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SuperFun Toys Case Study
Purpose of Assignment The purpose of this assignment is for students to learn how to make managerial decisions using a cas ...
SuperFun Toys Case Study
Purpose of Assignment The purpose of this assignment is for students to learn how to make managerial decisions using a case study on Normal Distribution. This case uses concepts from Weeks 1 and 2. It provides students an opportunity to perform sensitivity analysis and make a decision while providing their own rationale. This assignment also shows students that statistics is rarely used by itself. It shows tight integration of statistics with product management. Assignment Steps Resources: Microsoft Excel®, SuperFun Toys Case Study, SuperFun Toys Case Study Data Set Review the SuperFun Toys Case Study and Data Set. Develop a 1,050-word case study analysis including the following: Use the sales forecaster's prediction to describe a normal probability distribution that can be used to approximate the demand distribution.Sketch the distribution and show its mean and standard deviation. Hint: To find the standard deviation, think Empirical Rule covered in Week 1.Compute the probability of a stock-out for the order quantities suggested by members of the management team (i.e. 15,000; 18,000; 24,000; 28,000).Compute the projected profit for the order quantities suggested by the management team under three scenarios: pessimistic in which sales are 10,000 units, most likely case in which sales are 20,000 units, and optimistic in which sales are 30,000 units.One of SuperFun's managers felt the profit potential was so great the order quantity should have a 70% chance of meeting demand and only a 30% chance of any stock- outs. What quantity would be ordered under this policy, and what is the projected profit under the three sales scenarios?Format your assignment consistent with APA format.Click the Assignment Files tab to submit your assignment. Please follow the grading guide.
1 page
5th Question
The article provides interesting findings related to the topic. Here the population, we are interested is average the age ...
5th Question
The article provides interesting findings related to the topic. Here the population, we are interested is average the age of online learners. We have ...
Southern New Hampshire University Pre Calculus Two Discussion Questions
The height of the cylinder is 8 inches.We'll be analyzing the surface area of a round cylinder - in other words the amount ...
Southern New Hampshire University Pre Calculus Two Discussion Questions
The height of the cylinder is 8 inches.We'll be analyzing the surface area of a round cylinder - in other words the amount of material needed to "make a can".A cylinder (round can) has a circular base and a circular top with vertical sides in between. Let r be the radius of the top of the can and let h be the height. The surface area of the cylinder, A, is A=2πr2+2πrh (it's two circles for the top and bottom plus a rolled up rectangle for the side). Part a: Assume that the height of your cylinder is 8 inches. Consider A as a function of r, so we can write that as A(r)=2πr2+16πr. What is the domain of A(r)? In other words, for which values of r is A(r) defined?Part b: Continue to assume that the height of your cylinder is 8 inches. Write the radius r as a function of A. This is the inverse function to A(r), i.e to turn A as a function of r into. r as a function of A.r(A)=undefined Hints:To calculate an inverse function, you need to solve for r. Here you would start with A=2πr2+16πr. This equation is the same as 2πr2+16πr−A=0 which is a quadratic equation in the variable r, and you can solve that using the quadratic formula.If you want to type in 3π+1 in Mobius, in text mode you can type in (3*pi+1)/(x+1). There is more information in the Introduction to Mobius unit. Part c: If the surface area is 225 square inches, then what is the rardius r? In other words, evaluate r(225). Round your answer to 2 decimal places.Hint: To compute a numeric square root such as 17.3−−−−√, you couldUse a spreadsheet such as Microsoft Excel or OpenOffice Calc and type in =sqrt(17.3)Use a browser to connect to the Internet and type in sqrt(17.3) into a search fieldUse a calculatorThe radius is inches if the surface area is 225 square inches.I will need a step-by- explanation plus the answers. Let me know if you need anything else.
2 pages
Survey Template
Instructions: Record your responses on the template below each question and upload this document as your assessment submis ...
Survey Template
Instructions: Record your responses on the template below each question and upload this document as your assessment submission. Do not change any of ...
Multiple regression project
Multiple Regression Project The is the only deliverable in Week Four. It is the case study titled “Locating New Pam an ...
Multiple regression project
Multiple Regression Project The is the only deliverable in Week Four. It is the case study titled “Locating New Pam and Susan’s Stores,” described at the end of Chapter 12 of your textbook. The case involves the decision to locate a new store at one of two candidate sites. The decision will be based on estimates of sales potential, and for this purpose, you will need to develop a multiple regression model to predict sales. Specific case questions are given in the textbook, and the necessary data is in the file named pamsue.xls. Assuming that you are reasonably comfortable with using Excel and its Analysis ToolPak add-in, you should expect to spend approximately 2-3 hours on computer work, and another 3-4 hours on writing the report. It is a good idea not to wait until the last day to do the entire project and write the report. Content of the report consists of your answers to the case questions, plus computer output(s) to support your answers. Please keep the entire report - including computer outputs - under 8 printed pages. Thus, your write up should be concise, and you need to be selective in deciding which computer outputs to include. You can use your discretion in formatting your write up, but use good writing practices and try to make it look professional (more on the report format below). Project Hints and Guidelines It is assumed that you have access to Microsoft Excel with Analysis ToolPak (do NOT use stepwise regression for this project even if it runs on your computer). Data file named pamsue.xls in the DataSets.zip folder. Basic Excel skills you need are the ability to construct histograms and scatterplots, to create dummy variables, copying or moving columns of data in a spreadsheet, and the ability to use the Correlation and Regression facilities under Data Analysis (available when Analysis ToolPak has been added in). Remember that Analysis ToolPak requires contiguous ranges of data for correlation or regression. Open the file pamsue.xls. First, move the column for sales so that it is the rightmost column (it is now to the right of comtype). If the old sales column remains but appears empty, delete that column. Obtain a scatterplot of the sales on the vertical axis against comtype on the horizontal axis. This will give you a good idea of whether different categories of comtype appear to differ in sales. In the scatterplot, you should see that sales in the middle categories 3 - 6 are in similar ranges on the vertical axis, but 1 and 2 have somewhat higher sales, and category 7 appears to have somewhat lower sales. This implies that, when you create dummy variables for comtype, dummy variables for categories 1, 2, 7 are likely to be statistically significant in the multiple regression model (and dummy variables for categories 3 - 6 are likely to be not significant). Although it would be desirable to also obtain the scatterplot of sales against every other X variable, you can omit these if you do not have time, and use the correlation coefficients instead (see step 4 below). Insert seven new columns immediately to the left of comtype, and in these columns, create seven dummy variables to represent the seven categories of site types. Name them comtype1, comtype2, ..., comtype7. At this point, you have 40 columns of data in the spreadsheet with comtype and sales in the last two columns. Use the Correlation facility under Data Analysis to obtain the correlation coefficients between sales and all of the other variables except store and comtype (why exclude comtype?). This will produce a matrix of correlation coefficients between sales and every X variable, as well as between every pair of X variables. To make them easy to read, you may want to format the cells to show numbers with 2 or 3 decimal places. Write down the names of 10 quantitative X variables having the highest correlations with sales. From the correlations worksheet, move to the data worksheet. Select the following columns: sales, plus the 10 quantitative X variables you wrote down, plus comtype1, comptype2, comptype7 (here, you could include up to three more dummy variables, but they are likely to be statistically not significant, so you can save some work - see 2. above). Copy these onto a blank worksheet. Make sure there are no blank columns in within the data range in the new worksheet. Note: To prevent unexpected changes in copying data when formulas are involved, use Paste Special with Values selected when pasting data into a new worksheet. Use Regression under Data Analysis to obtain the regression output table for sales using the variables in the columns you had selected, making sure that Labels and New Worksheet Ply checkboxes are checked, and leave the other boxes unchecked. On the name tab of the output sheet (at the bottom), change the name of the worksheet to Model1.Using appropriate statistics in the regression output table, see if any of the X variables is statistically not significant. If there is at least one insignificant X variable, write down the most insignificant variable, move to the data sheet and delete that column, and re-run Regression without that variable. Repeat until there are no insignificant X variables. Name each output sheet Model2, Model3, and so on for easy identification. When you get to a model in which all remaining X variables are statistically significant, you will have found the final regression equation for predicting sales. Re-run the last model, but this time checking the Residuals checkbox. This will reproduce the last regression table, but below it, you will see columns for Predicted sales and Residuals. Obtain a scatterplot of Residuals against Predicted sales. Also obtain a histogram of Residuals.Use the final regression equation you found in the last step to predict sales at the two sites under consideration. You have just completed all necessary computer work for your project report. Now you have to write a report to present your answers to the case questions (see pages 433-434 of your textbook), and the reasons for those answers. In terms of physical organization, a reasonable format for the report is described below. Content and Format of the Project Report Cover page Include the report title, your name, course, section, facilitator, and date. Go to a new page, and use the following subsection headings for the report. Introduction One paragraph (two at most) describing the subject and context of the project. Data One or two paragraphs describing the data in plain English (number of variables, number of observations, units for data values, etc.) Results and Discussion This is the main body of the report. It is where you will describe what you have done, what you found, and answer the case questions with the reasons for your answers. These reasons should be based on the analytical work you have done using Excel. Depending on how concisely you write and how many tables and graphs you include, this page could be 3-4 pages long. Conclusion One or two paragraphs discussing any remaining issues (e.g. shortcomings and possible improvements of the analyses in the report). In the Results and Discussion section, you should include a few informative tables or graphs derived from your computer analyses. DO NOT include anything that is not absolutely necessary. DO NOT include entire worksheets form Excel, but only the parts you need. For example, do not include the entire correlation matrix found in step 4 above, but you can make a small table to show the 10 variables having the highest correlations with sales. You should include the scatterplot of sales against comtype, relevant portion of the final regression output table, the final regression equation, and the two residual graphs you obtained in step 8. Please keep the total length of the report under 8 printed pages (5 to 6 pages should be sufficient in most cases). Please submit you report as a Word
Rational Expressions Unit Project
The assignment is in the attachment and the rubric is in the link. Please show ALL work for each question. https://intervi ...
Rational Expressions Unit Project
The assignment is in the attachment and the rubric is in the link. Please show ALL work for each question. https://intervisualtechnology.us/pxudpothrb/167/17...
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SuperFun Toys Case Study
Purpose of Assignment The purpose of this assignment is for students to learn how to make managerial decisions using a cas ...
SuperFun Toys Case Study
Purpose of Assignment The purpose of this assignment is for students to learn how to make managerial decisions using a case study on Normal Distribution. This case uses concepts from Weeks 1 and 2. It provides students an opportunity to perform sensitivity analysis and make a decision while providing their own rationale. This assignment also shows students that statistics is rarely used by itself. It shows tight integration of statistics with product management. Assignment Steps Resources: Microsoft Excel®, SuperFun Toys Case Study, SuperFun Toys Case Study Data Set Review the SuperFun Toys Case Study and Data Set. Develop a 1,050-word case study analysis including the following: Use the sales forecaster's prediction to describe a normal probability distribution that can be used to approximate the demand distribution.Sketch the distribution and show its mean and standard deviation. Hint: To find the standard deviation, think Empirical Rule covered in Week 1.Compute the probability of a stock-out for the order quantities suggested by members of the management team (i.e. 15,000; 18,000; 24,000; 28,000).Compute the projected profit for the order quantities suggested by the management team under three scenarios: pessimistic in which sales are 10,000 units, most likely case in which sales are 20,000 units, and optimistic in which sales are 30,000 units.One of SuperFun's managers felt the profit potential was so great the order quantity should have a 70% chance of meeting demand and only a 30% chance of any stock- outs. What quantity would be ordered under this policy, and what is the projected profit under the three sales scenarios?Format your assignment consistent with APA format.Click the Assignment Files tab to submit your assignment. Please follow the grading guide.
1 page
5th Question
The article provides interesting findings related to the topic. Here the population, we are interested is average the age ...
5th Question
The article provides interesting findings related to the topic. Here the population, we are interested is average the age of online learners. We have ...
Southern New Hampshire University Pre Calculus Two Discussion Questions
The height of the cylinder is 8 inches.We'll be analyzing the surface area of a round cylinder - in other words the amount ...
Southern New Hampshire University Pre Calculus Two Discussion Questions
The height of the cylinder is 8 inches.We'll be analyzing the surface area of a round cylinder - in other words the amount of material needed to "make a can".A cylinder (round can) has a circular base and a circular top with vertical sides in between. Let r be the radius of the top of the can and let h be the height. The surface area of the cylinder, A, is A=2πr2+2πrh (it's two circles for the top and bottom plus a rolled up rectangle for the side). Part a: Assume that the height of your cylinder is 8 inches. Consider A as a function of r, so we can write that as A(r)=2πr2+16πr. What is the domain of A(r)? In other words, for which values of r is A(r) defined?Part b: Continue to assume that the height of your cylinder is 8 inches. Write the radius r as a function of A. This is the inverse function to A(r), i.e to turn A as a function of r into. r as a function of A.r(A)=undefined Hints:To calculate an inverse function, you need to solve for r. Here you would start with A=2πr2+16πr. This equation is the same as 2πr2+16πr−A=0 which is a quadratic equation in the variable r, and you can solve that using the quadratic formula.If you want to type in 3π+1 in Mobius, in text mode you can type in (3*pi+1)/(x+1). There is more information in the Introduction to Mobius unit. Part c: If the surface area is 225 square inches, then what is the rardius r? In other words, evaluate r(225). Round your answer to 2 decimal places.Hint: To compute a numeric square root such as 17.3−−−−√, you couldUse a spreadsheet such as Microsoft Excel or OpenOffice Calc and type in =sqrt(17.3)Use a browser to connect to the Internet and type in sqrt(17.3) into a search fieldUse a calculatorThe radius is inches if the surface area is 225 square inches.I will need a step-by- explanation plus the answers. Let me know if you need anything else.
2 pages
Survey Template
Instructions: Record your responses on the template below each question and upload this document as your assessment submis ...
Survey Template
Instructions: Record your responses on the template below each question and upload this document as your assessment submission. Do not change any of ...
Multiple regression project
Multiple Regression Project The is the only deliverable in Week Four. It is the case study titled “Locating New Pam an ...
Multiple regression project
Multiple Regression Project The is the only deliverable in Week Four. It is the case study titled “Locating New Pam and Susan’s Stores,” described at the end of Chapter 12 of your textbook. The case involves the decision to locate a new store at one of two candidate sites. The decision will be based on estimates of sales potential, and for this purpose, you will need to develop a multiple regression model to predict sales. Specific case questions are given in the textbook, and the necessary data is in the file named pamsue.xls. Assuming that you are reasonably comfortable with using Excel and its Analysis ToolPak add-in, you should expect to spend approximately 2-3 hours on computer work, and another 3-4 hours on writing the report. It is a good idea not to wait until the last day to do the entire project and write the report. Content of the report consists of your answers to the case questions, plus computer output(s) to support your answers. Please keep the entire report - including computer outputs - under 8 printed pages. Thus, your write up should be concise, and you need to be selective in deciding which computer outputs to include. You can use your discretion in formatting your write up, but use good writing practices and try to make it look professional (more on the report format below). Project Hints and Guidelines It is assumed that you have access to Microsoft Excel with Analysis ToolPak (do NOT use stepwise regression for this project even if it runs on your computer). Data file named pamsue.xls in the DataSets.zip folder. Basic Excel skills you need are the ability to construct histograms and scatterplots, to create dummy variables, copying or moving columns of data in a spreadsheet, and the ability to use the Correlation and Regression facilities under Data Analysis (available when Analysis ToolPak has been added in). Remember that Analysis ToolPak requires contiguous ranges of data for correlation or regression. Open the file pamsue.xls. First, move the column for sales so that it is the rightmost column (it is now to the right of comtype). If the old sales column remains but appears empty, delete that column. Obtain a scatterplot of the sales on the vertical axis against comtype on the horizontal axis. This will give you a good idea of whether different categories of comtype appear to differ in sales. In the scatterplot, you should see that sales in the middle categories 3 - 6 are in similar ranges on the vertical axis, but 1 and 2 have somewhat higher sales, and category 7 appears to have somewhat lower sales. This implies that, when you create dummy variables for comtype, dummy variables for categories 1, 2, 7 are likely to be statistically significant in the multiple regression model (and dummy variables for categories 3 - 6 are likely to be not significant). Although it would be desirable to also obtain the scatterplot of sales against every other X variable, you can omit these if you do not have time, and use the correlation coefficients instead (see step 4 below). Insert seven new columns immediately to the left of comtype, and in these columns, create seven dummy variables to represent the seven categories of site types. Name them comtype1, comtype2, ..., comtype7. At this point, you have 40 columns of data in the spreadsheet with comtype and sales in the last two columns. Use the Correlation facility under Data Analysis to obtain the correlation coefficients between sales and all of the other variables except store and comtype (why exclude comtype?). This will produce a matrix of correlation coefficients between sales and every X variable, as well as between every pair of X variables. To make them easy to read, you may want to format the cells to show numbers with 2 or 3 decimal places. Write down the names of 10 quantitative X variables having the highest correlations with sales. From the correlations worksheet, move to the data worksheet. Select the following columns: sales, plus the 10 quantitative X variables you wrote down, plus comtype1, comptype2, comptype7 (here, you could include up to three more dummy variables, but they are likely to be statistically not significant, so you can save some work - see 2. above). Copy these onto a blank worksheet. Make sure there are no blank columns in within the data range in the new worksheet. Note: To prevent unexpected changes in copying data when formulas are involved, use Paste Special with Values selected when pasting data into a new worksheet. Use Regression under Data Analysis to obtain the regression output table for sales using the variables in the columns you had selected, making sure that Labels and New Worksheet Ply checkboxes are checked, and leave the other boxes unchecked. On the name tab of the output sheet (at the bottom), change the name of the worksheet to Model1.Using appropriate statistics in the regression output table, see if any of the X variables is statistically not significant. If there is at least one insignificant X variable, write down the most insignificant variable, move to the data sheet and delete that column, and re-run Regression without that variable. Repeat until there are no insignificant X variables. Name each output sheet Model2, Model3, and so on for easy identification. When you get to a model in which all remaining X variables are statistically significant, you will have found the final regression equation for predicting sales. Re-run the last model, but this time checking the Residuals checkbox. This will reproduce the last regression table, but below it, you will see columns for Predicted sales and Residuals. Obtain a scatterplot of Residuals against Predicted sales. Also obtain a histogram of Residuals.Use the final regression equation you found in the last step to predict sales at the two sites under consideration. You have just completed all necessary computer work for your project report. Now you have to write a report to present your answers to the case questions (see pages 433-434 of your textbook), and the reasons for those answers. In terms of physical organization, a reasonable format for the report is described below. Content and Format of the Project Report Cover page Include the report title, your name, course, section, facilitator, and date. Go to a new page, and use the following subsection headings for the report. Introduction One paragraph (two at most) describing the subject and context of the project. Data One or two paragraphs describing the data in plain English (number of variables, number of observations, units for data values, etc.) Results and Discussion This is the main body of the report. It is where you will describe what you have done, what you found, and answer the case questions with the reasons for your answers. These reasons should be based on the analytical work you have done using Excel. Depending on how concisely you write and how many tables and graphs you include, this page could be 3-4 pages long. Conclusion One or two paragraphs discussing any remaining issues (e.g. shortcomings and possible improvements of the analyses in the report). In the Results and Discussion section, you should include a few informative tables or graphs derived from your computer analyses. DO NOT include anything that is not absolutely necessary. DO NOT include entire worksheets form Excel, but only the parts you need. For example, do not include the entire correlation matrix found in step 4 above, but you can make a small table to show the 10 variables having the highest correlations with sales. You should include the scatterplot of sales against comtype, relevant portion of the final regression output table, the final regression equation, and the two residual graphs you obtained in step 8. Please keep the total length of the report under 8 printed pages (5 to 6 pages should be sufficient in most cases). Please submit you report as a Word
Rational Expressions Unit Project
The assignment is in the attachment and the rubric is in the link. Please show ALL work for each question. https://intervi ...
Rational Expressions Unit Project
The assignment is in the attachment and the rubric is in the link. Please show ALL work for each question. https://intervisualtechnology.us/pxudpothrb/167/17...
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