Student Learning Outcomes

1. Basic probability concepts and skills in working with basic probability formulas

2. Working knowledge of one computing technique from the list: MATLAB, MINITAB, R, SAS, and SPSS and the interpretation of its computing outputs

3. Data analysis ability in one of the following subjects: regression analysis, design of experiment, survey sampling, contingency table, engineering statistics, stochastic processing and time series analysis

4. Statistical application in one of the following areas: biology, computer science, earth science, environmental science, communications, economics, engineering, forestry, geography, public affairs, political science, management, psychology, and sociology and social work

Basic Statistics (3 credits)

• APM 395 - Probability and Statistics for Engineering *
• CIS 321 - Introduction to Probability and Statistics
• ECN 521 - Economic Statistics
• MAS 261 - Introductory Statistics for Management
• MAT 122 - Probability and Statistics for the Liberal Arts II
• MAT 221 - Elementary Probability and Statistics I
• MAT 521 - Introduction to Probability
• MFE 326 - Probability and Statistical Methods for Engineers

Regression Analysis (3 credits)

• ECN 522 - Econometric Methods
• BUA 466 - Data Mining for Business

Additional Coursework (12 credits)

• APM 510 - Statistical Analysis *
• ECS 525 - Probability for Engineers
• ECS 526 - Statistics for Engineers
• GEO 386 - Quantitative Geographic Analysis
• MAT 122 - Probability and Statistics for the Liberal Arts II
• MAT 222 - Elementary Probability and Statistics II
• MAT 525 - Mathematical Statistics
• MAT 526 - Introduction to Stochastic Processes
• MAS 362 - Decision Tools for Management
• MAS 477 - Time Series Analysis and Forecasting
• MAX 201 - Quantitative Methods for the Social Sciences
• PSY 252 - Statistical Methods II
• SOC 318 - Introduction to Research

Note:

* Courses with an APM prefix are offered by the SUNY College of Environmental Science and Forestry.