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Really good video illustrating how (a) gathering data, and (b) understanding the shape of that data can give us insight onto real world issues, and help us to target approaches to tackling them "Britain has carried out one of the biggest data-gathering exercises on the gender pay gap, exposing large disparities between the average pay given to men and women in some of the country's best-known companies. We dispel some of the myths around the gap, and explain what it really means and why it matters"

Washington Post video discussing changes to Medicaid in the US. Republicans say they're not cutting Medicaid, they're increasing funding (just by less), others say this is a cut. The White House includes misleading and incomplete information in its video explaining Obamacare's failures.

Lots of quantitative information in this video about the impact of sugar on health in the US. Using comedy/performance to make a point about statistics regarding a social/health issue.

A great video example discussing a contentious issue (coal consumption) using the data!

Nice set of short videos on some fallacies from PBS. Moving the Goal Posts Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:05 The Fallacy Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:13 The Texas Sharpshooter Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:40 The Strawman Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:12 The Ad Hominem Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:23 The Black and White Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:05 The Authority Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:02 The "No True Scotsman" Fallacy | Idea Channel | PBS Digital Studios by PBS Idea Channel 2:22 3 Fallacies For Election Season! by PBS Idea Channel 11:50

hen the AP United States history students at Aragon High School in San Mateo California, scanned the professionally designed pages of www.minimumwage.com, most concluded that it was a solid, unbiased source of facts and analysis. They noted the menu of research reports, graphics and videos, and the "About" page describing the site as a project of a "nonprofit research organization" called the Employment Policies Institute. But then their teacher, Will Colglazier, demonstrated how a couple more exploratory clicks-critically, beyond the site itself-revealed that the Employment Policies Institute is considered by the Center for Media and Democracy to be a front group created by lobbyists for the restaurant and hotel industries. "I have some bright students, and a lot of them felt chagrined that they weren't able to deduce this," said Colglazier, who videotaped the episode last January. "They got duped."

A series of short articles, with videos and browser addons "investigating algorithmic injustice and the formulas that influence our lives."

A great visualisation of the income distribution (using a frequency distribution) to illustrate the change over time.

Blame the algorithm. That's become the go-to refrain for why your Instagram feed keeps surfacing the same five people or why YouTube is feeding you questionable "up next" video recommendations. But you should blame the algorithm - those ubiquitous instructions that tell computer programs what to do - for more than messing with your social media feed. Algorithms are behind many mundane, but still consequential, decisions in your life. The code often replaces humans, but that doesn't mean the results are foolproof. An algorithm can be just as flawed as their human creators. These are just some of the ways hidden calculations determine what you do and experience.

The argument is simple, and goes a bit like this. Science does not work by appeal to authority, but rather by the acquisition of experimentally verifiable evidence. Appeals to scientific bodies are appeals to authority, so should be rejected. ...If legitimate authorities are not to be consulted, presumably there is no point in having scientists around at all, as each person would need to verify any claim on their own terms and with their own resources. That would mean a speedy decline into very dark times indeed.

John Oliver explores America's wage gap between men and women and proposes a possible solution. Note: Solution proposed is 100% sarcastic. Think about the arguments being made and how they shift - e.g. the claim that 4% is "basically no wage gap" as a way to indicate a gap isn't in fact a problem. Using comedy/performance to make a point about statistics regarding a social issue

Last Week Tonight clip: John Oliver hosts a mathematically representative climate change debate, with the help of special guest Bill Nye the Science Guy, of course. Using performence & comedy to communicate a scientific point

Using comedy/performance to make a point about statistics regarding a social/health issue.

Using comedy/performance to make a point about statistics regarding a social/health issue.

Here's a discussion of how data science techniques that look at the kinds of things you watch, and try and make recommendations or customise based on that can work, and what might be problematic about that. "Some are noticing Netflix's tendency to entice black users with movie posters featuring black actors, no matter how minor their role in the film."

Why do arguments change people's minds in some cases and backfire in others? Hugo Mercier explains how arguments are more convincing when they rest on a good knowledge of the audience, taking into account what the audience believes, who they trust, and what they value.

Analysis of the day's news in an engaging & entertaining way. Host John Barron is joined by a panel of journalists, political & social commentators for a lively, thought-provoking discussion. #TheDrum This week includes discussion of vaccinations and the lock out laws - a great episode for aei

Q&A episode on misinformation and fake news. What's true, how do we distinguish high quality journalism from populism, should we worry about being in an 'echo-chamber' where we're only exposed to views that agree with us, is mainstream media fake news, etc.

Mona Chalabi on the perils of polling data and the importance of official statistics

False Equivalence: Why It's So Dangerous | Above the Noise