86 11,58 24,96 18,2 17,48 26,25 20,25 17,24 24,94 27,64 29,09 26,95 26,37 22,01 25,58 19,08 16,34 12,29 28,41 29,76 18,33 26,81 17,15 17,36 26,36 10,82 18,62 12,74 29,01 17,37 8,9 16,99 27,79 22,64 26,58 19,49 19,52 26,84 22,02 22,23 20,72 6,19 2,51 0 3,72 6,15 3,45 4,43 0 4,27 5,34 3,31 4,49 3,02 2,64 0 0 2,5 3,66 4,11 5,03 4,57 4,76 3,95 4,04 5,4 2,91 0 2,4 3,09 6,13 4,64 7,14 5,57 2,82 5,9 4,77 6,44 3,37 3,82 4,69 0 3,02 4,64 0 4,45 4,42 4,46 19,02 15,97 21,74 22,34 21,16 22,01 22,36 22,97 15 24,78 9,4 15,24 21,07 20,98 19,67 22,96 18,82 15,54 18,02 17,2 26,12 12,22 23,28 25,02 16,38 16,71 9,75 21,67 16,68 25,22 17,55 15,86 17,02 25,08 17,57 18,85 17,13 21,08 19,51 26,74 18,48 20,32 26,25 19,1 21,83 22,12 22,43 25,21 18,48 21,74 26,06 27,31 25,46 26,79 22,97 19,27 30,12 12,71 19,73 24,09 23,62 19,67 22,96 21,32 19,2 22,13 22,23 30,69 16,98 27,23 29,06 21,78 19,62 9,75 24,07 19,77 31,35 22,19 23 22,59 27,9 23,47 23,62 23,57 24,45 23,33 31,43 18,48 23,34 30,89 19,1 26,28 26,54 26,89 4,37 3,91 5,76 0 0 2,82 5,92 4,94 5,87 4,07 7,22 5,24 0 3,71 21,01 12,04 13,02 11,39 19,78 17,14 19,84 19,92 19,49 22,32 16,59 15,48 10,6 18,4 25,38 15,95 18,78 11,39 19,78 19,96 25,76 24,86 25,36 26,39 23,81 20,72 10,6 22,11 e, is the amount of time (in rder had to wait to be picked is the amount of time (in eliver the packaged order to as been picked up by the is the total amount of time.

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Xaib
School: UIUC

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Running Head: One Sample Hypothesis Testing Cases

One Sample Hypothesis Testing Cases
Student’s Name
Course Title
Professor’s Name
7th January 2017

2

One Sample Hypothesis Testing Cases
Case Study 1 (Election Results)
In this case, the two main candidates that were likely to win the elections is George Bush
of the Republican ...

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