Editor's note: This blog post is part of a series of posts, originally published here by our partner News Literacy Project, exploring the role of data in understanding our world. As discussed in previous posts, statistics and visual representations of data can be misleading. But what happens when the data itself is misleading? And if data is
Editor's note: This blog post is part of a series of posts, originally published here by our partner News Literacy Project, exploring the role of data in understanding our world. “Numbers don’t lie” is a phrase we often hear to support the idea that something must be true if you can cite data or
Editor's note: This blog post is the first in a series of posts, originally published here by our partner News Literacy Project, exploring the role of data in understanding our world. Charts and graphs are useful tools for communicating complex information. They allow consumers to see — rather than read or calculate — differences
SAS has always believed in the power of education, but in today’s data-driven economy, it’s more important than ever to ensure our students are introduced to data science at an early age. We as a company are focusing our resources on creating student experiences in data literacy, computer science and
Being overwhelmed by the volume of news isn’t a new phenomenon. But today, our sense of being overwhelmed has increased and triggered feelings of fear, frustration and anxiety, given the ongoing developments and research tied to COVID-19. How do we sift through the volume of information facing us and truly understand whether the news we consume is factual or based on
Testing people for coronavirus is a public health measure that reduces the spread of coronavirus. Dr. Anthony Fauci, a US infectious disease expert, recently mentioned the concept of "pool testing." The verb "to pool" means "to combine from different sources." In a USA Today article, Dr. Deborah Birx, the coordinator
During this coronavirus pandemic, there are many COVID-related graphs and curves in the news and on social media. The public, politicians, and pundits scrutinize each day's graphs to determine which communities are winning the fight against coronavirus. Interspersed among these many graphs is the oft-repeated mantra, "Flatten the curve!" As
この記事はSAS Institute Japanが翻訳および編集したもので、もともとはRick Wicklinによって執筆されました。元記事はこちらです（英語）。 2020年における新型コロナウイルスの世界的流行のようなエピデミック状況下では、各国の感染確認者の累計数を示すグラフがメディアによって頻繁に示されます。多くの場合、これらのグラフは縦軸に対数スケール（対数目盛）を使います。このタイプのグラフにおける直線は、新たなケースが指数関数的ペースで急増していることを示します。直線の勾配はケースがどれほど急速に倍加するかの程度を示し、急勾配の直線ほど倍加時間が短いことを示します。ここでの「倍加時間」とは、「関連状況が何も変わらないと仮定した場合に、累計の感染確認者数が倍増するまでに要する時間の長さ」のことです。 本稿では、直近のデータを用いて倍加時間を推計する一つの方法を紹介します。この手法は、線形回帰を用いて曲線の勾配（m）を推計し、その後、倍加時間を log(2) / m として推計します。 本稿で使用しているデータは、2020年3月3日～3月27日の間の、4つの国（イタリア、米国、カナダ、韓国）における新型コロナウイルス感染症（以下、COVID-19）の感染確認者の累計数です。読者の皆さんは、本稿で使用しているデータとSASプログラムをダウンロードすることができます。 累計感染者数の対数スケール・ビジュアライゼーション このデータセットには4つの変数が含まれています。 変数Region： 国を示します。 変数Day： 2020年3月3日からの経過日数を示します。 変数Cumul： COVID-19の感染確認者の累計数を示します。 変数Log10Cumul： 感染確認累計数の「10を底とする対数」（＝常用対数）を示します。SASでは、LOG10関数を用いて常用対数を計算することができます。 これらのデータをビジュアル化する目的には、PROC SGPLOTを使用できます。下図のグラフは感染確認者の総数をプロットしていますが、総数の縦軸に常用対数を指定するために「type=LOG」と「logbase=10」というオプションを使用しています。 title "Cumulative Counts (log scale)"; proc sgplot data=Virus; where Cumul > 0; series x=Day y=Cumul / group=Region curvelabel; xaxis grid; yaxis type=LOG logbase=10 grid values=(100 500 1000
During an epidemic, such as the coronavirus pandemic of 2020, the media often shows graphs of the cumulative numbers of confirmed cases for different countries. Often these graphs use a logarithmic scale for the vertical axis. In these graphs, a straight line indicates that new cases are increasing at an
During an outbreak of a disease, such as the coronavirus (COVID-19) pandemic, the media shows daily graphs that convey the spread of the disease. The following two graphs appear frequently: New cases for each day (or week). This information is usually shown as a histogram or needle plot. The graph
From sports and health data to environmental and policy data, our data visualization experts have used SAS technologies to explore and present analyses on hundreds of topics throughout the year. We've selected some of the best in this end-of-year roundup to showcase their skills and SAS technologies, and to demonstrate
Put simply, data literacy is the ability to derive meaning from data. That seems like a straightforward proposition, but, in truth, finding relationships in data can be fraught with complexities, including: Understanding where the data came from, including the lineage or source of that data. Ensuring that the data meet compliance
This summer the Accessibility and Applied Assistive Technology team at SAS launched a new course that teaches students with visual impairments how to independently analyze data, which is a critical skill that all students need for success in college and their careers. However, many students with visual impairments don’t have
News outlets share stats and graphs that they source from public data. It takes data literacy skills to critique the stats you see, and investigate more.
