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24 February 2021 - Simon Riche - Hecke action on the principal block of reductive algebraic groups

The subtitles/captions on this talk are being edited. They will be available within 2 weeks of the talk being published.24 February 2021Simon RicheTitle: Hecke action on the principal block of…

From  OLLIE Quinn on March 2nd, 2021 0 likes 25 plays 0  

FDS-S2-03-1-3 Large sample theory of A/B testing

We work through how to apply large-sample theory to A/B testing.

From  David Sterratt on January 28th, 2021 0 likes 130 plays 0  

FDS-S2-03-1-1 principle of A/B testing

We explain the principle of A/B testing, and how to derive confidence intervals for the difference in population proportions using the bootstrap.

From  David Sterratt on January 28th, 2021 0 likes 161 plays 0  

FDS-S2-02-2-3 Multiple logistic regression and confidence and intervals

We extend logistic regression to multiple independent variables, and show how we can use the boostrap to estimate confidence intervals for coefficients, and to test hypotheses.

From  David Sterratt on January 20th, 2021 0 likes 147 plays 0  

FDS-S2-01-2-9 Estimating confidence intervals for means of small samples

We'll look at means from small samples, where the normal approximation of the sampling distribution of the mean breaks down.

From  David Sterratt on January 15th, 2021 0 likes 126 plays 0  

FDS-S2-01-2-5 Definition of confidence intervals

We give a formal definition of confidence intervals, and show how the random interval can be converted to a random variable

From  David Sterratt on January 15th, 2021 0 likes 146 plays 0  

FDS-S2-01-2-3 Standard error

We introduce the standard error of an estimator and, in particular, the standard error of the mean.

From  David Sterratt on January 14th, 2021 0 likes 168 plays 0  

FDS-S2-01-2-2 Bias and variance

We'll introduce the concept of bias and variance of estimators.

From  David Sterratt on January 14th, 2021 0 likes 183 plays 0  

FDS-S2-01-2-1 Introduction to estimation

We'll introduce the concept of estimating a population or distribution parameter from a sample.

From  David Sterratt on January 14th, 2021 0 likes 204 plays 0  

Topic 47: Cramer-Rao Lower Bound for Parameter Vectors (PETARS, Chapter 6)

In this video, the concepts in estimation theory introduced so far for scalar random variables are extended to deal with estimating multiple parameters, for example the mean and variance of a…

From  James Hopgood on October 26th, 2020 0 likes 78 plays 0  

Topic 43: Measuring Performance of an Estimator (PETARS, Chapter 6)

In this video, the question of measuring and quantifying the performance of an estimator is discussed. The video focusses on the concepts and definitions of bias and variance of the probability…

From  James Hopgood on October 22nd, 2020 0 likes 95 plays 0  

Topic 42: Introduction to Estimation Theory (PETARS, Chapter 6)

In this video, Estimation Theory is introduced in which unknown parameters are estimated from data, rather than assuming that problems can be described by fully known distributions or statistics.…

From  James Hopgood on October 21st, 2020 0 likes 103 plays 0  

Topic 37: Linear Transformations (PETARS, Chapter 5)

Since linear transformations is such an important class of signal processing systems, this video looks at considering linear transformations of random vectors. After discussing various types of…

From  James Hopgood on October 14th, 2020 0 likes 81 plays 0  

Topic 33: Auxiliary Variables (PETARS, Chapter 5)

Auxiliary variables are introduced as a method for calculating a single function of multiple random variables, through a two-stage process of using the probability transformation rule followed by…

From  James Hopgood on October 7th, 2020 0 likes 101 plays 0  

Preliminaries - perceptrons

Preliminaries - perceptrons

From  Nigel Goddard on November 12th, 2016 1 likes 1,890 plays 0  

Breaking ties between nearest neighbors

Breaking ties between nearest neighbors

From  Nigel Goddard on September 21st, 2016 1 likes 1,817 plays 0