Introduction to Econometrics (3) Use of simple and multiple regression models in measuring and testing economic relationships. Problems including multicollinearity, hetroskedasticity, and serial correlation.
ECON 490 Introduction to Econometrics (3)
(BA) This course meets the Bachelor of Arts degree requirements.
This course is designed for a wide range of students, including those interested in a variety of fields in business (e.g. finance and management studies) and economics, to those in the sciences and engineering who are interested in learning about data analysis and regression techniques. The course is also a good starting point for learning about empirical economics, and may thus be useful for those intending to pursue graduate studies in economics and business. Economics 490 is designed to reach a large audience, and the ultimate goal of the course is to show students that the "application of statistics to the study of economics" is not only fun, but also indispensable for a well rounded economics education. Put another way, the primary focus of the course is on applied or empirical economics. Leaning about empirical methods in this course entails extensive computer work which focuses on the analysis of economic data using currently available software packages (some completely mouse driven), such as SAS, EASYREG, GAUSS, STATA, and EVIEWS. Computer analysis ranges from constructing and interpreting plots of economic data, to forming, fitting, and interpreting regression models. In addition to the computational component of the course, students are familiarized with numerous tools used in applied work, such as mean and variance, hypothesis testing (using statistics with t-,F-, and Chi-Squared distributions), regression model building, regression model estimation, and coefficient analysis. All of the tools learned throughout the course are used in the computational exercises. Completion of this course is useful particularly for students pursuing careers in business, economics, government, banking, insurance, finance, management, consulting, and academics, for example.
Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.