watch videos,then choose 3 case to analyze

the purpose of this topic is for you to be introduced to the power of data analytics.  They can be very simple or very complicated.  We are going to use the commercial s/w JMP to demo via a few cases.   for each case there are a pdf file explaining what the issues are and how to analyze, a JMP file with the data.  

you are to view the video, then analyze it yourself while keeping a record of your analysis with a pdf or Word doc.  then when you are done, upload the pdf/Word file together with the new JMP file with your graphs, tables in it to Blackboard.   

you are to do a min of 3 of such cases.  I would recommend Baggage Complaints and Credit card Marketing.  Credit card Marketing is the use of AI/Data Mining in analytics.  

1. watch the video of Medical Malpractice case, Descriptive Statistics, Graphics, and Exploratory Data Analysis

https://learn-us-east-1-prod-fleet01-xythos.s3.amazonaws.com/5ddc0af50a34e/5801892?response-cache-control=private%2C%20max-age%3D21600&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27Week%25202%2520Medical%2520Malpractice.mp4&response-content-type=video%2Fmp4&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20201006T060000Z&X-Amz-SignedHeaders=host&X-Amz-Expires=21600&X-Amz-Credential=AKIAZH6WM4PL5SJBSTP6%2F20201006%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=d1f597801f92334525323f1ccc155e10cf41260cbd537871ab122ea70adca1c0

2.watch the video of Credit Card Marketing, Data Mining method:  Classification trees, validation, confusion matrix, misclassification, leaf report, ROC curves, lift curves.

https://learn-us-east-1-prod-fleet01-xythos.s3.amazonaws.com/5ddc0af50a34e/5905054?response-cache-control=private%2C%20max-age%3D21600&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27Week%252010%2520Credit%2520card%2520marketing.mp4&response-content-type=video%2Fmp4&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20201006T060000Z&X-Amz-SignedHeaders=host&X-Amz-Expires=21600&X-Amz-Credential=AKIAZH6WM4PL5SJBSTP6%2F20201006%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=56adb1badba744138b5ca890972d07024a8c2ff6d9ecb9b6f9817e6cdac81147

3.watch the video of Baggage Compliants, Compare the baggage complaints for three airlines: American Eagle, Hawaiian, and United. Using descriptive statistics and time series plots, explore differences between the airlines, whether complaints are getting better or worse over time, and if there are other factors, such as destinations, seasonal effects or the volume of travelers that might affect baggage performance.

https://learn-us-east-1-prod-fleet01-xythos.s3.amazonaws.com/5ddc0af50a34e/8213001?response-cache-control=private%2C%20max-age%3D21600&response-content-disposition=inline%3B%20filename%2A%3DUTF-8%27%27Baggage%2520Complaints.mp4&response-content-type=video%2Fmp4&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20201006T060000Z&X-Amz-SignedHeaders=host&X-Amz-Expires=21600&X-Amz-Credential=AKIAZH6WM4PL5SJBSTP6%2F20201006%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=f5ec39e8ffcdf2c8927ad729888ef55058996754bff2fc1fe0cb0dd2ff5fd8f6