CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...

The beauty of Statistics is that if you can take a large enough group of people, you can predict really well what the outcome will be overall Our research works across the fields of probability, ...

Fuzzy statistics and random variables represent a progressive fusion of traditional probability theory with the principles of fuzzy logic, enabling the treatment of imprecision and vagueness inherent ...

This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option to ...

This course covers the ideas underlying statistical modelling, its implementation through computational methods, and links to practical applications. Topics include probability and random variables, ...

Ivan Bajic (ibajic at ensc.sfu.ca) Office hours: Monday and Wednesday, 13:00-14:00 online (Zoom, see the link in course materials) Introduction to the theories of probability and random variables, and ...

CATALOG DESCRIPTION: Advanced topics in random processes: point processes, Wiener processes; Markov processes, spectral representation, series expansion of random processes, linear filtering, Wiener ...

Probability is a measure of the likelihood of events happening. The greater the proportion of times an event can happen the greater (or more likely) the probability. Events can be ordered by the ...

Historically, public opinion surveys have relied on the ability to adjust their datasets using a core set of demographics – sex, age, race and ethnicity, educational attainment, and geographic region ...