
We work through how to apply largesample theory to A/B testing.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 28th, 2021


We explain the principle of A/B testing, and how to derive confidence intervals for the difference in population proportions using the bootstrap.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 28th, 2021


First video on Informed Search Algorithms.
Course Code
INFR08010 Licence Type
All rights reserved The University of Edinburgh Language
English


We'll look at means from small samples, where the normal approximation of the sampling distribution of the mean breaks down.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial No Derivatives Language
English Date Created
January 15th, 2021


We'll consider two aspects of the interpretation of confidence intervals
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 15th, 2021


We introduce the bootstrap method of estimating confidence intervals
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 15th, 2021


Here we introduce the principle of confidence intervals graphically.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 14th, 2021


We introduce the standard error of an estimator and, in particular, the standard error of the mean.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 14th, 2021


We'll introduce the concept of bias and variance of estimators.
Course Code
INFR08030 Publisher
David Sterratt Licence Type
Creative Commons  Attribution Non Commercial Language
English Date Created
January 14th, 2021


Constructing a bootstrap confidence interval for the slope
Course Code
MATH08077 Licence Type
Creative Commons  Attribution Non Commercial Share A Like


The least squares approach is presented as a nonprobabilistic method
for designing an estimator of a set of parameters, assuming a model is
provided for describing the data. This is presented as…
Course Code
PGEE11164 Licence Type
All rights reserved Date Created
October 28th, 2020


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.…
Course Code
PGEE11164 Licence Type
All rights reserved Date Created
October 19th, 2020


Estimating the mean height of the class; Standard Error
Course Code
PSYL11053 Licence Type
Creative Commons  Attribution Language
English Date Created
September 20th, 2020


Careers in Tech 2018 Employer Video  Employ.ed
Licence Type
All rights reserved The University of Edinburgh


Mitigating Climate Change  Carbon Capture Storage
Licence Type
Creative Commons  Attribution


A probabilistic formulation of the linear model
Licence Type
Creative Commons  Attribution
