We are at the half-way point of this class. This week’s assignment is not an essay. Instead, it is a review of material previously covered submitted in a presentation format via Microsoft PowerPoint.  This content review and presentation preparation will be useful to you for the activities expected in our upcoming residency.

Review the short video in this week’s content folder on APA format for PowerPoint.

Create a PowerPoint presentation that contains the following information:

a. Overview of methods (clustering, association rules, regression, classification, time series analysis) Explain what the method is and provide one tangible example. Use at least one slide per method (minimum # of slides for this portion is 5)

b. Overview of your previously discussed problem and approach from Week 6. Include industry and problem, proposed data elements, and proposed approach (minimum # of slides for this portion is 3)

c. Summary of applicable method for your previously discussed problem from Week 6. Include the method, reason chosen and one alternative choice and why it was not the best choice (minimum # of slides for this portion is 3)

Guidance:

• Use APA Formatting with Title slide, Reference slides, in-text citations, and cite/reference all graphics
• Use a template & colors of your choice. Minimum total # slides = 13

weak 6 assignment is:

his is an opportunity to expand on that work within the context of the business analytics lifecycle and connect theory to practice.

Construct an essay specific to your industry and a potential, specific problem to be solved that outlines your exploratory data analytics approach.

(a) Review the Kaggle website (

https://www.kaggle.com/datasets

) or any public dataset such as those obtained from Google dataset research (

https://datasetsearch.research.google.com/

). Choose a dataset that closely aligns to the problem you wish to solve. Provide a link to the dataset.

• (b) Identify five types of data that would be useful in solving the problem you identified.
• (c) Discuss your exploratory data approach. In your discussion include mention of a least one alternative approach that you believe would be inappropriate.