UTS-AEI

When it comes to Sydney's perennial east vs west rivalry, there are plenty of opinions and stereotypes about the spray-tanned, salmon-wearing 'silver tails' and ugg boot-bound bogan 'westies'. And then there are facts. Here, we've used data to explore the actual differences between life in a selection of Sydney's eastern and western suburbs. Some of it's serious, some of it's fun. Nothing here is meant to be perjorative. Because there's no 'superior' Sydney - just different ones.

The reasons for the disparity in pay vary from company to company but the broader source of the gap can be seen in the distribution of high earners by gender. Of all the companies that have reported to date the top pay quartile, the highest paid 25% of employees, is male-dominated. Almost two-thirds of the top quartile is made up of men, while conversely 57% of the lowest-paid employees are women.

Is income inequality growing (in America)? This article discusses the issue, and uses a chart from the Financial Times (and Pew research data) to demonstrate the change since 1971. Great visualisation and great discussion of what it shows.

An introduction to a set of deep dive articles an important issue....When we tell people that we work at the intersection of statistics and human rights, the reaction is often surprise. Everyone knows that lawyers and journalists think about human rights problems … but statisticians? Yet, documenting and proving human rights abuses frequently involves the need for quantification. In the case of war crimes and genocide, guilt or innocence can hinge on questions of whether violence was systematic and widespread or one group was targeted at a differential rate compared to others. Similar issues can arise in assessing violations of civil, social, and economic rights. Sometimes the questions can be answered through simple tabulations, but often, more-complex methods of data collection and analysis are required.

If you look at marathon times, you see most people run somewhere in the middle (4 hoursish), with a few under 3 hours (?!) and over 6 hours (very sensible). If you plot this data in a histogram, you can also see that there are spikes...people run just under 3, 3.5, 4, and 4.5 hours - you can see that people have a goal (of a nice round number) and the times are distributed accordingly.

Every year in Australia, the National Assessment Program - Literacy and Numeracy (NAPLAN) results show Indigenous school students are well behind their non-Indigenous peers. Reducing this disparity is a vital part of Australia's national Closing the Gap policy. ... Using an updated version of our equivalent year levels metric, introduced in Grattan Institute's 2016 report Widening Gaps, we estimate year nine Indigenous students in very remote areas are: five years behind in numeracy six years behind in reading, and seven to eight years behind in writing. In other words, the average year nine Indigenous student in a very remote area scores about the same in NAPLAN reading as the average year three non-Indigenous city student, and significantly lower in writing. But it would be a big mistake to see this only as a problem for isolated outback communities. Most Indigenous students live in cities or regional areas. So, even though learning outcomes are worse in remote and very remote areas, city and regional students account for more than two-thirds of the lost years of learning.

What is the best way of reporting on data related to the environment? Where do you find the data in the first place? How do you make it relatable to the public and which challenges do you face along the way? Last October, seven experts got together on the Data Journalism Awards Slack team on to tackle these questions.

There is a lot of discussion recently about proposed changes to NSW Selective High Schools. This contentious issue may be something to consider for AT4. For example, see the articles in the Sydney Morning Herald such as this one:

On the importance of having data, in order to understand and tackle an issue... The most recent U.S. estimate...concluded approximately 513,000 women and girls at risk of genital mutilation...But that number should be taken with a big grain of salt...the data doesn't account for immigrants from countries where female genital cutting isn't studied or widely practiced...."You also can't assume that people who come to the U.S. are a representative sample of their country of origin," Clark said. That's especially problematic for estimating rates of female genital cutting, since it's not practiced uniformly within countries. It's also possible, he said, that some immigrants abandon the procedure as they assimilate....some advocates point out that although the estimates focus on immigrants, ...female genital cutting isn't new to the U.S. Female circumcision was performed as a treatment for masturbation by American physicians as recently as the mid-20th century...

or those of us who can't stand the thought of creepy crawlies or who jump at the sight of a shadow in the ocean, summer in Australia can be a challenging time. Deadly snakes, sharks and spiders - you name it, we've got it. But just how deadly are these creatures and how disproportionate is our fear of them? To find out we compiled a list of deaths commonly associated with summer.

A complex look at an important issue and what data can tell us about it, and how missing data complicates the picture.

An opinion piece in last week's Annals of Internal Medicine argues that just how aggressively we screen for some cancers can actually distort our understanding of the risk factors for a particular cancer, as well as how common we perceive it to be.

Excellent analysis from the FT (you'll need to login to view via the link) that uses knowledge of the Mean and Median to show that some companies have reported incorrect (fabricated?) pay-gap information! One in 20 UK companies that have submitted gender pay gap data to the government have reported numbers that are statistically improbable and therefore almost certainly inaccurate, a Financial Times analysis has found. Sixteen companies, each with more than 250 employees, reported that they paid their male and female staff exactly the same, that is they had a zero average gender pay gap measured by both the mean and median. Experts on pay said that it was highly anomalous for companies of that size to have median and mean pay gaps that were identical because the two statistics measure different things. The mean gap measures the difference between the average male and female salary while the median gap is calculated using the midpoint salary for each gender.

When we launched Beyond the blade earlier this year, we wanted to know how many young people and children were being killed by knives in the UK. Who are these young people being killed?, Where are they dying? Is the scale of the issue changing, and if so how? We spoke to experts about the number of children and teenagers affected in Britain and Northern Ireland. We checked with the Office for National Statistics, the Home Office, politicians, academics and thinktanks. But the answer to how many young people are dying every year, it seemed, was that nobody knows. So we started trying to find out. Until now, there has been no publicly available information about the demographic profiles of those who have died from knife attacks in the UK

An excellent visual data story describing the gender pay gap (in America) and debunking the claim that there is no real difference in the amount men and women get paid. The pay gap varies depending on the occupation, working hours, education attainment, experience, and geography. That explains part of the difference in pay between men and women, but not all of it. And even though most economists agree that after adjusting for age, education, experience and other variables there's still an unexplained gap, there are voices who argue that the gender pay gap is a myth. Pay gap deniers purport that women's choices, rather than discrimination, cause the pay gap between women and men. But those choices are actually consequences of the social forces at play.

How excited would you be about a medication that lowered your risk of cardiovascular death, heart attack or stroke by 1.5%? Excited enough to spend a few thousand dollars a year on the drug? I expect not. What if, instead, the drug reduced those same terrible outcomes by 20%? That's probably enough benefit to interest some in the drug. Well, those statistics come from the same clinical trial, evaluating the same drug. In fact, they present the exact same results, but they simply do it in different ways.

some examples of how the 3 types of machine learning - supervised, unsupervised, and reinforcement - have already been used for journalistic purposes, and using those to explain what those are along the way. Examples include: supervised learning to investigate doctors and sex abuse; unsurprivsed learning to identify motifs in Wes Anderson films; reinforcement learning to create a rock-paper-scissors that can beat you...

A list of "happy data stories" or stories related to the arts...including: Pup Inflation: Good Dogs Getting Better. "Oh, but for a much purer example of silly data journalism that I remembered as soon as I hit send, earlier this year I scraped and analyzed the dog ratings from the Twitter account WeRateDogs." -David Henry Montgomery Sneakin' Toward the Weekend, Workers Fill Roadways "How about using hourly traffic counting stations to show how people are cheating out of the office earlier and earlier on Fridays? Mental note: we're four years away from that link being older than my incoming freshmen. Also, note the wonder at phones able to receive email being someday widely available in the story." -Matt Waite

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.).

It is vital that public policy be driven by rigorous research. In the last decade key policy changes have had profound impacts on nightlife in Sydney's inner city and suburbs. The most significant and controversial of these has been the 2014 "lockout laws".