Data driven decision making
In this task, you will address the real-world business situation that you identified in task 1. Using relevant data you have gathered, analyze the data and recommend a solution. This recommendation will be included in a report that you will write, summarizing the key details of your analysis.
Note: You must successfully pass task 1 before work on task 2 is started.
Approved data analysis techniques for this task include the following:
Recommended Analysis Techniques:
• regression (linear regression, multiple regression, or logistic regression)
• time series or trend analysis (regression, exponential smoothing, or moving average)
• crossover analysis
• break-even analysis
Additional Approved Analysis Techniques:
• statistical process control
• linear programming
• decision tree
Your submission must be your original work. No more than a combined total of 30% of the submission and no more than a 10% match to any one individual source can be directly quoted or closely paraphrased from sources, even if cited correctly. The originality report that is provided when you submit your task can be used as a guide.
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.
Create a report (suggested length of 2–4 written pages or 800 words) by doing the following:
A. Summarize the real-world business situation you identified in task 1.
B. Report the data you collected, relevant to the business situation, by doing the following:
1. Describe the relevant data you collected.
2. Create an appropriate graphical display (e.g., bar chart, scatter plot, line chart, or histogram) of the data you collected.
Note: This display should be a summary or representation of your data, not raw data.
C. Report how you analyzed the data using an analysis technique from the given list by doing the following:
1. Describe an appropriate analysis technique that you used to analyze the data.
2. Include the output and any calculations of the 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 2” in the course of study to see examples of acceptable output.
3. Justify why you chose this analysis technique.
D. Summarize the implications of your data analysis by doing the following:
1. Discuss the results of your data analysis.
Note: Refer “Prepare for the Performance Assessment Task 2” in the course of study to see an example of an acceptable discussion of results.
2. Discuss the limitation(s) of your data analysis.
3. Recommend a course of action based on your results.
Note: Your recommendation should focus on the results of your analytic technique output from part C2.
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.