STAT 324 PROBABILITY AND STATISTICS FOR ENGINEERS AND SCIENTISTS

Summary of the main learning outcomes for students enrolled in the course.

• Introduction to Sample space, Random events, Probability rules, Conditional probability, Baye’s rule.
• Definition of Random variables, Discrete and Continuous distributions.
• Definition of the mean (mathematical expectation) and the variance of a random variable. Mean and variance of a linear combination of independent random variables.
• Definition of Discrete distributions (Uniform, Binomial, Hyper geometric, Poisson).
• Definition of Continuous distributions (Uniform, Exponential, Normal).
• Sampling distributions of some sample statistics, the t-distribution.
• Emphasizing the concept of Estimation methods: Point estimation, Confidence interval estimation. 
• Introducing the concepts involved in Testing Hypotheses. Hypotheses testing of a single Population parameter (mean, proportion, difference between two means and difference between two proportions of independent populations.

Introducing the concept of simple linear correlation and linear regression.