STAT-6105: Measure and Probability
Description: Development of measure theoretic foundations of probability theory. 6105: sigma fields, probability, and general measures; random variables, measurability and distributions, integration, and expectation; product measures; Radon-Nikodym theorem and conditioning. 6106: Random variables and strong and weak laws of large numbers; characteristic functions, central limit theorem and martingales; stochastic processes and Brownian motion. 6105 partially duplicates Math 5225. Must be enrolled in PhD program.
Pathways: N/A
Course Hours: 3 credits
Corequisites: N/A
Crosslist: N/A
Repeatability: N/A
Sections Taught: 16
Average GPA: 3.90 (A)
Strict A Rate (No A-) : 92.34%
Average Withdrawal Rate: 0.00%
| Pang Du | 2022 | 96.4% | 1.8% | 0.6% | 0.0% | 1.3% | 0.0% | 3.92 | 10 |
| George R Terrell | 2015 | 93.1% | 6.9% | 0.0% | 0.0% | 0.0% | 0.0% | 3.93 | 4 |
| Dan J Spitzner | 2006 | 77.8% | 22.2% | 0.0% | 0.0% | 0.0% | 0.0% | 3.73 | 2 |