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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.

Going beyond a surface level analysis of the statistics to delve deeper into the story A similar contrast can be seen in the census data on the religiosity of Australians. The census asks participants to state their religion. The answers reveal that while on the one hand Australians are becoming less religious, on the other they are becoming more religiously diverse. In the 2011 census, 68.3% of people identified themselves as having a religion. This was down from 69.5% in 2006. However, the census does not tell the whole story. It cannot tell us how often a person attends a church, mosque, synagogue or temple. It cannot tell us how often a person prays or performs some other religious ritual.

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).

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.

Journalists often make mistakes when reporting on data such as opinion poll results, federal jobs reports and census surveys because they don't quite understand - or they ignore - the data's margin of error. Data collected from a sample of the population will never perfectly represent the population as a whole. The margin of error, which depends primarily on sample size, is a measure of how precise the estimate is. The margin of error for an opinion poll indicates how close the match is likely to be between the responses of the people in the poll and those of the population as a whole. To help journalists understand margin of error and how to correctly interpret data from polls and surveys, we've put together a list of seven tips, Look for the margin of error - and report it. It tells you and your audience how much the results can vary. Remember that the larger the margin of error, the greater the likelihood the survey estimate will be inaccurate. Make sure a political candidate really has the lead before you report it. Note that there are real trends, and then there are mistaken claims of a trend. Watch your adjectives. (And it might be best to avoid them altogether.) Keep in mind that the margin of error for subgroups of a sample will always be larger than the margin of error for the sample. Use caution when comparing results from different polls and surveys, especially those conducted by different organizations.

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.

Data analysis is playing an increasing role in the U.S. electoral system, raising an important question as the Trump administration prepares to oversee the 2020 Census: What if the data aren't reliable?