Indices of multiple deprivation (IMD) are widely-used datasets within the UK to classify the relative deprivation (essentially a measure of poverty) of small areas. Multiple components of deprivation are weighted with different strengths and compiled into a single score of deprivation. The calculation and publication of the indices is devolved and indices of multiple deprivation for Wales, Scotland, England, and Northern Ireland are calculated separately. While the components of deprivation that make up the overall deprivation score are similar in all four nations of the UK the weights assigned to each component, the size of the geographies for which deprivation scores are calculated, and the years of calculation are different. As a result levels of deprivation cannot be easily compared between nations. The geography at which IMDs are produced varies across the nations of the UK and has varied over time. Currently the smallest geography for which IMDs are published is LSOA level in both England and Wales, data zone level for Scotland, and Super Output Area (SOA) for Northern Ireland. Early versions of the English IMDs were published at electoral ward and English local authority level. The use of IMDs in social analysis aims to balance the desire for a single number describing the concept of deprivation in a place and the recognition that deprivation has many interacting components. IMDs may be an improvement over simpler measures of deprivation such as low average household disposable income because they capture variables such as the advantage of access to a good school and the disadvantage of exposure to high levels of air pollution. A potential disadvantage is that the choice of components and the weighting of those components in the construction of the overall multiple deprivation score is unavoidably subjective. (Wikipedia).
Percentiles, Deciles, Quartiles
Understanding percentiles, quartiles, and deciles through definitions and examples
From playlist Unit 1: Descriptive Statistics
Determining values of a variable at a particular percentile in a normal distribution
From playlist Unit 2: Normal Distributions
Multimeter Review / DMM Review / buyers guide / tutorial
A list of my multimeters can be purchased here: http://astore.amazon.com/m0711-20?_encoding=UTF8&node=5 In this video I do a review of several digital multimeters. I compare features and functionality. I explain safety features, number of digits, display count, accuracy and resolution. Th
From playlist Multimeter reviews, buyers guide and comparisons.
Introduction to standard deviation, IQR [Inter-Quartile Range], and range
From playlist Unit 1: Descriptive Statistics
A silent video testing series for convergence or divergence using the comparison test
From playlist 242 spring 2012 exam 3
Data science applications: Urban data science - Professor Cecilia Mascolo, University of Cambridge
Bio Cecilia Mascolo is Full Professor of Mobile Systems in the Computer Laboratory, University of Cambridge, UK. Prior joining Cambridge in 2008, she has been a faculty member in the Department of Computer Science at University College London. Her research interests are in human mobility
From playlist Data science classes
"Evolutionary Medicine" Sinauer Associates (2015) is the textbook that supports these lectures. Instructors can request examination copies and sign up to download figures here: http://www.sinauer.com/catalog/medical/evolutionary-medicine.html
From playlist Evolution and Medicine (2015) with Stephen Stearns
Irrigation Efficiencies - Part 1
From playlist TEMP 1
Lessons Learned on Poverty Measurement through Household Panel Surveys
Panel surveys offer insights into the development process that data collected for short-term purposes cannot provide. They enable development economics researchers to follow households over time and observe multiple aspects of individuals’ lives, enabling a better understanding of the dyna
From playlist Yale Economic Growth Center (EGC)
Team 3015 Charter School Wilmington presentation 2014
In Moody's Mega Math Challenge 2014, more than 5,000 high school students across the U.S. set out to determine what makes a school lunch easy on the stomach...and the wallet. Participants pored over data, crunched numbers, and used mathematical analysis to determine how school lunches can
From playlist M3 Challenge 2014 Team Presentations
Unveiling Dr. Rhonda Patrick's Secret to Longer Life: Sauna, Nutrition, Rigorous Exercise & More!
The Passion Struck Podcast is HERE!! 💥 https://passionstruck.com/passion-struck-podcast/👈 Listen, follow, and rate wherever you listen to your favorite podcasts OR watch here on YouTube. New episodes drop every Tuesday, Thursday, and Friday! --- On today's show, I have the pleasure of hos
From playlist As Seen On
From playlist Basic Statistics (Descriptive Statistics)
Ruby On Ales 2013 Hacking Cognition by Jonan Scheffler
We are fortunate as software developers to spend our lives learning. Our careers require us to keep pace with an industry that innovates like few others and we adapt ourselves to constant change. Given the amount of time we dedicate to learning it is surprising that we don't make a greater
From playlist Ruby on Ales 2013
Vincent Lafforgue - Chtoucas et paramétrisation de Langlands
On expliquera d’abord la paramétrisation globale des formes automorphes cuspidales sur les corps de fonctions, avec une simplification de la preuve par rapport au cours donné en octobre 2013 à l’IHES: http://www.youtube.com/playlist?list=PLx5f8IelFRgGVy2henk_0KhP31-EbyOoi On évoquera ensu
From playlist Journée inaugurale du Laboratoire Alexander Grothendieck
Covariance (7 of 17) Example of the Covariance Matrix - EX 2
Visit http://ilectureonline.com for more math and science lectures! To donate:a http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will find the covariance matrix of 2 data sets. Example 2 Next video in this series can be seen at: https://youtu.be/1_QWGUM_31M
From playlist COVARIANCE AND VARIANCE
Understanding Transport-Health-Environment interactions using new micro-mobility data
The afternoon will be orientated towards academics/researchers who are working with a variety of new forms of data (location, image, social media, transactions etc) in a transport/mobility context. The workshop will be stocktaking on recent research, identifying research needs and also loo
From playlist Workshop on New Forms of Data for Mobility
Disrupting Attachment | Revision for Psychology A-Level and IB
I want to help you achieve the grades you (and I) know you are capable of; these grades are the stepping stone to your future. Even if you don't want to study science or maths further, the grades you get now will open doors in the future. Study (daily and weekly) planners https://www.prim
From playlist AQA A-Level Psychology | Revision Playlist
Dr. Matthew Walker on Sleep for Enhancing Learning, Creativity, Immunity, and Glymphatic System
This episode features Matthew Walker, PhD, who is a professor of neuroscience and psychology at the University of California, Berkeley, and serves as the Director of the Center for Human Sleep Science. Formerly, Dr. Walker served as a professor of psychiatry at the Harvard Medical School.
From playlist Interviews
Computing z-scores(standard scores) and comparing them
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Computing z-scores(standard scores) and comparing them
From playlist Statistics