You are now in the main content area
MTH 304
Probability
Topics include: Elements of Probability Theory. Discrete Probability Distribution. (Hyper-geometric, Binomial, Poisson). Normal Distribution and its applications. Lognormal Distribution, Multivariate Distributions, Covariance and Correlation, Moment Generating Functions, Central limit theorem and applications. A statistics computer package will be used in this course.
Weekly Contact: Lab: 1 hr. Lecture: 3 hrs.
GPA Weight: 1.00
Course Count: 1.00
Billing Units: 1
Mentioned in the Following Calendar Pages
*List may not include courses that are on a common table shared between programs.
- CPS 521 - Introduction to Data Science
- CPS 707 - Software Verification and Validation
- CPS 721 - Artificial Intelligence I
- CPS 803 - Machine Learning
- CPS 824 - Reinforcement Learning
- CPS 843 - Introduction to Computer Vision
- CPS 844 - Data Mining
- CPS 870 - Applied Natural Language Processing
- Computer Science Core Elective Table I
- ECN 129 - Statistics for Economics I
- Financial Mathematics
- MTH 380 - Probability and Statistics I
- MTH 404 - Statistics
- MTH 410 - Statistics
- MTH 500 - Introduction to Stochastic Processes
- MTH 642 - Data Analytics: Advanced Methods
- MTH 655 - Machine Learning in Business
- MTH 665 - Mathematical Game Theory
- MTH 707 - Modelling and Searching Networks
- Mathematics and its Applications
- PCS 335 - Thermodynamics and Statistical Physics
- PCS 352 - Nuclear Physics/Radiation Protection
- PCS 810 - Complex Networks and Applications
- SOC 411 - Intro to Quantitative Data Analysis