INTRO TO BUSINESS ANALYTICS II

Catalog description

Analytics is used to transform data into actions through analysis and insights in the context of organizational decision-making and problem solving. Analytics include the extensive use of data, statistical and quantitative analysis. The ability to leverage data effectively to drive rapid, precise and profitable decisions is a critical strategic advantage for companies. The increasing availability of braod and deep sources of information - Big Data - increases the importance of business analytics in enterprises of all types and sizes. This course aims to build upon foundational mathematical and statistical basis for managerial decision making to introduce higher-level and advanced statistical applications. This course begins with a review of descriptive statistics, including central tendency, variability, probability and data visualization. After a review, the course covers estimation, confidence intervals and effect size. Inferential statistics are introduced using a range of decision-making tools - t tests; one-way, factorial, and covariate ANOVAs; linear and multiple linear regression; regression model building; forecasting, time series, and trend analysis. Further considerations for big data, analysis techniques, and methods for quality control are made with an emphasis on the use of these techniques in data analysis.