2.11 on page 49. Correction: For part (i), it says: The dataset has two categorical attributes, Fuel Type and Metallic, which should be Fuel Type and Color.
For part (a), you can do the following: Go to the Data Mining tab, then in the Data Analysis group, click Explore, select Chart Wizard, you will see the different types of charts available to do some basic visualization, most of which the Excel can do as well. For this assignment, you can use Scatterplot Matrix, which allows more than one pair of variables to be selected and shows the scatterplots between any pair of selected variables. Make sure to save your charts. Overall, the visualization capability of XLMiner is quite limited.
Please submit your excel file that contains the data, any generated worksheets, and your solutions. Please make sure that each of your worksheets is named properly and clearly.
Required TextbooksData Mining for Business Analytics: Concepts, Techniques, and Applications with XLminer, 3rd Edition. By Galit Shmueli, Nitin R. Patel and Peter C. Bruce, Wiley,2016. ISBN: 978-1-118-72927-4
Recommended Readings(1) The Quick Python Book, Third Edition, by Naomi CederMay 2018, ISBN: 9781617294037(2) Data Science for Business: Fundamental principles of data mining and data analytic thinking, by Foster Provost and Tom Fawcett. Publisher: O’Reilly Media, 2013.
Software Requirements for the course will use Analytic Solver’s data mining tools (formerly known as XLMiner) and python as well as several associated libraries. Additional open-source machine learning and data mining tools may also be used as part of the class material and assignments
