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

Explain why probability is important to statistics and data science. See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance ...

Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...

Stochastic differential equations (SDEs) and random processes form a central framework for modelling systems influenced by inherent uncertainties. These mathematical constructs are used to rigorously ...

Here’s a deceptively simple exercise: Come up with a random phone number. Seven digits in a sequence, chosen so that every digit is equally likely, and so that your choice of one digit doesn’t affect ...

Pew Research Center designed this study to assess the current state of online survey sampling methods – both probability-based and opt-in – and determine their accuracy on general population estimates ...