Category Archives: QNT 561 (NEW)

QNT 561 Entire Course NEW (With Final Guide)

QNT 561 Entire Course Updated (With Final Guide)

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QNT 561 Final Exam Guide (New, 2018) Updated

QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions Consumer Food Updated

QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions Financial Data Updated

QNT 561 Week 2 Case Study MBA Schools in Asia Pacific Updated

QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point Updated

QNT 561 Week 3 Case Study Super Fun Toys (2 Papers) Updated

QNT 561 Week 4 Case the Payment Time Updated

QNT 561 Week 5 Spicy Wings Case Study Updated

QNT 561 Week 5 Team One-Sample Hypothesis Testing (Election Results, SpeedX) Updated

QNT 561 Week 6 Signature Assignment (Consumer Food) Updated

QNT 561 Week 6 Signature Assignment (Hospital) Updated

QNT 561 Final Exam Guide (New, 2020) Updated

QNT 561 Final Exam Guide (New, 2020) Updated

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QNT 561 Final Exam Guide (New, 2020) Updated

1. James Desreumaux, VP of Human Resources of American First Banks (AFB), is reviewing the employee training programs of AFB banks. His staff randomly selected personnel files for 100 tellers in the Southeast Region and determined that their mean training time was 25 hours. Assume that the population standard deviation is 5 hours. The 95% confidence interval for the population mean of training times is
2. If x is a binomial random variable with n=10 and p=0.8, the mean value of x is______
3. According to the central limit theorem, for samples of size 64 drawn from a population with µ =800 and σ = 56, the standard deviation of the sampling distribution of sample means would equal ______
4. Life tests performed on a sample of 13 batteries of a new model indicated: (1) an average life of75 months, and (2) a standard deviation of 5 months. Other battery models, produced by similar processes, have normally distributed life spans. The 98% confidence interval for the population mean life of the new model is _________
5. A large national company is considering negotiating cellular phone rates for its employees Human Resource department would like to estimate the proportion of its employee population who own an Apple iPhone. A random sample of size 250 is taken and 40% of the sample own and iPhone.. The 95% confidence interval to estimate the population proportion is _______
6. The number of bags arriving on the baggage claim conveyor belt in a 3 minute time period would best be modeled with the ________
7. The weight of a USB flash drive is 30 grams and is normally distributed. Periodically, quanlity control inspectors at Dallas Flash Drives randomly select a sample of 17 USB flash drive. If the mean weight of the USB flash drives is too heavy or too light the machinery is shut down for adjustment; otherwise, the production process continues. The last sample showed a meanand standard deviation of 31.9 and 1.8 grams, respectively. Using a = 0.10, theappropriate decision is_______
8. Elwin Osbourne, CIO at GFS, Inc., is studying employee use of GFS e-mail for non-business communications. He plans to use a 95% confidence interval estimate of the proportion of e-mail messages that are non-business; he will accept a 0.05 error. Previous studies indicate that approximately 30% of employee e-mail is not business related. Elwin should sample _______ e-mail messages
9. The following frequency distribution was constructed for the wait times in the emergency room The frequency distribution reveals that the wait times in the emergency room are _______
10. The number of cars arriving at a toll booth in five-minute intervals is Poisson distributed with a mean of 3 cars arriving in five-minute time intervals. The probability of 5 cars arriving over a five-minute interval is ________
11. The number of finance majors within the School of Business is an example of _______
12. According to the central limit theorem, for samples of size 64 drawn from a population with µ = 800 and σ = 56, the mean of the sampling distribution of sample means would equal _______
13. Consider the following null and alternative hypotheses Ho: m ≤ 67 Ha: m > 67 These hypotheses ___________
14. A market research team compiled the following discrete probability distribution on the numberof sodas the average adult drinks each day. In this distribution, x represents the number of sodas which an adult drinks
x
P(x)
0
0.30
1
0.10
2
0.50
3
0.10
The mean (average) value of x is ______________
15. A researcher wants to determine the sample size necessary to adequately conduct a study to estimate the population mean to within 5 points. The range of population values is 80 and the researcher plans to use a 90% level of confidence. The sample size should be at least ______
16. The mean life of a particular brand of light bulb is 1200 hours. If you know that at about 95% of this brand of bulbs will last between 1100 and 1300 hours, then what is the standard deviation of the light bulbs’ life?
17. Completion time (from start to finish) of a building remodeling project is normally distributed with a mean of 200 work-days and a standard deviation of 10 work-days. To be 99% sure that we will not be late in completing the project, we should request a completion time of ______ work-day.
18. A large industrial firm allows a discount on any invoice that is paid within 30 days. Of all invoices, 10% receive the discount. In a company audit, 10 invoices are sampled at random. The probability that fewer than 3 of the 10 sampled invoices receive the discount is approximately_______________.​
19. Suppose a population has a mean of 400 and a standard deviation of 24. If a random sample of size 144 is drawn from the population, the probability of drawing a sample with a mean less than 402 is _______
20. If x is a binomial random variable with n=10 and p=0.8, what is the probability that x is equal to 4 ?
21. The normal distribution is used to test about a population mean for large samples if the population standard deviation is known. “Large” is usually defined as _______
22. Lucy Baker is analyzing demographic characteristics of two television programs, Americandol (population 1) and 60 Minutes (population 2). Previous studies indicate no difference in the ages of the two audiences (The mean age of each audience is the same.) Lucy plans to test this hypothesis using a random sample of 100 from each audience. Her null hypothesis is
23. Maureen McIlvoy, owner and CEO of a mail order business for wind surfing equipment and supplies, is reviewing the order filling operations at her warehouses. Her goal is 100% of orders shipped within 24 hours. In previous years, neither warehouse has achieved the goal, but the East Coast Warehouse has consistently out-performed the West Coast Warehouse. Her staff randomly selected 200 orders from the West Coast Warehouse (population 1) and 400 orders from the East Coast Warehouse (population 2), and reports that 190 of the West Coast Orders were shipped within 24 hours, and the East Coast Warehouse shipped 372 orders within 24 hours. Maureen’s alternate hypothesis is _______
24. Ophelia O’Brien, VP of Consumer Credit of American First Banks (AFB), monitors the default rate on personal loans at the AFB member banks. One of her standards is “no more than 5% of personal loans should be in default.” On each Friday, the default rate is calculated for a sample of 500 personal loans. Last Friday’s sample contained 30 defaulted loans. Ophelia’s null hypothesis is _______.​
25. Catherine Chao, Director of Marketing Research, is evaluating consumer acceptance of a new toothpaste package. Her staff reports that 17% of a random sample of 200 households prefers the new package to all other package designs. If Catherine concludes that 17% of all households prefer the new package, she is using _______.
26. The empirical rule says that approximately what percentage of the values would be within 2 standard deviations of the mean in a bell shaped set of data
27. Medical Wonders is a specialized interior design company focused on healing artwork. The CEO, Kathleen Kelledy claims that artwork has healing effects for patients staying in a hospital, as measured by reduced length of stay. Her current client is a children’s cancer hospital. Kathleen is interested in determining the effect of three different pieces of healing artwork on children. She chooses three paintings (a horse photo, a bright abstract, and a muted beach scene) and randomly assigns six hospital rooms to each painting. Kathleen’s null hypothesis is _____________
28. The expected (mean) life of a particular type of light bulb is 1,000 hours with a standard deviation of 50 hours. The life of this bulb is normally distributed. What is the probability that a randomly selected bulb would last fewer than 940 hours
29. The mean life of a particular brand of light bulb is 1200 hours and the standard deviation is 75 hours. Tests show that the life of the bulb is approximately normally distributed. It can be concluded that approximately 68% of the bulbs will last between _______.​
30. A market researcher is interested in determining the average income for families in San Mateo County, California. To accomplish this, she takes a random sample of 300 families from the county and uses the data gathered from them to estimate the average income for families of the entire county. This process is an example of _______.

QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point Updated

QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point Updated

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QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point Updated

Learning team paper

Purpose of Assignment

This assignment has two cases. The first case is on expansion strategy. Managers constantly have to make decisions under uncertainty. This assignment gives students an opportunity to use the mean and standard deviation of probability distributions to make a decision on expansion strategy. The second case is on determining at which point a manager should re-order a printer so he or she doesn’t run out-of-stock. The second case uses normal distribution. The first case demonstrates application of statistics in finance and the second case demonstrates application of statistics in operations management.

Assignment Steps

Resources: Microsoft Excel®, Bell Computer Company Forecasts data set, Case Study Scenarios

Write a 1,050-word report based on the Bell Computer Company Forecasts data set and Case Study Scenarios.

Include answers to the following:

Case 1: Bell Computer Company

Compute the expected value for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of maximizing the expected profit?

Compute the variation for the profit associated with the two expansion alternatives. Which decision is preferred for the objective of minimizing the risk or uncertainty?

Case 2: Kyle Bits and Bytes

What should be the re-order point? How many HP laser printers should he have in stock when he re-orders from the manufacturer?

Format your assignment consistent with APA format.

QNT 561 Week 3 Case Study Super Fun Toys (2 Papers) Updated

QNT 561 Week 3 Case Study Super Fun Toys (2 Papers) Updated

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QNT 561 Week 3 Case Study Super Fun Toys (2 Papers) Updated

Individual Paper:

Purpose of Assignment

The purpose of this assignment is for students to learn how to make managerial decisions using a case study on Normal Distribution. This case uses concepts from Weeks 1 and 2. It provides students an opportunity to perform sensitivity analysis and make a decision while providing their own rationale. This assignment also shows students that statistics is rarely used by itself. It shows tight integration of statistics with product management.

Assignment Steps
Develop a 1,050-word case study analysis including the following:
• Use the sales forecaster’s prediction to describe a normal probability distribution that can be used to approximate the demand distribution.
• Sketch the distribution and show its mean and standard deviation. Hint: To find the standard deviation, think Empirical Rule covered in Week 1.
• Compute the probability of a stock-out for the order quantities suggested by members of the management team (i.e. 15,000; 18,000; 24,000; 28,000).
• Compute the projected profit for the order quantities suggested by the management team under three scenarios: pessimistic in which sales are 10,000 units, most likely case in which sales are 20,000 units, and optimistic in which sales are 30,000 units.
One of SuperFun’s managers felt the profit potential was so great the order quantity should have a 70% chance of meeting demand and only a 30% chance of any stock- outs. What quantity would be ordered under this policy, and what is the projected profit under the three sales scenarios?

SuperFun Toys, Inc., sells a variety of new and innovative children’s toys. Management learned the pre-holiday season is the best time to introduce a new toy because many families use this time to look for new ideas for December holiday gifts. When SuperFun discovers a new toy with good market potential, it chooses an October market entry date. To get toys in its stores by October, SuperFun places one-time orders with its manufacturers in June or July of each year.
Demand for children’s toys can be highly volatile. If a new toy catches on, a sense of shortage in the marketplace often increases the demand to high levels and large profits can be realized. However, new toys can also flop, leaving SuperFun stuck with high levels of inventory that must be sold at reduced prices. The most important question the company faces is deciding how many units of a new toy should be purchased to meet anticipated sales demand. If too few are purchased, sales will be lost; if too many are purchased, profits will be reduced because of low prices realized in clearance sales.
This is where SuperFun feels that you, as an MBA student, can bring value.
For the coming season, SuperFun plans to introduce a new product called Weather Teddy. This variation of a talking teddy bear is made by a company in Taiwan. When a child presses Teddy’s hand, the bear begins to talk. A built-in barometer selects one of five responses predicting the weather conditions. The responses range from “It looks to be a very nice day! Have fun” to “I think it may rain today. Don’t forget your umbrella.” Tests with the product show even though it is not a perfect weather predictor, its predictions are surprisingly good. Several of SuperFun’s managers claimed Teddy gave predictions of the weather that were as good as many local television weather forecasters.
As with other products, SuperFun faces the decision of how many Weather Teddy units to order for the coming holiday season. Members of the management team suggested order quantities of 15,000, 18,000, 24,000, or 28,000 units. The wide range of order quantities suggested indicates considerable disagreement concerning the market potential.
Having a sound background in statistics and business, you are required to perform statistical analysis and the profit projections which is typically done by the product management group. You want to provide management with an analysis of the stock-out probabilities for various order quantities, an estimate of the profit potential, and to help make an order quantity recommendation.
SuperFun expects to sell Weather Teddy for $24 based on a cost of $16 per unit. If inventory remains after the holiday season, SuperFun will sell all surplus inventories for $5 per unit. After reviewing the sales history of similar products, SuperFun’s senior sales forecaster predicted an expected demand of 20,000 units with a 95% probability that demand would be between 10,000 units and 30,000 units.
One of SuperFun’s managers felt the profit potential was so great the order quantity should have a 70% chance of meeting demand and only a 30% chance of any stock- outs. What quantity would be ordered under this policy, and what is the projected profit under the three sales scenarios?

QNT 561 Week 4 Case the Payment Time Updated

QNT 561 Week 4 Case the Payment Time Updated

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QNT 561 Week 4 Case the Payment Time Updated

Individual Paper

Purpose of Assignment

The purpose of the assignment is to develop students’ abilities in using datasets to apply the concepts of sampling distributions and confidence intervals to make management decisions.

Assignment Steps

Resources: Microsoft Excel®, The Payment Time Case Study, The Payment Time Case Data Set

Review the Payment Time Case Study and Data Set.

Develop a 700-word report including the following calculations and using the information to determine whether the new billing system has reduced the mean bill payment time:

• Assuming the standard deviation of the payment times for all payments is 4.2 days, construct a 95% confidence interval estimate to determine whether the new billing system was effective. State the interpretation of 95% confidence interval and state whether or not the billing system was effective.

• Using the 95% confidence interval, can we be 95% confident that µ ≤ 19.5 days?

• Using the 99% confidence interval, can we be 99% confident that µ ≤ 19.5 days?

• If the population mean payment time is 19.5 days, what is the probability of observing a sample mean payment time of 65 invoices less than or equal to 18.1077 days?

Format your assignment consistent with APA format.

Please plagiarism free, she is acting to show how we got to the numbers we got so show work. Must have excel worksheet also.

QNT 561 Week 5 Spicy Wings Case Study Updated

QNT 561 Week 5 Spicy Wings Case Study Updated

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QNT 561 Week 5 Spicy Wings Case Study Updated

Individual Paper

• 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 700-word statistical analysis.

Use descriptive statistics to compute a measure of performance John can use to analyze his delivery performance. Find the following for your measures:

• Mean

• Standard deviation

• Sample size

• Five-number summary on the total time

Conduct a formal hypothesis testing to help John decide whether to offer the delivery guarantee or not.

Estimate the probability of an order taking longer than 30 minutes.

Make a recommendation in a short narrative including the following:

• 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?

Format your assignment consistent with APA format.