IS 704 - Data Analysis in Information Systems

(3 units)

This course provides a comprehensive understanding of data analysis, focusing on statistical learning, model selection, regression techniques, classification methods, and advanced data modeling. Students will gain hands-on experience with advanced statistical methods to solve complex business problems.

Maximum units a student may earn: 3

Prerequisite(s): BADM 700 or admission to the MS in Information Systems (MSIS)

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. apply statistical learning techniques to identify appropriate models for data analysis.
2. implement resampling methods such as cross-validation and bootstrap to assess model accuracy.
3. perform linear and multiple regression analysis, utilizing variable selection and shrinkage techniques to optimize models.
4. apply diagnostics and validation techniques to ensure robust regression models.
5. utilize dimension reduction methods to manage high-dimensional data, with an emphasis on applications in regression contexts.
6. model non-linear relationships using advanced regression techniques.
7. implement basic classification methods and understand their applications in data analytics.

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