Question

Keep your eyes and ears open as you read or listen to the news this week. Find/discover an example of statistics & probability in the news. Was it explained well, or poorly? What is the context? Do you think anything about the article is misleading? Can you make any inferences based on it? Do you think that the statistics in the article would convince the reader that we are all facing a serious problem with our environment? Explain why or why not by referencing examples from the article.

Answer 1

News:-

Coronavirus: our study suggests more people have had it than previously

Many people suspect they’ve been infected with COVID-19 by now, despite the fact that only 0.5% of the UK’s population has actually been diagnosed with it. Similar numbers have been reported in other countries. Exactly how many people have actually had it, however, is unclear. There is also uncertainty around what proportion of people who get COVID-19 die as a result, though many models assume it is around 1%.

This is the news about the pandemic corona virus. In the news there is given some data. The data shows that we are facing serious issues. The world is in danger. There is no misleading in the news. I believe that there has been over confidence in the reporting of infection prevalence and fatality rate statistics. When it comes to covid-19.Such stastics fails to take account of uncertainties in the data and explainations for these. We have to developed a computer model that look these uncertainties into account when estimating covid-19 fatality rates. And we can see a different picture.

This model allows us to combine multiple data sources and assess how sensitive the infection prevalce and fatality rates are to two dominating sources of uncertainty. One is the accuracy of serological (antibody) testing, which is cricially deoendent on our ability to accuratelymeasure whether an individual had antibodies. We account for factors such as false positives or negative rates for manufacturer test kits. We also take account of the reliability of fatality data. This is important because the fatality rate, the probability of death for covid19 infected patient, is defined as the death avount divided by the number of infected people in the community. If either of there variables is uncertain, any policy descions based on the resulting fatality rate will themselves be unreliable, or potentially dangerous.

In this way we can complete the news. And trying to said that the news need all the data properly.