This course focuses on using statistical concepts and techniques to analyze a variety of problems in information systems, information technology, business, and other disciplines. Topics expand on student’s knowledge of descriptive statistics, sampling, distributions, confidence intervals, correlation, and introduce regression and multiple regression, residual analysis, analysis of variance, robustness, and big data, through statistical programming. The integrated lab component of the course gives students hands-on exposure to data analysis practices. Pre-requisite(s): MTH 102 (or higher) and CSS 225, or permission of Program Chair or designate. Co-requisite(s): None. 5 quarter hours