University of Phoenix The Payment Time and Data Set Case Study Paper Review case study documents: Payment Time Case Study and Data Set, compile and calcula
University of Phoenix The Payment Time and Data Set Case Study Paper Review case study documents: Payment Time Case Study and Data Set, compile and calculate the results. Create 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 (Please note student options as noted in the announcement posted 7/29/2019 at 12:06 a.m.):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? 100% Original work, cite references. PayTime
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Case Study Payment Time Case Study
QNT/561 Version 9
University of Phoenix Material
Case Study Payment Time Case Study
Major consulting firms such as Accenture, Ernst & Young Consulting, and Deloitte & Touche Consulting
employ statistical analysis to assess the effectiveness of the systems they design for their customers. In
this case, a consulting firm has developed an electronic billing system for a Stockton, CA, trucking
company. The system sends invoices electronically to each customers computer and allows customers to
easily check and correct errors. It is hoped the new billing system will substantially reduce the amount of
time it takes customers to make payments. Typical payment timesmeasured from the date on an
invoice to the date payment is receivedusing the trucking companys old billing system had been 39
days or more. This exceeded the industry standard payment time of 30 days.
The new billing system does not automatically compute the payment time for each invoice because there
is no continuing need for this information. The management consulting firm believes the new system will
reduce the mean bill payment time by more than 50 percent. The mean payment time using the old billing
system was approximately equal to, but no less than, 39 days. Therefore, if µ denotes the new mean
payment time, the consulting firm believes that µ will be less than 19.5 days. Therefore, to assess the
systems effectiveness (whether µ < 19.5 days), the consulting firm selects a random sample of 65
invoices from the 7,823 invoices processed during the first three months of the new systems operation.
Whereas this is the ?rst time the consulting company has installed an electronic billing system in a
trucking company, the ?rm has installed electronic billing systems in other types of companies.
Analysis of results from these other companies show, although the population mean payment time varies
from company to company, the population standard deviation of payment times is the same for different
companies and equals 4.2 days. The payment times for the 65 sample invoices are manually determined
and are given in the Excel® spreadsheet named The Payment Time Case. If this sample can be used to
establish that new billing system substantially reduces payment times, the consulting firm plans to market
the system to other trucking firms.
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