This is a good article about how municipalities are using well-being indexes to measure intangibles such as levels of happiness among citizens. That alone makes this article useful to markets (to compare to their shoppers happiness levels or to find metrics that markets could also use perhaps?) but also interesting is that the article details how responses were collected. Ensuring that the proper methodology and sample size is crucial to anyone collecting qualitative data.
Food system organizers in these cities could learn from the conclusions and even work with these municipal leaders to also survey farmers market shoppers, possibly adding a question or two about their use of local foods and markets. Additionally, knowing about these data collection projects could also allow markets to easily locate experienced survey teams and tested methodology for their own survey work.
“Despite this caveat, Hadley stresses that the undertaking is eminently worthwhile, given the relative ease of conducting the surveys. “It’s not as hard as it seems to do a good, simple survey of your residents,” he says. “We did it all in-house and we did it all for under $4,000. It’s totally doable.” And the more cities that begin to do the surveys, the better, because they can compare results and learn from each other. For example, Somerville’s average rate of satisfaction was 7.5, but this number is hard to interpret without the context of responses from other cities.”
Farmers Market Metrics
Survey Monkey sez start with your conclusion
Writing your conclusion first is just like proposing a hypothesis for a science experiment.
DATA + DESIGN A simple introduction to preparing and visualizing information
A free online book to data visualization by the creators of Infoactive. I am proud to be a Kickstarter backer of this innovative company and hope we can lure them into the farmers market/food system world of data collection. This book came out of that campaign and-well, maybe just read what the author said about how the book came to be:
“It started with a message on Kickstarter:
Hi Trina! Stats dork from Chicago here….Do you have any plans to include tutorials for basic data cleaning and data selection techniques for users who may not have any statistics background?
At the time, I didn’t know that this one message would turn into a book, a community, and a global endeavor to make information design more accessible.
The message author, Dyanna Gregory, was a statistical programmer who knew the challenges of teaching university-level stats to those who don’t identify as math nerds. I was an entrepreneur building Infoactive, a web application to help people create interactive infographics and data visualizations. I was also a Reynolds Fellow at the Donald W. Reynolds Journalism Institute where my goal was to find ways to simplify the process of making data visualizations in newsrooms. I had launched a Kickstarter campaign to support Infoactive, and we had nearly 1,500 backers who were excited about breaking down barriers in data visualization.
We all believed in the vision of making data simple.
But working with data can be far from simple. Data come in all different shapes, sizes, and flavors. There’s no one-size-fits-all solution to collecting, understanding, and visualizing information. Some people spend years studying the topic through statistics, mathematics, design, and computer science. And many people want a bit of extra help getting started.”