1. Statistical process control, hypothesis testing, and control charts Consumers value prompt service when they order takeout or delivered pizza, and pizza restaurants compete for customers by making time promises. Papa John's, for instance, offers a 10-minute takeout guarantee. Domino's advertises a 30-minute delivery time. Suppose that the quality control manager at a nationwide pizza chain defines this production variable: An order is processed on time or late. Every night, a random sample of pizza orders is selected, and data are collected on the production variable for each order in the sample. To detect a change in the number of orders that are late, the quality control manager uses Based on the control chart, the quality control manager decides that the variation in output is due to assignable causes. Consequently, the manager concludes that the production process is ; it is Statistical procedures for process control use a hypothesis-testing framework. The null and alternative hypotheses are the states of the production process, and the decision to continue or to adjust the production process is based on sample data. If the null hypothesis is true, the quality control manager has made a

Understanding Business
12th Edition
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Author:William Nickels
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1. Statistical process control, hypothesis testing, and control charts
Consumers value prompt service when they order takeout or delivered pizza, and pizza restaurants compete for customers by making time promises.
Papa John's, for instance, offers a 10-minute takeout guarantee. Domino's advertises a 30-minute delivery time.
Suppose that the quality control manager at a nationwide pizza chain defines this production variable: An order is processed on time or late. Every
night, a random sample of pizza orders is selected, and data are collected on the production variable for each order in the sample.
To detect a change in the number of orders that are late, the quality control manager uses
Based on the control chart, the quality control manager decides that the variation in output is due to assignable causes. Consequently, the manager
concludes that the production process is
; it is
Statistical procedures for process control use a hypothesis-testing framework. The null and alternative hypotheses are the states of the production
process, and the decision to continue or to adjust the production process is based on sample data.
If the null hypothesis is true, the quality control manager has made a
Transcribed Image Text:1. Statistical process control, hypothesis testing, and control charts Consumers value prompt service when they order takeout or delivered pizza, and pizza restaurants compete for customers by making time promises. Papa John's, for instance, offers a 10-minute takeout guarantee. Domino's advertises a 30-minute delivery time. Suppose that the quality control manager at a nationwide pizza chain defines this production variable: An order is processed on time or late. Every night, a random sample of pizza orders is selected, and data are collected on the production variable for each order in the sample. To detect a change in the number of orders that are late, the quality control manager uses Based on the control chart, the quality control manager decides that the variation in output is due to assignable causes. Consequently, the manager concludes that the production process is ; it is Statistical procedures for process control use a hypothesis-testing framework. The null and alternative hypotheses are the states of the production process, and the decision to continue or to adjust the production process is based on sample data. If the null hypothesis is true, the quality control manager has made a
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