Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Designed for students majoring in the Isenberg School of Management, Resource Economics, Economics, and other social science majors, and for students who haven't declared a major. Introduction to basic statistical methods used to collect, summarize, and analyze numerical data. Emphasis on application to decision making; examples from the social sciences. Topics include: common statistical notation, elementary probability theory, sampling, descriptive statistics, statistical estimation and hypothesis testing. Basic algebra required. (Gen.Ed.

Intermediate level microeconomic theory. Consumer demand theory and economics of production. Geometric and mathematical approaches. Models of market behavior, related to examples. Applications to business and government decision making emphasized. Required course for more advanced departmental offerings. Prerequisite: RES-ECON 102 or ECON 103 and MATH 127 or 131.

Intermediate level microeconomic theory. Consumer demand theory and economics of production. Geometric and mathematical approaches. Models of market behavior, related to examples. Applications to business and government decision making emphasized. Required course for more advanced departmental offerings. Prerequisite: RES-ECON 102 or ECON 103 and MATH 127 or 131.