MS Statistics Program Learning Objectives
Program Learning Objectives
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
- 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
- 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