Singapore University of Social Sciences

Applications of Regression Analysis

Applications of Regression Analysis (MTH308)


MTH308 is the second of two sequential courses on applied regression anlysis (the first one is MTH307: Principles of Regression Analysis). It will focus on the treatment of practical and application issues pertinent to regression analyis. Topics include model building & variable screening, deviations from standard assumptions, and residual analysis.

Level: 3
Credit Units: 5
Presentation Pattern: Every January


  • Model building and variable screening.
  • Models with one, two, three and more qualitative independent variables.
  • Models with both quantitative and qualitative independent variables.
  • All-possible-regression selection procedure.
  • Practical Issues in regression.
  • Data transformations.
  • Residual Analysis.
  • Detecting unequal variances.
  • Checking the normality assumption.
  • Detecting residual correlation: the Durbin-Watson test.
  • Piecewise linear, logistic and ridge regression.
  • Robust regression.

Learning Outcome

  • Apply statistical concepts in regression analysis.
  • Analyze the number of variables in regression models, including variable screening.
  • Use transformations of data to better fit regression models.
  • Verify conclusions from residual analysis, including verification with F and t-tests.
  • Test of variety of general regression models, including nonparametric models.
  • Apply regression models, including those involving binary data.
  • Construct a range of mathematical techniques to solve a variety of quantitative problems.
  • Formulate solutions to problems individually and/or as part of a group.
  • Analyze and solve a number of problem sets within strict deadlines.
  • Verify solutions related to regression analysis using IT.
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