This short course provides an overview of statistical analyses useful for comparing the means for one or more samples. The statistical training will include the discussion of the one sample t-test, ...

In recent years, a need for compact representations of databases has become apparent, for example in natural language understanding, machine learning, and decision making, accompanied by a need for ...

DTSA 5001 Probability and Foundations for Data Science and AI - Same as APPA 5001 DTSA 5002 Statistical Estimation for Data Science and AI - Same as APPA 5003 DTSA 5003 Statistical Inference and ...

Eleanor has an undergraduate degree in zoology from the University of Reading and a master’s in wildlife documentary production from the University of Salford.View full profile Eleanor has an ...

With a population of over 27 million and counting, crows seem almost ubiquitous across the US. Their loud “caws” are hard to miss, and the tone of these cries varies depending on what the birds are ...

Figure 1: Measuring fit of the Ricker model. There is extremely strong statistical evidence that the Nicholson blowfly fluctuations are limit cycles perturbed by noise. They are not the result of ...

In this article, the problem of semi-parametric inference on the parameters of a multidimensional Lévy process L t with independent components based on the low-frequency observations of the ...

The most widely used statistical inference procedures were invented more than 10 years ago and are not well suited for handling state-of-the art high-resolution neuroimaging data. MRI technology ...

Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...