Coursework

Required Courses

The Master of Statistics degree requires a minimum of 30 semester hours (ten courses). This includes seven required courses. Most students take one course per semester while others take a full-time load of three courses per semester.  

We offer our required courses most semesters, allowing the courses to be done in sequence.  For instance, the required ST 501/502/503 courses can be taken in sequence starting in the summer or fall.

• ST 501 – Fundamentals of Statistical Inference I (Summer, Fall)
• ST 502 – Fundamentals of Statistical Inference II (Fall, Spring)
• ST 503 – Fundamentals of Linear Models and Regression (Spring, Summer)

The required ST 517/518 sequence can be taken starting in the summer or fall as well.

• ST 517 – Applied Statistical Methods I (Summer, Fall)
• ST 518 – Applied Statistical Methods II (Fall, Spring)

One programming intensive course from the following list is required:

• ST 554 – Big Data (Python) (Spring, Summer)
• ST 555 – Statistical Programming I (SAS) (Summer, Fall, Spring)
• ST 558 – Data Science for Statisticians (R) (Summer, Fall)

Lastly, our required ‘capstone’ course is available each spring and summer.

• ST 542 – Statistical Practice (Spring, Summer)

For those entering the program with a strong statistics background, the ST 517 requirement can be waived.  For those entering the program with a strong programming background, the requirement of ST 554, ST 555, or ST 558 can be waived. In both cases, the course would be replaced with a three-credit elective.  

Substitutions may be made for courses taken elsewhere, but transfer credit is not given.

Elective Courses

To fill out the remaining nine required credits (three courses), elective courses are taken. We currently do not offer the concentrations available for the in-person master’s degree as we do not have as many elective options available in the online program.

The offerings of electives generally rotates each semester depending on interest and demand.  When scheduling, members of the program are polled and feedback on elective offerings is considered.  

Electives and when they are commonly offered are given below.

• ST 519 – Teaching and Learning of Statistical Thinking (Spring)
• ST 534 – Applied Time Series (Fall)
• ST 537 – Applied Multivariate and Longitudinal Data Analysis (Fall)
• ST 540 – Applied Bayesian Analysis (Spring)
• ST 544 – Applied Categorical Data Analysis (Spring)
• ST 556 – Statistical Programming II (Spring, Summer)
• ST 563 – Introduction to Statistical Learning (Spring, Summer)

Students can also take more than one programming intensive course from the required courses list. Local students can take in-person courses if approved by the program director. Non-ST electives can also be taken with approval from the program director.

Example Plan of Work

Your coursework could really begin in a number of ways.  Below you’ll find a few example course sequences depending on when you are admitted and your intended course load.