If you're a journalist, you don't need to have a phobia about math; here are resources to help you

Help is available for math-phobic journalists who need to tackle math to write stories. "Whether it’s reading a government-produced spreadsheet, calculating percentage changes or judging the results of complex academic studies, journalists often must confront the world of math, like it or not," John Wihbey reports for Journalist's Resource, a service of Harvard University's Shorenstein Center on Media, Politics and Public Policy. Wihbey offers these resources:

• Try the classic “Mathematics Competency Test for Journalists,” developed by Philip Meyer of the University of North Carolina, author of The New Precision Journalism, Educators can find a version of the test without answers here.
• Key areas in business and politics often present challenges for general assignment reporters in terms of knowing what’s relevant and detecting underlying data problems. For examples, see “Reading Economic Data Releases from the Government,” by Chris Roush at UNC. Likewise, because knowledge of polling, survey methods and error margins is crucial, see “Polling Fundamentals and Concepts: An Overview for Journalists.”
• For a more advanced understanding of terminology at higher levels of analysis, review “Statistical Terms Used in Research studies: A Primer for Media.”
• The Centre for Investigative Journalism has produced a helpful report, “Statistics for Journalists,” which examines issues such as how averages can mislead and “regression to the mean.” Authored by Connie St. Louis, City University, London.
• Robert Niles also provides a very helpful general resource with “Statistics Every Writer Should Know.”
• To get in the mode of thinking more empirically, check out this fun take on “What Headlines Would Look Like If We Lived in a Mathematically Literate World.”
• Then see “Math Basics for Journalists: Working with Averages and Percentages,” from Journalist’s Resource. It’s a quick refresher.
• Interpreting and writing about academic studies can be tricky. For useful insights, see “Interpreting Academic Studies: A Primer for Media,” also from Journalist’s Resource.
• To get a taste of how quantitative researchers use data, check out “Regression Analysis: A Quick Primer for Media on a Fundamental Form of Data Crunching.” It takes you through a basic technique researchers use to look at the relationship between variables.
• It’s worth remembering that even some of the best data-driven journalism practitioners sometimes fall short of achieving true scientific rigor. The University of Miami’s Alberto Cairo writes at Nieman Lab about how data journalism still needs to “up its own standards.”
• Finally, some problems go well beyond simple numerical errors and ultimately come down to flaws in logic, inference and causality. For a rigorous overview of how to build an explanatory theory, see “Guide to Critical Thinking, Research, Data and Theory: Overview for Journalists.”