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bys in your stores by October, you place one-time orders with manufacturers in June or July of each year. You ar mand to high levels and large profits can be realized. However, new toys can also flop, leaving the company stu tant question you face is deciding how many units of a new toy should be purchased to meet anticipated sales d season, the company plans to introduce a new product called Weather Teddy. This variation of a talking teddy be ed to local television forecasters. tment has given you the following sales forecast information: Weather Teddy Sales Forecast in Units A .95 .025 A = 20,000 25 10,000 30,000 ould you need to order to have a 70% chance of meeting demand?

bys in your stores by October, you place one-time orders with manufacturers in June or July of each year. You ar mand to high levels and large profits can be realized. However, new toys can also flop, leaving the company stu tant question you face is deciding how many units of a new toy should be purchased to meet anticipated sales d season, the company plans to introduce a new product called Weather Teddy. This variation of a talking teddy be ed to local television forecasters. tment has given you the following sales forecast information: Weather Teddy Sales Forecast in Units A .95 .025 A = 20,000 25 10,000 30,000 ould you need to order to have a 70% chance of meeting demand?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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### Case Problem: Specialty Toys #### Introduction You are an inventory specialist for Specialty Toys, Inc. The company sells a variety of new and innovative children's toys. You know that the preholiday 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 the company discovers a new toy with good market potential, it chooses an October market-entry date. #### The Challenge For you to get toys in your stores by October, you place one-time orders with manufacturers in June or July of each year. You are aware that 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 the company stuck with high levels of inventory that must be sold at reduced prices. The most important question you face is deciding how many units of a new toy should be purchased to meet anticipated sales demand. If you order too few, sales will be lost; if you order too many, profits will be reduced because of low prices offered in clearance sales. #### Upcoming Season's Product For the coming season, the company plans to introduce a new product called Weather Teddy. This variation of a talking teddy bear will make weather predictions using an internal barometer when its hand is pressed. Tests show the toy’s weather predictions are quite good as compared to local television forecasters. #### Sales Forecast The sales department has given you the following sales forecast information: **Graph Analysis: Weather Teddy Sales Forecast in Units** The graph illustrates a normal distribution curve representing the forecast for Weather Teddy sales. Key features and information from the graph include: - **Probability Distribution:** - **0.025 (2.5%)** on both tails of the graph represents the extremes of the distribution (low and high sales). - **0.95 (95%)** represents the central region of the graph, indicating the high probability area where most sales will likely fall. - **Mean (µ):** The expected average sales figure is **20,000 units**. - **Range:** The distribution covers a range from approximately **10,000** to **30,000 units**. #### Decision Making To determine the appropriate ordering quantity to ensure a 70% chance of meeting demand, consider the following options: - **a.** 30,000 units - **b
Transcribed Image Text:### Case Problem: Specialty Toys #### Introduction You are an inventory specialist for Specialty Toys, Inc. The company sells a variety of new and innovative children's toys. You know that the preholiday 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 the company discovers a new toy with good market potential, it chooses an October market-entry date. #### The Challenge For you to get toys in your stores by October, you place one-time orders with manufacturers in June or July of each year. You are aware that 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 the company stuck with high levels of inventory that must be sold at reduced prices. The most important question you face is deciding how many units of a new toy should be purchased to meet anticipated sales demand. If you order too few, sales will be lost; if you order too many, profits will be reduced because of low prices offered in clearance sales. #### Upcoming Season's Product For the coming season, the company plans to introduce a new product called Weather Teddy. This variation of a talking teddy bear will make weather predictions using an internal barometer when its hand is pressed. Tests show the toy’s weather predictions are quite good as compared to local television forecasters. #### Sales Forecast The sales department has given you the following sales forecast information: **Graph Analysis: Weather Teddy Sales Forecast in Units** The graph illustrates a normal distribution curve representing the forecast for Weather Teddy sales. Key features and information from the graph include: - **Probability Distribution:** - **0.025 (2.5%)** on both tails of the graph represents the extremes of the distribution (low and high sales). - **0.95 (95%)** represents the central region of the graph, indicating the high probability area where most sales will likely fall. - **Mean (µ):** The expected average sales figure is **20,000 units**. - **Range:** The distribution covers a range from approximately **10,000** to **30,000 units**. #### Decision Making To determine the appropriate ordering quantity to ensure a 70% chance of meeting demand, consider the following options: - **a.** 30,000 units - **b
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