UTS-AEI

The more serious problem with California's law is one of effect size. Health, and cancer, aren't binary. Consumers can't just be concerned with whether a danger exists; they also need to be concerned about the magnitude of that risk. Even if there's a statistically significant risk between huge quantities of coffee and some cancer (and that's not proven), it's very, very small. Cigarettes have a clear and easily measured negative impact on people's health. Acrylamide, especially the acrylamide in coffee, isn't even close. Warning labels should be applied when a danger is clear, a danger is large and a danger is avoidable. It's not clear that, with respect to acrylamide, any of these criteria are met. It's certainly not the case regarding coffee. Whatever the intentions of Proposition 65, this latest development could do more harm than good.

Medicine's decades-long march toward patient autonomy means patients are often now asked to make the hard decisions - to weigh trade-offs, to grapple with how their values suggest one path over another. This is particularly true when medical science doesn't offer a clear answer: Doctors encourage patients to decide where evidence is weak, while making strong recommendations when evidence is robust. But should we be doing the opposite?People in general are not great at evaluating risk. They worry more about shark attacks than car crashes.

The Guardian datablog has a set of visualisations https://www.theguardian.com/technology/data-visualisation and a set of stories focused on the Australian context; useful for exploring how data analysis and visusalisation are used to tell a story.

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"

Some fantastic visualisations in this piece from the Guardian, including a scatterplot and some different kinds of histograms! Well worth exploring. "The figures reveal men are paid more than women in 7,795 out of 10,016 companies and public bodies in Britain, based on the median hourly pay. Across the companies and organisations that had filed by 8am on Thursday, eight out of 10 had a gender pay gap. While the figures do not reflect equal pay for equal work, they do raise questions about structural inequalities in the workforce and may hold the answer to closing the gap."

For AT2 we're asking you to analyse one of the datasets https://tinyurl.com/AEIDatasets . This piece provides some nice examples of how people are using data to do deep exploration of a topic (bike sharing) and its impact for particular stakeholders. If you were doing something on road safety/bikes, then these kinds of resources are good examples of other research you could draw on to support your own analysis of the data and to tell your data story.

The census has been used for hundreds of years to determine how many U.S. House members each state will have, and it currently helps determine how hundreds of billions of dollars in federal spending is divvied up. "The risk that really troubles me is that there's a big undercount and then there's a big lack of representation," said John Thompson, who was director of the U.S. Census Bureau until he resigned last year (the bureau is still without a director).

When it comes to inequality, a growing body of evidence shows that people across countries underestimate the size of the gap between the rich and poor, including their wages. This can undermine support for policies to tackle inequality and even lead to apathy that consolidates the gap. But how exactly are existing perceptions of inequality measured by social scientists?

Public sector employers with more than 250 staff are legally obliged to publish their gender pay gap by Friday, while private firms and charities have until Wednesday 4 April. About 7,000 of a estimated total of 9,000 organisations had filed results by Thursday.companies have filed mathematically impossible figures - at least 17 have reported a bonus gap of more than 100%. One company reported an hourly mean gender pay gap of 106.4%, implying that for every £100 earned by a man a woman would "pay" £6.40. A spokesperson at the company declined to comment.

For the 11 million Australians with private hospital cover, premium rises are nothing new. The 3.95% average increase on April 1, 2018 will be the seventeenth consecutive year in which insurance premiums have been hiked up. Health insurance premiums have increased by an average of 5.35% per year since 2000, which is significantly more than wage growth, meaning that households are spending a larger share of their income on health care.

Interesting links to different sources discussing data on teacher pay, and what it shows in relation to different things that stakeholders might care about. educator pay varies significantly across states, from an average of $44,921 in Oklahoma to $77,957 in New York. Why should school administrators and government leaders care about teacher pay - beyond wanting their employees to be able to afford their living expenses? Below, we present research that examines this issue. What scholars have found is that teacher salaries are linked to employee retention and that better pay seems to draw smarter people to the field and into the classroom. It's not clear, however, whether higher salaries result in higher student achievement.

It's not just disadvantaged and vulnerable groups that struggle with financial decision-making. People who are highly educated in finance also make poor decisions - for instance, by focusing too much on growing their assets and ignoring risks. But studies show that when regulation is effective and the financial system can be trusted, even consumers with limited financial knowledge and information-processing capabilities have the potential to deal with complex financial decisions. For example, when considering mortgage protection insurance, applicants stand to benefit from knowing the actual risk of events like serious illness or injury that can affect their ability to meet monthly loan repayments.

Since the census is the ultimate measure of population in the U.S., one might wonder how we could even know if its count was off. In other words, who recounts the count? Well, the Census Bureau itself, but using a different data source. After each modern census, the bureau carries out research to gauge the accuracy of the most recent count and to improve the survey for the next time around. The best method for determining the scope of the undercount is refreshingly simple: The bureau compares the total number of recorded births and deaths for people of each birth year, then adds in an estimate of net international migration and … that's it. With that number, the bureau can vet the census - which missed 4.6 percent of kids under 5 in 2010, according to this check.

There is a black hole in our knowledge of women and girls around the world. They are often missing from official statistics, and areas of their lives are ignored completely. So campaigners say - but what needs to be done?

"Between 2000 and 2015, nearly every African country improved childhood nutrition, especially in reducing stunted growth caused by malnutrition" .... " national averages do not tell the full story. In Kenya, for example, rates of wasting in children under 5 were below 6% on average nationwide in 2015, yet in certain regions plagued by several years of poor rains, crop failure and disease outbreaks, estimated levels of wasting reach as high as 28%."... "Such fine-grained insight brings tremendous responsibility to act. It shows governments, international agencies and donors exactly where to direct resources and support."..."This shows how crucial it is to invest in data. Data gaps undermine our ability to target resources, develop policies and track accountability. Without good data, we're flying blind. If you can't see it, you can't solve it."

Use of mean and median to analyse the paygap at The Guardian group. The gender pay gap at Guardian News & Media is 11.3% - calculated by mean hourly pay - the company has reported as part of the government's compulsory gender pay gap initiative.Across GNM, the median pay difference, which takes the mid-point when all wage rates are lined up from the biggest to smallest - which reduces the impact of one-off outliers - is wider, at 12.1%. The figure for non-editorial is 18.2%, and nearly 9% in editorial.

When Ice Cream Sales Rise, So Do Homicides. Coincidence, or Will Your Next Cone Murder You?

Short (10 minute) podcast "How to question dubious statistics in just a few short steps."....it's got some very British humour (sorry), but pretty good!

Advancement toward gender equality at work has slowed since the 1990s for three major reasons: people's attitudes stopped becoming more gender egalitarian, occupations stopped gender integrating, and the gender wage gap began decreasing at slower rates. Sociologist Paula England has called this phenomenon an "uneven and stalled" gender revolution, and there have been dozens of studies showing how the progress in gender equality experienced during and immediately after the feminist movement of the 1970s has not been sustained through the 1990s and 2000s. Does this stalled revolution play out in management positions, too? And if so, how? To explore this, I used data on full-time managers obtained from the U.S. Census and American Community Survey for the years 1980 and 2010 to examine three major factors that contribute to gender equality in the labor force: women's representation in management, the occupational gender segregation among managers, and the gender wage gaps that vary across managerial occupations.

A great data-story on the gender imbalance worldwide, using data and research to investigate and highlight key issues. This piece in the economist takes a different approach to using the data https://www.economist.com/node/15636231 "In 1960, the earliest year the World Bank provides data for, the world was within 0.002 percentage points of a perfectly equal distribution. Ever since, the gap has widened; now men outnumber women on the planet by more than 66 million. When this piece was first published in early 2014, the gap had already been the widest ever - the trend continues."