In Module Seven, you will submit your selection of statistical tools and data analysis, which are critical elements III and IV. You will submit a 3- to 4-page paper and a spreadsheet that provides justification for the appropriate statistical tools needed to analyze the company’s data, a hypothesis, the results of your analysis, any inferences from your hypothesis test, and a forecasting model that addresses the company’s problem. Specifically, the following critical elements must be addressed: III. Identify statistical tools and methods to collect data: 

A. Identify the appropriate family of statistical tools that you will use to perform your analysis. What are your statistical assumptions concerning the data that led you to selecting this family of tools? In other words, why did you select this family of tools for statistical analysis? 

B. Determine the category of the provided data in the given case study. Be sure to justify why the data fits into this category type. What is the relationship between the type of data and the tools? 

C. From the identified family of statistical tools, select the most appropriate tool(s) for analyzing the data provided in the given case study. 

D. Justify why you chose this tool to analyze the data. Be sure to include how this tool will help predict the use of the data in driving decisions. 

E. Describe the quantitative method that will best inform data-driven decisions. Be sure to include how this method will point out the relationships between the data. How will this method allow for the most reliable data? 

IV. Analyze data to determine the appropriate decision for the identified problem: 

A. Outline the process needed to utilize your statistical analysis to reach a decision regarding the given problem. 

B. Explain how following this process leads to valid, data-driven decisions. In other words, why is following your outlined process important? 

C. After analyzing the data sets in the case study, describe the reliability of the results. Be sure to include how you know whether the results are reliable. 

D. Illustrate a data-driven decision that addresses the given problem. How does your decision address the given problem? How will it result in operational improvement?