STAT 240
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Probability and Inference 1
Statistics
College of Computational, Mathematical & Physical Sciences
Course Description
Discrete sample spaces; conditional probability; random variables; mathematical expectation; moment generating functions; joint distributions; correlation; simulation.
When Taught
Fall; Winter.
Min
3
Fixed/Max
3
Fixed
3
Fixed
0
Recommended
It is strongly suggested that STAT 130 and MATH 113 be taken concurrently with or before STAT 240.
Title
Sample Spaces
Learning Outcome
Apply fundamentals of set theory, set operations, and counting to specify/enumerate events in a discrete sample space.
Title
Probability
Learning Outcome
Use the axioms of probability, conditional probability, independence, and Bayes' theorem in probabilistic calculations.
Title
Discrete Random Variables
Learning Outcome
Use probability mass functions for discrete random variables and transformations of discrete random variables.
Title
Continuous Random Variables
Learning Outcome
Use probability density and cumulative distribution functions to compute probabilities for continuous random variables.
Title
Expectation and Moments
Learning Outcome
Find and interpret expectations of random variables and functions of random variables; use moment generating functions.
Title
Named Distributions
Learning Outcome
Understand the assumptions and properties of named distributions: binomial, Poisson, uniform, exponential, normal, and gamma.
Title
Joint Distributions
Learning Outcome
Find probabilities and expectations for joint, marginal, and conditional distributions.
Title
Correlation
Learning Outcome
Calculate expectation of linear combinations, covariance, and correlation.
Title
Probabilistic Thinking
Learning Outcome
Apply tools of probability to quantitatively frame and solve problems involving uncertain outcomes.
Title
Simulation
Learning Outcome
Verify probabilistic calculations via simulation.
