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Course Descriptions

The curriculum of the program in the Department of Mathematics is designed to provide a broad education in both theoretical and applied mathematics. It also develops the scientific knowledge and the problem solving, computing, and communications skills that are critical to a successful mathematically based career.

MA 485 - Applied Regression Analysis & Introduction to Time Series

  • Credit Hours: 4R-0L-4C
  • Term Available: W (odd years)
  • Graduate Studies Eligible: No
  • Prerequisites: MA 212, and either MA 223 or MA 382
  • Corequisites: None

Review of simple linear regression; confidence and prediction intervals for estimated values using simple linear regression; introduction to such concepts as model fit, misspecification, multi-collinearity, heterogeneous variances and transformation of both independent and dependent variables; introduction to multiple regression to include polynomial regression; use of dummy variables and diagnostics based on residuals; sequential variable selection to include forward inclusion and backward exclusion of variables; best subset regression; introduction to time series; autocorrelation; moving averages and exponential smoothing.

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