DAT 310 - Data Analytics I

Credit(s) 3.00
Lecture Hours: 3.00
Through this course students develop an in-depth knowledge of the following statistics principles: Review of Multiple Regression Analysis, Logistic Regression Analysis, Discriminant Analysis, Cluster Analysis, Time Series Analysis, and Forecasting Techniques.

Prerequisite(s): DAT 301
SLOs:
Upon successful completion of this course, students will be able to:

Implement decision-making skills by basing decisions upon the outcome of statistical tests.
Analyze real-world scenarios and determine the appropriate type of analytical problem-solving techniques to utilize.
Interpret the results of print-outs (Multiple Regression Analysis, Logistic Regression Analysis, Discriminant Analysis, Cluster Analysis, and Time Series Analysis, etc) generated from SPSS.
Explain the reasoning/basis behind each statistical test.
Interpret the statistical results in a report format.