UTS-AEI

Any great story means visualization and detail. It takes the small additions of those details to build a picture in someone's mind to truly make the story complete. The same goes for analytics and data. Data is just a collection of numbers until you turn it into a story. Showing reports and dashboards can be overwhelming without adding a narrative to the data. Any great insight explains what happened, why it is important and how you can use it to turn it into something actionable. Data visualization is using data and statistics in creative ways to show patterns and draw conclusions about a hypothesis, or prove theories, that can help drive decisions in the organization.

Aleks Krotoski explores why science is being drowned out by Snake Oil online, and how the balance can be shifted to keep desperate people from being exploited. But despite there being more scientific information online than ever, in the modern day the power of the internet has completely flipped. Verified science and medicine are crowded out by a plethora of misinformation and snake oil salesmen. From the relatively harmless quackery such as infrared light treatments or 'wellness' focused diets, to conspiracy theories around vaccinations that are influencing political policy, and have resulted in outbreaks of dangerous, preventable diseases across the world - what is happening online is having a tangible impact across the globe. Aleks Krotoski explores how the infrastructure of the internet allows medical misinformation to thrive, finds out how people can be drawn into communities centred around medical misinformation and conspiracy theory, and how both scientists and every day internet users can redress the balance online.

"I am quite sure now that often, very often, in matters of religion and politics a man's reasoning powers are not above the monkey's," wrote Mark Twain. Having written a book about our most common reasoning errors, I would argue that Twain was being rather uncharitable - to monkeys. Whether we are discussing Trump, Brexit, or the Tory leadership, we have all come across people who appear to have next to no understanding of world events - but who talk with the utmost confidence and conviction. And the latest psychological research can now help us to understand why.

Last month, CNBC reported on a page in Google's account settings titled "Purchases" - a month-by-month list of items you've bought across online services like Amazon and other apps that are collected via Google services like Gmail. Purchases is a jarring example of how leaky our data really is and how large companies can aggregate that information unbeknown to the consumer. I, for one, was unaware that almost every concert ticket, Domino's pizza and Amazon purchase (including a 2014 accidental purchase of the film "Tango & Cash") was being logged by Google. Equally troubling: The purchases can't easily be deleted from the page without also deleting the receipt emails from your Gmail account.

Scientists have typically justified excluding female animals from experiments - even when studying conditions that are more likely to affect women - on the basis that fluctuating hormones would render the results uninterpretable. However, according to Rebecca Shansky, a neuroscientist at Northeastern University, in Boston, it is entirely unjustified by scientific evidence, which shows that, if anything, the hormones and behaviour of male rodents are less stable than those of females. Shansky is calling for stricter requirements to include animals of both sexes in research, saying the failure to do so has led to the development of drugs that work less well in women.

From climate change to armed conflict, our world is struggling with urgent global issues. But disagreements about how to solve them can spiral out of control. The only way to resolve intractable conflicts is to overcome desire to talk to allies more often than opponents. Here, a social psychologist, two ecologists and a cartoonist explain the toolbox of communication we need to resolve difficult issues.

Adrienne is a Marvel movie fanatic: Her favorite films all involve the Hulk, Thor or Black Panther. Brandon prefers animated features like Inside Out, The Incredibles and anything with Buzz Lightyear. I like both kinds, although I'm probably closer to Adrienne than Brandon. And I might skew a little toward Cora, who loves thrillers like Get Out and The Shining. Whose movie preferences are closest to yours: Adrienne's, Brandon's or Cora's? And how far are your cinematic tastes from those of the other two? It might seem strange to ask "how far" here. That's a question about distance, after all. What does distance mean when it comes to which movies you like? How would we measure it?

Journalists know they need to get better with data and statistics, but they have a long way to go Only 25 percent of journalists surveyed said they were "very" well equipped to interpret statistics from sources, and only 11 percent said the same about doing statistical analysis themselves.

When creating a machine-learning algorithm, designers have to make many choices: what data to train it on, what specific questions to ask, how to use predictions that the algorithm produces. These choices leave room for discrimination, particularly against people who have been discriminated against in the past. For example, training an algorithm to select potential medical students on a data set that reflects longtime biases against women and people of color may make these groups less likely to be admitted. In computing, the phrase "garbage in, garbage out" describes how poor-quality input leads to poor-quality output. In this case we might say, "White male doctors in, white male doctors out."

Most of the poor people in the world are women. In no country on earth are women economically equal to men, and Australia is no exception. Research from Acoss and the University of New South Wales last year showed that a higher share of people living in poverty in Australia are women. The experience of living below the breadline in our very wealthy nation is a gendered one, for reasons that are complex and intertwined. As women progress through life, they encounter a series of barriers and setbacks that simply do not encumber men in the same way. The cause of gendered poverty is structural. It is entrenched in our workplace settings, and embedded in our personal relationships. It is at play at every stage of a woman's life, from childhood to the grave, making its mark on our education, our employment, our homes, our familial responsibilities and our retirement options. At its heart is the simple fact that women do the lion's share of caring for others. Caring is women's work, and our society does not value women's work.

Nearly every ad you see online is tailored just for you. These digital ads are powered by vast, hidden datasets that allow advertisers to make eerily accurate guesses about who you are, where you've been, how you feel and what you might do next. While targeted ads may be familiar by now, how they work - and the power they have - often seems invisible. We decided to lift the veil on this part of the internet economy, so we bought some ad space. We picked 16 categories (like registered Democrats or people trying to lose weight) and targeted ads at people in them. But instead of trying to sell cars or prescription drugs, we used the ads to reveal the invisible information itself.

In our teens and early twenties, we're still figuring out what we want to be when we grow up. As we get older, we start to settle into a career. In between, we switch jobs in the search. Based on data from the Current Population Survey, this is when people make the switches and the jobs they switch to.The chart above shows the rate by age, relative to the total number of people who switched to each job. So you see a lot of switching in the early years, and then things seem to settle down at older ages. If someone takes a new job when they're older, it tends towards management or jobs that require more education.

Australian farms generate huge volumes of agricultural data. Examples include the types of crops being grown, crop yields, livestock numbers and locations, types of fertilisers and pesticides being used, soil types, rainfall and more. This data is typically collected through the use of digital farming machinery and buildings featuring robotics and digital technologies, artificial intelligence, and devices connected to the internet ("internet of things", or IoT). But a recent review from the Australian Bureau of Statistics and the Australian Bureau of Agricultural and Resource Economics highlights the patchy and fragmented nature of existing government and industry approaches to agricultural data. What that means is Australian farmers are currently not adequately protected from their farm data being collected and used without their knowledge or consent.

Interesting discussion of wealth vs income inequality, and our perceptions of wealth inequality and how to tackle it. The Essential Report survey highlights the lack of awareness most of us have about the level of wealth inequality that exists, and also our confusion over what policies are best suited to dealing with it.

Most people pass through some type of public space in their daily routine - sidewalks, roads, train stations. Thousands walk through Bryant Park every day. But we generally think that a detailed log of our location, and a list of the people we're with, is private. Facial recognition, applied to the web of cameras that already exists in most cities, is a threat to that privacy. To demonstrate how easy it is to track people without their knowledge, we collected public images of people who worked near Bryant Park (available on their employers' websites, for the most part) and ran one day of footage through Amazon's commercial facial recognition service.

Excellent NYT interactive - where do you draw the line on how your data is used by social media companies and smart devices?

At The Economist, we take data visualisation seriously. Every week we publish around 40 charts across print, the website and our apps. With every single one, we try our best to visualise the numbers accurately and in a way that best supports the story. But sometimes we get it wrong. We can do better in future if we learn from our mistakes - and other people may be able to learn from them, too. After a deep dive into our archive, I found several instructive examples. I grouped our crimes against data visualisation into three categories: charts that are (1) misleading, (2) confusing and (3) failing to make a point. For each, I suggest an improved version that requires a similar amount of space - an important consideration when drawing charts to be published in print.

In what feels like an increasingly polarised world, trying to convince the "other side" to see things differently often feels futile. Psychology has done a great job outlining some of the reasons why, including showing that, regardless of political leanings, most people are highly motivated to protect their existing views."Our results show why debates about controversial issues often seem so futile," the researchers said. "Our values can blind us to acknowledging the same logic in our opponent's arguments if the values underlying these arguments offend our own."

Read the comments alongside the article here - interesting speculation and use of evidence. initiatives will not turn the affordability problem around while tax settings continue to support existing homeowners and investors at the expense of first time buyers and renters. Moreover, apart from a brief interruption 2008-2012, the Commonwealth has been steadily winding back its explicit housing role for more than 20 years. The post of housing minister was deleted in 2013, and just last month Government senators dismissed calls for renewed Commonwealth housing policy leadership recommended by the Senate's extensive (2013-2015) Affordable Housing Inquiry. This complacency cannot go unchallenged.

The quest for balance in a health news story can fail before the first sentence if the headline isn't appropriately calibrated. With that in mind, I looked at news stories and releases that we reviewed over the past month and compared the headline message with that of the study on which the news is based. About a third of news story headlines and a quarter of news release headlines either misstated the results or went beyond what the research could support.