An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

An introduction to operations management in manufacturing and service industries. Emphasis on learning the basic principles, using MS EXCEL, required to organize and manage service and manufacturing organizations. Topics may include improved facility layout, project management, supply-chain management, Just-in-Time systems, inventory management, scheduling, and work force management. Discussions of real world applications frequently used to demonstrate concepts.

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Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.

Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.

Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.

Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.

Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.

Second semester of applied business statistics for Isenberg School of Management majors. Emphasis on understanding and interpreting statistical information, and using it to form sound judgments in business situations. Includes brief review of sampling, sampling distributions, and basic inference for one-sample situations; comparison of two populations, chi-square tests for contingency tables, analysis of variance, simple linear regression, and topics in multiple regression and time series. Statistical software used for computations. A project using regression methods required.