Bharatendra Rai

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Register for this course.

Data analytics to describe, predict, advise decision-making, & improve business performance. The student will learn how to analyze business problems using a quantitative decision-making approach. This course focuses on methods, descriptive/predictive models for decision-making, & possible actions that would profit from analysis & results examined in a business context. This course is required of all undergraduate business majors.
Register for this course.

Introduction to business analytics and data mining. Topics covered include data mining, exploratory data analysis, methods for classification and prediction, affinity analysis, multiple regression, logistic regression, discriminant analysis, and clustering. Applications of business analytics and data mining methodologies to a wide variety of real world business data are included.
Register for this course.

Principles and practices underlying the continuous improvement of quality in organizations. Students will be introduced to the concept of total quality management and learn to appreciate the importance of quality as a competitive strategy. Particular attention is given to philosophies and methods of organizing for quality and to quality improvement tools, including statistical process control.
Register for this course.