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
	
                   
               
               
               PLO 1
               
               
                  
                  - 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.
PLO 2
               
               
                  
                  - 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.
PLO 3
               
               
                  
                  - 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