ISIT 338 Data Analysis Techniques • 5 Cr.
Students learn a variety strategies and techniques for analyzing data and making decisions based upon that data. Students use case studies to integrate their analysis and problem solving skills. Students use current software systems to do analysis and they are required to present the results of their analyses. Prerequisite: ISIT 330 with a C or better, and MATH 130.
After completing this class, students should be able to:
- Select data sources to use for collecting information and assess the data quality, clean the data to make it useful and distinguish signal from noise.
- Create basic data models to illuminate patterns, and assimilate new information into the models.
- Evaluate techniques to handle ambiguous information.
- Design experiments to test hypotheses and draw conclusions.
- Using segmentation, organize data within discrete market groups.
- Visualize data distributions to reveal new relationships and persuade others.
- Predict future outcomes with sampling and probability models.
- Communicate the results of an analysis to an audience.
- Winter 2020 (current quarter)