Does data provide insights, or does it add to the confusion? As the whole world grapples with the concept of "fake news," it is time to also take a look at the way we and the rest of society look at our data. This is the same data that inspires a dating website survey to write a headline that says grilled cheese lovers have more sex and are better people than the rest of the population.
Much of data today is misinterpreted or misrepresented, and that's the topic of a book by statistician John H. Johnson, Everydata: The Misinformation Hidden in the Little Data You Consume Every Day. Johnson will join us as our guest on AllAnalytics radio on July 11, 2017 at 2 pm ET/11am PT. Join us and bring your questions. You can register here right now.
Johnson, who holds a Ph.D. in economics from MIT, used his book to look at some of the common ways data is misrepresented or misinterpreted today, and how we can lead the charge as experts in data and analysis to help business users and others in the enterprise correctly interpret data.
Why is data so often misinterpreted and misrepresented? Johnson's book lays out some of the common ways data can get mishandled or misinterpreted to yield misleading results. He looks at averages and aggregates, how sampling can affect results, correlation versus causation, outliers, and the struggle to create predictions.
Have you ever run into these kinds of problems in your organization? Do you ever struggle to help business users understand these concepts? Join us as Johnson takes us through the struggle and offers advice.
[This post has been updated to reflect a change in date of the event.]