Through Stanford massive online course, students across the world learn how to interpret data
Statistics in Medicine is a free 9-week course offered to students around the world through the university's open-source platform, OpenEdX. About 16,000 students are taking the course, two-thirds of them auditing and one-third completing the homework assignments and quizzes.
Early mornings, while her family sleeps, Tracy Womack logs on to her computer and watches Kristin Sainani, a clinical assistant professor at Stanford School of Medicine, explain the finer points of statistical methodology.
The middle school math teacher in Santa Barbara, Calif., is taking Statistics in Medicine, a free massive open online course, or MOOC, "because I want to be a learner," she wrote in an email. "I like math, so this is fun for me."
Across the Pacific Ocean, in Tokyo, Takayuki Oguri is expecting the MOOC to improve the quality of his work as a clinical research associate, which requires him to "design, monitor, record and report clinical study," and statistics directly influences the quality of his reports, he wrote. "That's why I take this course."
Stanford is offering Sainani's 9-week course to students around the world through the university's open-source platform, OpenEdX.
About 16,000 students are taking the course, two-thirds of them auditing and one-third completing the homework assignments and quizzes. Those who score 60 percent or higher on the homework, quizzes and a final will receive a Statement of Accomplishment – with distinction if they earn 90 percent or higher.
Sainani, who has a doctorate from Stanford in epidemiology, teaches ways to graph and visualize data, calculate probability and risk, and evaluate a margin of error.
She uses real-life examples of statistics gone wrong, such as media reports of lead in lipstick (which she proves is negligible compared with the lead we consume daily) and a medical journal article on Vioxx (the authors chose numbers that made the pain drug appear less harmful than it was).
The course includes about six lectures and accompanying quizzes each week and a homework assignment due at the beginning of the following week. Students will have a four-day window in which to complete the final.
Each lecture starts with Sainani talking, then the screen switches to graphs, charts and short paragraphs while Sainani keeps explaining, often writing simple equations onscreen.
While the examples she uses are drawn from the health care field, the lessons are valuable for anyone in need of skills in statistical analysis. "Everyone has data, everyone is getting more data, and we need to learn how to interpret them," Sainani said. "I want my students to learn how to use common sense about data, to have some skepticism."
A survey of the students indicated that 31 percent are health care professionals and 7 percent medical students. The rest are professors, students – high school through graduate school – journalists, scientists, math teachers, engineers and others. In a discussion forum on the course site, most students said they hoped the course will assist them in their careers and studies.
Sainani recorded the lectures for a combination online and in-person course for Stanford students this past spring. "Since I was putting together material for the on-campus course, it made sense to offer it as widely as possible," she said.
"I like getting my course material out to the world."
Mandy Erickson writes for Stanford Graduate School of Education.