DAT 301 - Introduction to Data Analytics

Credit(s) 3.00
Lecture Hours: 3.00
This course covers the theory of statistical analysis with emphasis upon the practical applications to data analysis and decision making scenarios. Topics covered included: hypothesis testing, Chi-Square goodness of fit tests, analysis of variance, linear regression analysis, and Time Series and Forecasting, Statistical Quality Control, and Decision making.

Prerequisite(s): CSC 116 and MAT 156
SLOs:
Upon successful completion of this course, students will be able to:

Develop and refine decision-making skills by basing decision 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 (ANOVA, t-tests, regression analysis, time series, statistical quality control, etc) generated from SPSS.
Understand the reasoning/basis behind each statistical test.
Manually solve selected problems