UTS-AEI

A good example of poor reporting of a medical study, the Daily Mail claimed that "Diets laden with butter, cream and cheese 'can help combat surge in type 2 diabetes' - but the evidence does not support that argument - looking at the evidence, it's clear there is a small quantifiable difference between the two groups analysed, and that the study focuses on a short period of time.

If you were surprised by the result of the Brexit vote in the UK or by the Trump victory in the US, you might live in an echo chamber - a self-reinforcing world of people who share the same opinions as you. Echo chambers are a problem, and not just because it means some people make incorrect predictions about political events. They threaten our democratic conversation, splitting up the common ground of assumption and fact that is needed for diverse people to talk to each other. A few tools are mentioned in the post that help you see "the other side" of a story - you might like to play with them, e.g. http://politecho.org "is a browser extension that shows the political biases of your friends and Facebook newsfeed"

I set out to discover which Harry Potter actors have had the best careers since the franchise kicked off in 2001 - similar to the analysis I did of people who've acted in the Star Wars franchise. How many other movies did they make, how good were those movies and how much money did they bring in? To find out, I turned to IMDb. For every actor who was credited in one of the eight Harry Potter movies, I pulled every full-length feature film2 that he or she was credited in, as well as the ratings for each film and its box-office take, if IMDb had it.

Where else have you seen risk claims like "x causes 50% increase in health-problem y"? Do you tend to trust these claims? Do you understand what they mean? Would they change your behaviour? "Interpreting health (or any other) risk estimates reported in the media is not straightforward. Even health professionals can get tripped up trying to make sense of these statistics, so it is no wonder the public can easily be confused or misled. Often there is tendency to overreact to risk estimates, so it's worth unpacking what these really mean."

Of the 6,916 news items examined in our research, more than 20% featured a statistic. Most of these statistical references were fairly vague, with little or limited context or explanation. Overall, only a third provided some context or made use of comparative data.

'Significance' is a magazine published by the UK Royal Statistical Society and American Statistical Association. E.g. this article discusses the data we might use to analyse food security, thinking about what sources of data are available and the questions they might help us answer. "data on food insecurity is biased towards the environment in which it was created and the priorities of those who collect or commission it. Data from schools is concerned with reimbursement; government data might be focused on budgetary constraints or accountability; grocery stores could (if willing) tell us what food is bought, but not how it is used; meanwhile, non-profits are most interested in demonstrating impact to funders. There is a wide variety of data sets available, but very few are created with the intent to understand the real drivers of hunger and poverty. The data may be repurposed, but modellers must be especially careful to moderate the assumptions of each data set. ...... It is also especially important that those experiencing hunger and poverty are consulted when designing any data analysis project. The input of domain experts is crucial to the success of data science endeavours, and those experiencing poverty know the right questions to ask."

Argument: Because deductions (the amount of income you can claim is not-taxable) will be reduced, even though the tax rate will go down, the richest will not in fact see an absolute reduction in tax paid. Counterargument - looking at the data, this is in fact not the case...

Ourworldindata is a great website discussing lots of different datasets about global issues. This example data-story discusses the issue of global health, giving an overview (and lots of great visualisations), and discussing how we actually measure 'health' (life expectancy, quality of life measures, etc.).

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

"Fenofibrate may reduce heart disease risk in some patients with type 2 diabetes" The release goes on to suggest that among patients with type 2 diabetes who also had high levels of triglycerides and low levels of "good" cholesterol, the drug lowered the risk of cardiovascular events compared with placebo. Sounds like it might be time to ask your doctor about the benefits of fenofibrate, right? Before you schedule that appointment, you might want to consider this detail that wan't included in the news release: The findings of benefit came from a small group of patients within a larger study whose results had previously been reported. And that larger study, known as ACCORD, found no overall cardiovascular benefit among patients treated with fenofibrate.

There's a huge debate going on in social science right now. The question is simple, and strikes near the heart of all research: What counts as solid evidence? The answer matters because many disciplines are currently in the midst of a "replication crisis" where even textbook studies aren't holding up against rigorous retesting. ...

Some advice on evaluating claims made on data Bergstrom believes that calling bullshit on data, big or otherwise, doesn't require a statistics degree-only common sense and a few habits of mind. "You don't have to understand all the gears inside a black box in order to evaluate what you're being told," he said. For those who were unable to enroll in INFO 198/BIOL 106B this spring, here is some of his and West's advice:

just knowing facts doesn't necessarily guarantee that one's opinions and behaviors will be consistent with them. For example, many people "know" that recycling is beneficial but still throw plastic bottles in the trash. Or they read an online article by a scientist about the necessity of vaccines, but leave comments expressing outrage that doctors are trying to further a pro-vaccine agenda. Convincing people that scientific evidence has merit and should guide behavior may be the greatest science communication challenge, particularly in our "post-truth" era. Luckily, we know a lot about human psychology - how people perceive, reason and learn about the world - and many lessons from psychology can be applied to science communication endeavors.

Not so much about data, but about how we use evidence when we don't know the original source, and how e e.g. a politician failing to deny something might be good confirmation that it's actually true. 5 tips for reading stories with unnamed sources

Nice article, don't just show the data, tell us what it means "I use a Misfit activity tracker to count my steps. The Misfit app does a decent job of showing me step counts per day and every month, misfit also sends me a summary of the previous month's activity. Unfortunately, the numbers in that summary are presented without any context, making that summary almost entirely useless."

The conceptual, practical, and ethical issues surrounding "big data" and data in general begin at the very moment of data collection. Particularly when the data concern people, not enough attention is paid to the realities entangled within that significant moment and spreading out from it.1. Data sets are the results of their means of collection. It's easy to forget that the people collecting a data set, and how they choose to do it, directly determines the data set. An illustrative example can be found in the statistics for how many hate crimes were committed in the United States in 2012. According to the FBI Uniform Crime Reporting Program (UCR), the number was 5,796. However, the Department of Justice's Bureau of Statistics reported 293,800 hate crimes.

examples of data journalism in audio / podcast form - including: Right To Remain Silent is one particularly good example, because it's about bad data: specifically. police who manipulated official statistics. You might also listen to Choosing Wrong, which includes a section about polling. Another favourite of mine is an audio story by The Economist about the prostitution industry, based on data scraped from sex trade websites: More bang for your buck (there are even worse puns in the charts). David Rhodes, a BBC data journalist, has a range of stories on his Audioboom account, including pieces on Radio 4, Radio 5 Live, and a piece discussing "Did Greece really not pay 89.5% of their taxes in 2010" from the excellent factchecking radio programme, More or Less.

What is the basis for the argument that poor Americans will be healthier if they are required to pay substantially more for health care? It appears that proponents like Ms. Verma have looked at research and concluded that having Medicaid is often no better than being uninsured - and thus that any private insurance, even with enormous deductibles, must be better. But our examination of research in this field suggests this kind of thinking is based on a classic misunderstanding: confusing correlation for causation.

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.

Very cool visualisation, showing the power of thinking in manageable numbers. If Australia were just 100 people, what would it look like? New census data gives us an opportunity to find out, and provides some surprising insights into the state of the nation.