#1 Analyzation of two visual stories
COURSE: Visual Journalism
This data comes from a large number of interviews conducted online by the global data and survey firm Dynata at the request of The New York Times. The firm asked a question about mask use to obtain 250,000 survey responses between July 2 and July 14, enough data to provide estimates more detailed than the state level. (Several states have imposed new mask requirements since the completion of these interviews.)
Specifically, each participant was asked: How often do you wear a mask in public when you expect to be within six feet of another person?
This survey was conducted a single time, and at this point we have no plans to update the data or conduct the survey again.
To transform raw survey responses into county-level estimates, the survey data was weighted by age and gender, and survey respondents’ locations were approximated from their ZIP codes. Then estimates of mask-wearing were made for each census tract by taking a weighted average of the 200 nearest responses, with closer responses getting more weight in the average. These tract-level estimates were then rolled up to the county level according to each tract’s total population.
By rolling the estimates up to counties, it reduces a lot of the random noise that is seen at the tract level. In addition, the shapes in the map are constructed from census tracts that have been merged together — this helps in displaying a detailed map, but is less useful than county-level in analyzing the data.
Analyzing who is wearing masks in USA and what might affect them wearing or not.
Mask use is high/Mask use is often partisan/Mask use is related to Covid risk.