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 ...

This article resulted from our participation in the session on the “role of expert opinion and judgment in statistical inference” at the October 2017 ASA Symposium on Statistical Inference. We present ...

Multivariate statistical inference encompasses methods that evaluate multiple outcomes or parameters jointly, allowing researchers to understand complex interdependencies within data. Permutation ...

Measurement error models address the deviation between observed and true values, thereby refining the reliability of statistical inference. These frameworks are ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

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 ...

Properties of estimators: unbiasedness, consistency, efficiency and sufficiency. Methods of estimation with particular emphasis given to the method of maximum likelihood. Hypothesis testing and ...

All of the captive kea were given the opportunity to participate in the sampling task, but not all of them were interested. (Credit: Amalia Bastos.) Those remarkable kea are at it again: now the ...

This course is compulsory on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research), MSc in Statistics (Research), MSc in Statistics ...

This course is compulsory on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Financial Mathematics and Statistics and BSc in Mathematics, Statistics and Business ...