MATH062 HM - Introduction to Probability and Statistics

Credit(s): 3

Instructor(s): Haddock, Martonosi, Williams

Offered: Spring

Description: Sample spaces, events, axioms for probabilities; conditional probabilities and Bayes' theorem; random variables and their distributions, discrete and continuous; expected values, means and variances; covariance and correlation; law of large numbers and central limit theorem; point and interval estima­tion; hypothesis testing; simple linear regression; applications to analyzing real data sets. Possible additional topics include ANOVA, multiple regression, and logistic regression. 

Prerequisite(s): MATH019 HM  
Corequisite(s): MATH073 HM  

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