Data analytics reveal how we decide

Can you identify the critical difference between these two scenarios?  In one, a medication has a 1 percent rate of adverse side effects in those who use it. In the other, a medication causes adverse side effects for one person in one hundred.

If the situations sound identical, it’s likely that you’re good at math. For consumers who are not math-literate, however, the second scenario—the one that affects a person—implies a higher risk.

petersAccording to Ellen Peters, PhD, director of Ohio State’s Decision Sciences Collaborative, consumers in healthcare settings often struggle with numeracy. Peters uses data analytics to learn how to turn data into usable, meaningful information for decision-makers, especially in healthcare.

It’s almost transcendent—a study of data analytics to improve data analytics. “I do not use data analytics is a traditional sense,” she allows. “I use it to look at how humans process information, judge and decide.”

Frequently in healthcare situations, Peters says, the person who dispenses information has a high level of understanding when it comes to data, while the audience who is the decision maker does not. Her goal is to understand how to bridge the gap and help the information provider adjust to the needs of the audience.

krajbich.70c79e60TDA@OhioState member Ian Krajbich, PhD, a neuroeconomist in Ohio State’s Department of Psychology and Department of Economics, is another member of the Decision Science Collaborative who uses data analytics—in his case, to look beyond choice outcomes into the physiological underpinnings of human decisions.

Data, for example, can be analyzed to explore how people make low-stakes choices in snack foods. As an illustration, Krajbich offers an experiment where student participants are placed in front of computer screens equipped with cameras that measure eye movement and gaze time. The participants are shown two snack foods, such as an apple and an orange. By tracking and measuring a student’s gaze, researchers can predict which snack any particular student will choose.

“It’s more than identifying the options and making a choice, there’s looking back and forth,” Krajbich says. “The object that tends to be chosen is the one that is interesting; it’s the one that is seen and holds attention.” To that end, the images of the apple or orange can be manipulated to appear more interesting and demand more gaze time, thus increasing the probability of being chosen as snacks by participants.

Says Krajbich of data analytics: “It’s a window into decision making.”

Share this page
Suggested Articles
Parthasarathy team receives NSF funds to study social sensors in disaster responses

Changing the Disaster Narrative The story of disaster management is typically one of failure. When catastrophes such as floods or hurricanes strike, the aftereffects include structural failures, power failures, transportation...

Check out TDAI in Ohio State Alumni magazine

An article in the new Ohio State Alumni magazine showcases Translational Data Analytics Institute faculty and programs and the university’s responsive approach to educating students in data science and analytics. Check...

What wind, currents, and geography tell us about how people first settled Oceania

Just look at a map of Remote Oceania – the region of the Pacific that contains Hawaii, New Zealand, Samoa, French Polynesia and Micronesia – and it’s hard not to...

Data reveal possible smoking ban advantages

For policymakers wanting to discourage health-endangering smoking habits, TDA affiliate Mike Vuolo and two colleagues at Purdue have news: They found through analysis of nationwide data that smoking bans reduce...

Ohio State joins initiative to put farmers in control of data they collect

The Ohio State University has joined a coalition that will put important farm data into the hands of farmers while keeping it secure. The Agricultural Data Coalition (ADC) is dedicated...