The COVID-19 pandemic has highlighted how much modern societies are governed by statistics. Despite their objective appearance, these numbers gain their strength from very human relationships.
African governments must engage rating agencies better, providing them and investors with credible economic data, and regularly address all concerns being raised.
Health statisticians keep careful tabs on how many people die every week. Based on what’s happened in past years, they know what to expect – but 2020 death counts are surging beyond predictions.
The pandemic has exposed many of us to new statistical concepts, on the news, in everyday conversations and on social media. But how many are you getting wrong?
Health statisticians keep careful tabs on how many people die every week. Based on what’s happened in past years, they know what to expect – but 2020 death counts are surging beyond predictions.
A team of researchers from Indiana University performed random testing for SARS-CoV-2 across the state. The results offer some of the most accurate data to date about important aspects of the virus.
Many of the more formal models for predicting the pandemic try to understand why changes happen – but often it can be more accurate to ignore the reasons and simply look at the data.
Why one city suffers significantly more deaths than another isn’t always obvious. A simple experiment shows how failing to consider certain factors can point policy makers in the wrong direction.
On the 200th anniversary of Florence Nightingale’s birth, we take a look at how her monumental efforts helped shape the way we model health care and disease outbreak data today.
Countries aiming to flatten the coronavirus curve have one crucial aim: reduce the “effective reproduction number” of the virus to below 1. This means the spread is slowing, rather than accelerating.
Tim Hortons changed Roll up the Rim to include a digital element. A statistician correctly predicted that playing on the last day of the contest would dramatically increase the odds of winning.
Researchers and public health officials still don’t know how widespread nor how deadly the coronavirus really is. Random testing is a way to quickly and easily learn this important information.
Professor, Future Fellow and Head of Statistics at UNSW, and a Deputy Director of the Australian Centre of Excellence in Mathematical and Statistical Frontiers (ACEMS), UNSW Sydney