Statistics Curriculum Map
 

Shown below are the 2000, 3000- and 4000-level courses required for Statistics majors, and the emphasis – None (0), low (1), moderate (2), high (3) – each course places on each learning objective. 

Student Learning Outcomes
MAC 2313 MAS 3105 STA 4321 STA 3163 STA 3164 STA 4322 STA 4945
1.  Recognize and apply principles of theoretical statistics to solve basic probability problems and mathematical statistics problems 0 1 3 1 1 3 1
2.  Recognize and apply principles of applied statistics such as analysis of variance, linear regression, correlation and nonparametric methods to analyze data 0 0 0 3 3 2 3
3.  Use statistical software such as SAS to solve basic problems 0 0 0 3 3 0 3
4.  Describe data sets using standard summary and graphical methods 0 0 1 3 3 1 3
Critical Thinking Skills
 
5.  Apply principles of theoretical statistics and applied statistics to solve advanced and/or complex statistics problems 0 0 3 1 1 3 2
6.  Design an experiment using standard methodology 0 0 0 1 1 0 2
7.  Choose, implement and interpret appropriate statistical inferences 0 0 1 3 3 2 3
8.  Use technology to solve problems 1 2 0 3 3 0 3
9.  Create and use mathematical models 1 1 0 2 2 0 3
Communication Skills
 
10. Write coherent and correct reports and solutions to problems 3 3 3 3 3 3 3
11. Verbally present proofs and solutions to problems 1 1 1 1 1 1 3
12. Explain statistics verbally. 0 0 1 1 1 1 3
13. Explain statistics in writing. 0 0 2 3 3 3 3