MATERIAL NEEDED TO COMPLETE MILESTONE:
Week 8: Milestone 3 (100 points)
In Week 8, populate the following sections in the Course Project template tutorial and example document.
The Milestone 3 deliverables are listed below.
Deliverable: Classify Various Models and Their Characteristics (50 points)
Which of the following statements is not one of the important issues defining types of arrivals in a queuing system?
Whether customers arrive one at a time or in batches
Whether customers are all essentially alike or are in separate priority classes
Whether customers have been through the system before or not
Whether customers will wait in line or not
When a customer already in line in a queuing system becomes impatient and leaves the system before starting service, what is this called?
Name one type of service discipline.
A queuing system where customers join a single line and then are served by the first available server are said to be what?
A requirement for steady state analysis of a queuing system is that _____.
The exponential distribution is _____.
The parameter l in an exponential distribution can be interpreted as a what?
Deliverable: Perform Regression Analysis to Determine a Course of Action Intended to Deal With a Business Problem (50 points)
Scenario: The station manager of a local television station is interested in predicting the amount of television (in hours) that people will watch in the viewing area. The explanatory variables are: X1 age (in years), X2 education (highest level obtained, in years), and X3 family size (number of family members in household). The multiple regression output is shown below:
StErr of Estimate
Using Microsoft Excel as well as the Excel Add-ins that you have used throughout this course, complete all parts of the question.
Show all of your work for each step. You will need to copy and paste from your Excel spreadsheets for each step as appropriate.
Refer to the scenario. Using the information above to estimate the linear regression model. Place your answer here and show your work.
Refer to the scenario. Interpret each of the estimated regression coefficients of the regression model above. Place your answer here and show your work.
Refer to the scenario. Identify and interpret the percentage of variation explained (R2) for the model. Place your answer here and show your work.
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