ASSIGNMENT 1 Due Today 08/10/18

For this discussion, you will assess the use of various support decision tools and explain why outliers are sometimes called influential observations. Discuss what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included. Will this necessarily happen when a point is an outlier? You are required to give at least two examples in your response.

ASSIGNMENT 2  Due Tomorrow 08/11/18

Complete Problem 50 in Chapter 10 on page 477.

10-55) A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

a. Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

b. Interpret your best-fitting equation.

c. Using the best-fitting equation, predict sales during a month in which the price is $470.

In the discussion area, attach the Excel document showing work.

Assignment 3 Due Tomorrow 08/11/10

Multiple Regression

For this assignment, you are required to complete Problem 64 (p. 593) in Chapter 12 of your textbook. Use the appropriate Excel file templates from www.cengagebrain.com. Once complete, post your Excel Document in Waypoint. Show all work.

23-64) Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file Week 4 Assignment Chapter 12 Problem 64. Use regression to fit the following model to these data:
Yt = a + b1Yt−1 + b2Pt + et
This equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term.

a. If the price of a portrait during month 21 is $10, what would you predict for sales in month 21?

b. Does there appear to be a problem with autocorrelation of the residual? Explain your answer.

ASSIGNMENT 4 Due 08/12/18

After reviewing the optimization models in the text, select one model that you can use to improve a specific business process. Explain your reasoning.  You can work with a business process at your current job, previous jobs, think of a hypothetical situation (i.e. how FedEx may be routing their shipments or how a call center may be scheduling their employees), or use the scenario from the discussion in Week 1.

**YOU CAN USE ANY BUISNESS YOU WANT THAT HAS TO DO WITH LOGISTICS LIKE A WAREHOUSE.

ASSIGNMENT 1 Due Today 08/10/18

For this discussion, you will assess the use of various support decision tools and explain why outliers are sometimes called influential observations. Discuss what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included. Will this necessarily happen when a point is an outlier? You are required to give at least two examples in your response.

ASSIGNMENT 2  Due Tomorrow 08/11/18

Complete Problem 50 in Chapter 10 on page 477.

10-55) A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

a. Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

b. Interpret your best-fitting equation.

c. Using the best-fitting equation, predict sales during a month in which the price is $470.

In the discussion area, attach the Excel document showing work.

Assignment 3 Due Tomorrow 08/11/10

Multiple Regression

For this assignment, you are required to complete Problem 64 (p. 593) in Chapter 12 of your textbook. Use the appropriate Excel file templates from www.cengagebrain.com. Once complete, post your Excel Document in Waypoint. Show all work.

23-64) Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file Week 4 Assignment Chapter 12 Problem 64. Use regression to fit the following model to these data:
Yt = a + b1Yt−1 + b2Pt + et
This equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term.

a. If the price of a portrait during month 21 is $10, what would you predict for sales in month 21?

b. Does there appear to be a problem with autocorrelation of the residual? Explain your answer.

ASSIGNMENT 4 Due 08/12/18

After reviewing the optimization models in the text, select one model that you can use to improve a specific business process. Explain your reasoning.  You can work with a business process at your current job, previous jobs, think of a hypothetical situation (i.e. how FedEx may be routing their shipments or how a call center may be scheduling their employees), or use the scenario from the discussion in Week 1.

**YOU CAN USE ANY BUISNESS YOU WANT THAT HAS TO DO WITH LOGISTICS LIKE A WAREHOUSE.

ASSIGNMENT 1 Due Today 08/10/18

For this discussion, you will assess the use of various support decision tools and explain why outliers are sometimes called influential observations. Discuss what could happen to the slope of a regression of Y versus a single X when an outlier is included versus when it is not included. Will this necessarily happen when a point is an outlier? You are required to give at least two examples in your response.

ASSIGNMENT 2  Due Tomorrow 08/11/18

Complete Problem 50 in Chapter 10 on page 477.

10-55) A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

a. Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

b. Interpret your best-fitting equation.

c. Using the best-fitting equation, predict sales during a month in which the price is $470.

In the discussion area, attach the Excel document showing work.

Assignment 3 Due Tomorrow 08/11/10

Multiple Regression

For this assignment, you are required to complete Problem 64 (p. 593) in Chapter 12 of your textbook. Use the appropriate Excel file templates from www.cengagebrain.com. Once complete, post your Excel Document in Waypoint. Show all work.

23-64) Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file Week 4 Assignment Chapter 12 Problem 64. Use regression to fit the following model to these data:
Yt = a + b1Yt−1 + b2Pt + et
This equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term.

a. If the price of a portrait during month 21 is $10, what would you predict for sales in month 21?

b. Does there appear to be a problem with autocorrelation of the residual? Explain your answer.

ASSIGNMENT 4 Due 08/12/18

After reviewing the optimization models in the text, select one model that you can use to improve a specific business process. Explain your reasoning.  You can work with a business process at your current job, previous jobs, think of a hypothetical situation (i.e. how FedEx may be routing their shipments or how a call center may be scheduling their employees), or use the scenario from the discussion in Week 1.

**YOU CAN USE ANY BUISNESS YOU WANT THAT HAS TO DO WITH LOGISTICS LIKE A WAREHOUSE.