Linda J. Young is Chief Mathematical Statistician and Director of Research and Development of USDA's National Agricultural Statistics Service . She oversees efforts to continually improve the methodology underpinning the Agency's collection and dissemination of data on every facet of U.S. agriculture. She works on the surveys designed to characterize agricultural activity in the US.
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Linda J. Young is Chief Mathematical Statistician and Director of Research and Development of USDA's National Agricultural Statistics Service . She oversees efforts to continually improve the methodology underpinning the Agency's collection and dissemination of data on every facet of U.S. agriculture. She works on the surveys designed to characterize agricultural activity in the US.
Data visualizations are everywhere, showing up in social media, in the news, and on company websites. With this onslaught, it can be hard to know what visualizations to trust. Learning how to navigate bad graphs and charts is a focus of this episode of Stats and Stories with guest Nathan Yau.
Yau is the author of several books on data visualization, including Visualize This and a number of other works. He also runs the Flowing Data blog, where he works to make the process of creating data visualizations accessible to a wide audience. He recently published a defense against dishonest charts on his blog, which serves as a guide to determining which visualizations to trust.
Flowing Data's Origin and Development 2:32
Surprising Insights and Misleading Charts 7:55
Anatomy of a Chart and Common Misleading Techniques 12:25
Strategies for Reading Data and Interactive Charts 16:31
Feedback and Tools for Visualization 23:26
Stats + Stories
Linda J. Young is Chief Mathematical Statistician and Director of Research and Development of USDA's National Agricultural Statistics Service . She oversees efforts to continually improve the methodology underpinning the Agency's collection and dissemination of data on every facet of U.S. agriculture. She works on the surveys designed to characterize agricultural activity in the US.
