MS Statistics Program Learning Objectives

Program Learning Objectives

Assessment Schedule

PLO Course Semester Year
1 164 Spring 2024
2 261A Fall 2024
3 269 Spring 2025

Map of Course Learning Objectives (CLOs) to PLOs


  • Derive a point estimator for one or more parameters of a parametric model using the method of moments and the method of maximum likelihood.
  • Construct a confidence interval using the method of pivotal quantity and large-sample approximations.
  • Derive a test of statistical hypotheses based on the Neyman-Pearson lemma and the generalized likelihood ratio method.


  • Develop an appropriate regression model for a given application.
  • Assess the validity of model assumptions for a given data set.
  • Set up and test meaningful hypotheses for a given data set.
  • Analyze data using statistical software and formulate conclusions in the context of the problem.


  • Describe the characteristics of an effective consultant, a satisfied client,
    and a successful consulting session.
  • Identify the issues involving statistical ethics.
  • Present effective oral and written arguments.

Map of PLOs to University Learning Goals (ULGs)

  • ULG 1 (Specialized knowledge): PLOs 1 and 3
  • ULG 2 (Broad integrative knowledge): PLOs 1, 2, and 3
  • ULG 3 (Intellectual skills): PLOs 1, 2, and 3
  • ULG 4 (Applied knowledge): PLOs 2 and 3
  • ULG 5 (Social and global responsibilities): PLOs 1 and 3