Learning Outcomes

1. Define terms and concepts in mathematics and fundamental statistics.
2. Solve problems in basic probability theory and basic statistical theory using appropriate tools, including calculus-based methods and linear algebra.
3. Appropriately design data collection processes and ethically manage data.
4. Identify appropriate statistical and mathematical procedures and use appropriate software tools for implementation.
5. Draw inferences from data, big or small, using appropriate statistical methodology, including exploratory and graphical methods.
6. Effectively communicate statistical reasoning and findings.

To earn the 120 credit hour B.S. in Applied Statistics, students must complete general education and other campus-specific requirements as well as the following Applied Statistics degree components: 

Math Core (22 credits) 

• MATH-M 215 Calculus I (5 credits) 
• MATH-M 216 Calculus II (5 credits) 
• MATH-M 301 Linear Algebra and Applications OR MATH-M 303 Linear Algebra (3 credits) 
• MATH-M 311 Calculus III (3 credits) 
• MATH-M 447 Mathematical Modeling and Application I (3 credits) 
• MATH-M 448 Mathematical Modeling and Application II (3 credits)
  

Probability and Statistics Core (24 credits)

1. Complete one of the following three course/9 credit hour probability and statistics sequences 

• MATH-M 360 Elements of Probability  
• MATH-M 366 Elements of Statistical Inference  
• MATH-M 367 Introduction to Statistical Programming in R
  

OR  

• MATH-M 463 Probability (3 credits) and  
• MATH-M 466 Statistics (3 credits)  
• STAT-I 421 Modern Statistical Modeling Using R and SAS (3 credits) 

 2. Complete all of the following courses (15 credits) 

• STAT-S 431 Applied Linear Modeling  
• STAT-S 437 Categorical Data Analysis 
• STAT-S 412 Statistical Learning Using R 
• STAT-S 470 Exploratory Data Analysis
• STAT-S 352 Data Modeling and Inference

• STAT-S 432 Applied Linear Models II 
• STAT-S 450 Time Series Analysis  
• STAT-S 460 Sampling 
• STAT-I 414 Introduction to Design of Experiments  
• Additional electives may be added by the faculty at a later time. 

Programming (4 credits) 

• CSCI-A 201 Introduction to Programming, Python (4 credits)