Data to Insight – MOOC with FREE access

There is still time to signup to the FutureLearn Data to Insight MOOC. This is a fantastic opportunity for anyone who wants to start an introduction to data handling.

The course is being facilitated by the Department of Statistics at The University of Auckland, New Zealand, below you can find a brief introduction from Professor Chris Wild who is based in the department and is the lead educator for Data to Insight.

Note that while the educators and facilitators are based in New Zealand the FutureLearn MOOC is based in the UK where most of the content is hosted.

With the world of data (big and otherwise) growing explosively, statistics education has to find ways to get much further, much faster.

By agreeing to produce a statistics MOOC, my university has given me the space and technical support to produce a prototype for introductory statistics that takes up the challenge of finding ways for getting much further into data much faster. The course, called “Data to Insight” launched on the UK’s FutureLearn platform 10 days ago.

Course Details

Most of the content is delivered in 42 five-minute videos. The course has a 8-week, “3 hours a week” structure and each week features just 30-minutes of instructional video. Within a few days, students are launched into a 10,000-observation, 70-variable dataset derived from a large observational health study (NHANES) and a dataset derived from Gapminder using 30 country-level indicators of over the last 50 years.

There are a large number of new ideas and approaches prototyped in this course and one of the main audiences I want to reach with them is other tertiary (university and college) teachers of statistics and research methods.

To make it easy for you to see quickly what has been done and how, I’ve made a combined course outline/index page which lets you bypass the normal course layout and jump right to particular movies.

Access to the resources can be secured up until 30 November so start the course soon, here:

Chris Wild, Department of Statistics, The University of Auckland, New Zealand