OA3101: Probability - NPS Online
Overview
Probability axioms, counting techniques, conditional probability. Discrete and continuous probability distributions: binomial, hypergeometric, negative binomial, Poisson, normal, exponential, gamma, and others. Joint probability distributions, conditional distributions and conditional expectation, linear functions. Random samples, probability plots. CO-REQUISITES: MA1118 and MA3042.
Corequisites
- MA1118
- MA3042
Learning Outcomes
After successfully completing this course, students will be able to:
· Identify the components that comprise a probability model, and the quantities that would need to be estimated in order to draw quantitative conclusions from the model.
· Use counting techniques to solve probability problems involving equally likely outcomes.
· Compute conditional probabilities using their definition and using Bayes’ Rule.
· Identify commonly used discrete probability distributions, articulate their underlying assumptions, and use them to compute probabilities.
· Identify commonly used continuous probability distributions, articulate their underlying assumptions, and use them to compute probabilities.
· Compute probabilities using joint probability distributions.
Application Deadlines
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Academic Calendar
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