CMPE343

Introduction to Probability and Statistics for Computer Engineers

Course Information  

Catalog Description  

Introduction to probability theory. Random variables, expectation, variance and moment generating functions. Distributions: Bernoulli, binomial, uniform, Gaussian, exponential, Poisson, gamma. Introduction to statistical concepts. Sampling and sample statistics. Point and interval estimation. Hypothesis testing. Regression. Numerical and computational aspects of random variable generation, sampling, and estimation.

Course Learning Outcomes  

The objective of this course is to provide the foundations of probability theory and statistics. Upon successful completion of this course, students will have gained the necessary understanding on:

• Laws of probability theory and its applications
• Use of Bayes’ theorem
• Concept of random variables
• Probability distributions and their properties
• Concept of sampling
• Concept of hypothesis testing
• Concept of regression
• Practical implementation of some of the probability and statistics concepts

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