Data Analysis and Probability Models

Course #OS3080

Est.imated Completion Time: 3 months

POC: NPS Online Support

Overview

Coming soon...

Learn hypothesis testing for contingency tables, ANOVA, and nonparametric tests.
Discuss and design experiments for two-factor, three factor and larger. Methods to screen experiments when number of factors are large.
Effectively use simple and multiple regression to create models for data.
Learn how to effectively work with time series, including use of lagging variables, autoregression techniques and smoothing models.
Review basic probability concepts and Bayes’ theorem. Learn about conditioning to compute expectation and probability.
Introduce reliability for systems in series and/or parallel. Define failure rate and hazard rate. Fit parametric models to failure data including censored data.
Review Poisson and exponential distributions. Define Poisson Processes.
Introduce stochastic models. Learn terminology for Markov models, one-step of n-step transition matrices, steady state probabilities and mean first passage time.

Offerings database access

Asset Publisher

08 Jan 2024

Spring Quarter applications due

01 Apr 2024

Summer Quarter applications due

08 Jul 2024

Fall Quarter applications due

Asset Publisher

12 Dec 2023 – 14 Dec 2023

Fall Quarter final examinations

15 Dec 2023

Fall Quarter graduation

18 Dec 2023 – 05 Jan 2024

Winter break