help with assgn - 2 tasks - due in 1 week

C207 Task 2: Decision Tree Analysis

Introduction

Managers are required to organize, interpret, and display data that is reliable and relevant to the real-world decisions they must make in their businesses. The use of analytical tools will improve your ability to use data to make informed decisions. In this task, you will address the business situation in the attached scenario. You will access the scenario and dataset by entering your student ID number in the “Start” tab of the “Decision Tree Analysis Resources” document found in the Supporting Documents section. The scenario and dataset are located in the “Decision Tree Scenario” tab. Using this dataset, you will perform a decision tree analysis and recommend a solution. This recommendation will be included in a report you will write summarizing the key details of your analysis. For full functionality of the scenario and data attachment, you must use Microsoft Excel, which is available via the Microsoft Office 365 subscription service provided to all WGU students. It can be downloaded using the "Microsoft Office 365" link in the Web Links section.

Scenario

Refer to the scenario located in the supporting document, “Decision Tree Analysis Resources.”

Requirements

Your submission must represent your original work and understanding of the course material. Most performance assessment submissions are automatically scanned through the WGU similarity checker. Students are strongly encouraged to wait for the similarity report to generate after uploading their work and then review it to ensure Academic Authenticity guidelines are met before submitting the file for evaluation. See  Understanding Similarity Reports for more information.   Grammarly Note:  Professional Communication will be automatically assessed through Grammarly for Education in most performance assessments before a student submits work for evaluation. Students are strongly encouraged to review the Grammarly for Education feedback prior to submitting work for evaluation, as the overall submission will not pass without this aspect passing. See  Use Grammarly for Education Effectively for more information.   Microsoft Files Note:  Write your paper in Microsoft Word (.doc or .docx) unless another Microsoft product, or pdf, is specified in the task directions. Tasks may not be submitted as cloud links, such as links to Google Docs, Google Slides, OneDrive, etc.  All supporting documentation, such as screenshots and proof of experience, should be collected in a pdf file and submitted separately from the main file. For more information, please see  Computer System and Technology Requirements.  

 

You must use the rubric to direct the creation of your submission because it provides detailed criteria that will be used to evaluate your work. Each requirement below may be evaluated by more than one rubric aspect. The rubric aspect titles may contain hyperlinks to relevant portions of the course.

 

Complete your decision tree analysis and create a report by doing the following:

 

Note: The supporting document “Decision Tree Analysis Resources” contains a scenario, data set, and template. While you must use the scenario and data set provided in the supporting document, the template is optional. You are encouraged to use the template to complete your analysis. Please see supporting document, “QUM3 Task 2 Getting Started,” for help accessing the scenario and dataset. 

 

A.  Summarize the business scenario by doing the following:

1.  Describe a business question that could be answered by applying decision tree analysis and is derived from the scenario in “Decision Tree Analysis Resources."

2.  Justify why decision tree analysis is the appropriate analysis technique, and include relevant details from the scenario to support your justification.

 

B.  Identify the relevant data values required for your decision tree analysis, including the following:

•   demands

•   profits per unit

•   probabilities

 

C.  Report how you analyzed the data using decision tree analysis by completing a decision tree diagram that includes  each of the following: 

•   state-of-nature nodes

•   calculated payoffs,  each expressed out to two decimal places

•   expected values,  each expressed out to two decimal places

 

Note:  Include “Decision Tree Analysis Resources.” spreadsheet with your task submission for evidence of your calculations and decision tree diagram.

Note: Refer to "Prepare for the Performance Assessment Task 2"  in the course of study to examples of acceptable output.

 

D.  Summarize the implications of your decision tree analysis by doing the following:

1.  Explain each step required to determine the expected value based on payoffs. 

2.  List one limitation for  each of the following:

•   any one of the data values listed in part B

•   the decision tree analysis

 

E.  Recommend a course of action that addresses the business question from part A and is based on the results of your decision tree analysis.

 

F.  Acknowledge sources, using in-text citations and references, for content that is quoted, paraphrased, or summarized.

 

G.  Demonstrate professional communication in the content and presentation of your submission.

File Restrictions

File name may contain only letters, numbers, spaces, and these symbols: ! - _ . * ' ( ) File size limit: 200 MB File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, csv, txt, qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif, tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z

Task 1: Linear Regression Analysis

Introduction

Managers are required to organize, interpret, and display data that is reliable and relevant to the real-world decisions they must make in their businesses. The use of analytical tools will improve your ability to use data to make these informed decisions. In this task, you will address the business situation in the attached "Linear Regression Analysis Resources" scenario. You will access the scenario and dataset by entering your student ID number in the “Start” tab of the attachment, then continuing to the “Scenario” tab. Using this data set, you will perform a linear regression analysis and write a report in which you recommend a solution by summarizing the key details of your analysis. For full functionality of the scenario and dataset attachment, you are strongly encouraged to use Microsoft Excel, which is available via the Microsoft Office 365 subscription service provided to all WGU students. It can be downloaded using the "Microsoft Office 365" link in the Web Links section.

Scenario

Refer to the scenario located in the attached “Linear Regression Analysis Resources.”

Requirements

Your submission must represent your original work and understanding of the course material. Most performance assessment submissions are automatically scanned through the WGU similarity checker. Students are strongly encouraged to wait for the similarity report to generate after uploading their work and then review it to ensure Academic Authenticity guidelines are met before submitting the file for evaluation. See  Understanding Similarity Reports for more information.   Grammarly Note:  Professional Communication will be automatically assessed through Grammarly for Education in most performance assessments before a student submits work for evaluation. Students are strongly encouraged to review the Grammarly for Education feedback prior to submitting work for evaluation, as the overall submission will not pass without this aspect passing. See  Use Grammarly for Education Effectively for more information.   Microsoft Files Note:  Write your paper in Microsoft Word (.doc or .docx) unless another Microsoft product, or pdf, is specified in the task directions. Tasks may not be submitted as cloud links, such as links to Google Docs, Google Slides, OneDrive, etc.  All supporting documentation, such as screenshots and proof of experience, should be collected in a pdf file and submitted separately from the main file. For more information, please see  Computer System and Technology Requirements.  

 

You must use the rubric to direct the creation of your submission because it provides detailed criteria that will be used to evaluate your work. Each requirement below may be evaluated by more than one rubric aspect. The rubric aspect titles may contain hyperlinks to relevant portions of the course.

 

Complete your linear regression analysis and create a report by doing the following:

 

Note: The supporting document “Linear Regression Analysis Resources” contains a scenario, data set, and data analysis template. While you must use the scenario and data set provided in the supporting document, the template is optional. You are encouraged to use the template to complete your analysis. Please see supporting document, “QUM Task 1 Getting Started,” for help accessing the scenario and dataset. 

 

A.  Summarize the business scenario by doing the following: 

1. Describe a business question that could be answered by applying linear regression analysis and is derived from the scenario in the attached “Linear Regression Analysis Resources."

2. State the null hypothesis for this linear regression analysis.

3. Using relevant details from the scenario, the business question you proposed in part A1, and the null hypothesis you stated in part A2, justify why linear regression is the appropriate analysis technique. 

 

B.  Describe the data provided in the attached “Linear Regression Analysis Resources” by doing the following:

1.  Describe the relevant data characteristics for your linear regression analysis, including  each of the following:

•   independent variable or variables

•   dependent variable

•   level of measurement for each variable

•   sample size or number of observations

 

C.  Report how you analyzed the data using linear regression by doing the following:

1. Provide the output and calculations of the linear regression analysis you performed.

 

Note: The output should include the output from the software you used to perform the analysis. Refer to "Prepare for the Performance Assessment Task 1" in the course of study to see examples of acceptable output.

 

2. Create a graphical display of the data using a scatter plot that includes  each of the following:

•   chart title

•   legend

•   axis titles

 

Note: This display should be a summary or representation of the data provided, not raw data.

 

D.  Describe the implications of your data analysis from the scenario by doing the following:

1.  Interpret the results of the data analysis by doing the following:

a. Discuss the goodness of fit with the supporting test statistic from your linear regression analysis output.

b. Discuss the significance of the independent variable(s) with support from your linear regression analysis results.

c. Create the linear equation, then describe how it can be applied to the scenario in future business decision-making.

2. Discuss a limitation of the research that could affect the recommended course of action.

3. Recommend a course of action that aligns with your linear regression analysis results.

 

Note: Your recommendation should focus on the results of your analytic technique output from part C1.

 

E. Acknowledge sources, using in-text citations and references, for content that is quoted, paraphrased, or summarized.

 

F.  Demonstrate professional communication in the content and presentation of your submission. 

File Restrictions

File name may contain only letters, numbers, spaces, and these symbols: ! - _ . * ' ( ) File size limit: 200 MB File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, csv, txt, qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif, tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z

Rubric

A1:BUSINESS QUESTION

Not Evident: A description of a business question is not provided.

Approaching Competence: The business question described is not derived from the scenario or is not consistent with the application of linear regression analysis.

Competent: The business question described is derived from the scenario and is consistent with the application of linear regression analysis.

A2:NULL HYPOTHESIS

Not Evident: A null hypothesis is not provided.

Approaching Competence: The null hypothesis provided is not accurately stated for the linear regression analysis or is not relevant to the scenario.

Competent: The null hypothesis provided is accurately stated for the linear regression analysis and is relevant to the scenario.

A3:ANALYSIS TECHNIQUE JUSTIFICATION

Not Evident: A justification of linear regression analysis is not provided.

Approaching Competence: The justification of linear regression analysis does not logically explain why it is the appropriate technique to answer the business question from part A1, does not use the null hypothesis from A2, or is not supported with relevant details from the scenario.

Competent: The justification of linear regression analysis logically explains why it is the appropriate technique to answer the business question from part A1, uses the null hypothesis from A2, and is supported with relevant details from the scenario.

B1:DESCRIPTION OF RELEVANT DATA

Not Evident:A description of data characteristics is not provided.

Approaching Competence: The description does not accurately address the relevant data characteristics of the linear regression analysis, or 1 or more of the given elements are not included.

Competent: The description accurately addresses the relevant data characteristics of the linear regression analysis, including each of the given elements.

C1:ANALYSIS OUTPUT AND CALCULATIONS

Not Evident:A linear regression analysis output and calculations are not provided.

Approaching Competence: The linear regression analysis output or calculations provided contain 1 or more inaccuracies.

Competent: The linear regression analysis output and calculations provided are accurate.

C2:GRAPHICAL DISPLAY

Not Evident: A graphical display of the data is not provided.

Approaching Competence: The graphical display of the data does not use a scatter-plot does not accurately represent the data, or does not include 1 or more of the given elements.

Competent: The graphical display of the data uses a scatter plot to accurately represent the data, including each of the given elements.

D1A:GOODNESS OF FIT

Not Evident: A discussion of the goodness of fit is not provided.

Approaching Competence: The discussion of goodness of fit is not supported with the appropriate test statistic from the linear regression analysis output, or the interpretation of the test statistic is inaccurate.

Competent: The discussion of goodness of fit is supported with the appropriate test statistic from the linear regression analysis output, and the interpretation of the test statistic is accurate.

D1B:INDEPENDENT VARIABLE(S) SIGNIFICANCE

Not Evident:A discussion of the significance of the independent variable(s) is not provided.

Approaching Competence: The discussion of the significance of the independent variable(s) is not logical or is not supported by the linear regression analysis results, or the associated interpretation of the comparison to the significance level is inaccurate.

Competent: The discussion logically addresses the significance of the independent variable(s) with support from the linear regression analysis results, and the associated interpretation of the comparison to the significance level is accurate.

D1C:LINEAR EQUATION APPLICATION

Not Evident: A linear equation and an explanation of the equation are not provided.

Approaching Competence: The linear equation provided is not accurate, or the explanation does not logically address the application of the linear equation

Competent: The linear equation provided is accurate, and the explanation logically addresses the application of the linear equation to the scenario in future business decision-making.

D2:LIMITATION

Not Evident: A discussion of a limitation of the research is not provided.

Approaching Competence: The discussion does not accurately describe a limitation of the research that could affect the recommended course of action.

Competent: The discussion accurately describes a limitation of the research that could affect the recommended course of action.

D3:RECOMMENDED COURSE OF ACTION

Not Evident: A recommended course of action is not provided.

Approaching Competence: The recommended course of action is not logically aligned with the results of the linear regression analysis.

Competent: The recommended course of action is logically aligned with the results of the linear regression analysis.

E:SOURCES

Not Evident:The submission does not include both in-text citations and a reference list for sources that are quoted, paraphrased, or summarized.

Approaching Competence: The submission includes in-text citations for sources that are quoted, paraphrased, or summarized and a reference list; however, the citations or reference list is incomplete or inaccurate.

Competent: The submission includes in-text citations for sources that are properly quoted, paraphrased, or summarized and a reference list that accurately identifies the author, date, title, and source location as available.

F:PROFESSIONAL COMMUNICATION

Not Evident: This submission includes pervasive errors in professional communication related to grammar, sentence fluency, contextual spelling, or punctuation, negatively impacting the professional quality and clarity of the writing. Specific errors have been identified by Grammarly for Education under the Correctness category.  

Approaching Competence: This submission includes substantial errors in professional communication related to grammar, sentence fluency, contextual spelling, or punctuation. Specific errors have been identified by Grammarly for Education under the Correctness category.  

Competent: This submission includes satisfactory use of grammar, sentence fluency, contextual spelling, and punctuation, which promote accurate interpretation and understanding.