Difference between revisions of "Covid-19 Research"
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*'''<u>Approach articles with skepticism</u>''': Be critical of the evidence provided in the article and try not to draw your own conclusions or accept the conclusions presented until you have read many articles on the subject. | *'''<u>Approach articles with skepticism</u>''': Be critical of the evidence provided in the article and try not to draw your own conclusions or accept the conclusions presented until you have read many articles on the subject. | ||
*'''<u>Be careful when drawing conclusions from statistics</u>''': Ronald Coase has been credited with saying: "If you torture the data enough, nature will always confess." What this means is that you should avoid reading too much into Covid-19 statistics (or ''any'' statistics for that matter) and avoid making far-fetched implications. Statistics is a great tool for extracting meaningful information and finding patterns in a large body of data. However, statistics are only as meaningful as the accuracy and complexity of the model. And remember, ''correlation does not imply causation''. | *'''<u>Be careful when drawing conclusions from statistics</u>''': Ronald Coase has been credited with saying: "If you torture the data enough, nature will always confess." What this means is that you should avoid reading too much into Covid-19 statistics (or ''any'' statistics for that matter) and avoid making far-fetched implications. Statistics is a great tool for extracting meaningful information and finding patterns in a large body of data. However, statistics are only as meaningful as the accuracy and complexity of the model. And remember, ''correlation does not imply causation''. | ||
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Revision as of 20:26, 26 April 2020
Introduction and Guidelines
The purpose of this page is to provide the latest facts on Covid-19 using research directly from scientific articles. With many secondary sources being inaccurate (or misleading at best), it is more important than ever to relay scientific research as unbiased as possible and to be as thorough as possible. Of course, in practice, it is impossible to be completely unbiased in conveying information, so my best advice in using this page is to use the guidelines below:
- Don't judge an article by its title (or its abstract!): Although you should search for scientific articles by category, title, and abstract, you should not simply read the title or an abstract of an article expect to know everything about it. You should read it in its entirety so that you get the complete picture and intended message.
- Approach articles with skepticism: Be critical of the evidence provided in the article and try not to draw your own conclusions or accept the conclusions presented until you have read many articles on the subject.
- Be careful when drawing conclusions from statistics: Ronald Coase has been credited with saying: "If you torture the data enough, nature will always confess." What this means is that you should avoid reading too much into Covid-19 statistics (or any statistics for that matter) and avoid making far-fetched implications. Statistics is a great tool for extracting meaningful information and finding patterns in a large body of data. However, statistics are only as meaningful as the accuracy and complexity of the model. And remember, correlation does not imply causation.