This came across my email announcements, and I wanted to make sure and share it. Dr. Lloyd Rieber is offering his free MOOC again on statistics. It starts on October 7, 2013.
I’ve heard a couple of folks talk about the first iteration of the course, and it’s been really well received. As I mentioned in my previous post about Lloyd, he is an exceptional teacher. He is able to make complex topics concrete and understandable. This would be an excellent refresher or a great introduction for someone a little apprehensive. It’s free with very low risks to you. You’ll like Dr. Rieber and how he teaches. 😉
Here’s the details:
I am again offering my MOOC on introductory uses of statistics in education.
This section will run from October 7-November 11, 2013 on Canvas.net
Here’s a link to the course site:
The course is free.
I designed the course for “mere mortals,” meaning that I designed it for
people who want to know about and use statistics as but one important tool
in their work, but who are not — and don’t want to be — mathematicians or
statisticians. A special note that I also designed it with doctoral students
in mind, especially those who are about to take their first statistics
course. It could also be good for those students who just finished a
statistics course, but are still fuzzy on the details.
However, this course would be useful to anyone who wants a good, short,
hands-on, friendly introduction to the most fundamental ideas of statistics
Here’s my approach … I provide a short presentation or two on each
statistics topic, followed by a video tutorial where you build an Excel
spreadsheet from scratch to compute the statistic. Then, I ask you to take a
short quiz — consisting of sometimes just one question — where I ask you to
plug in some new data into your spreadsheet and then copy and paste one of
your new calculations as your answer. (And yes, there is also a short final
exam on the conceptual stuff.)
Examples of specific skills to be learned include the scales of measurement,
measures of central tendency, measures of variability, and the computation
of the following: mean, mode, and median, standard deviation, z (standard)
scores, Pearson product-moment correlation coefficient (r),
correlated-samples t test (i.e. dependent t test), independent-samples t
test, and a one-way analysis of variance (ANOVA).
* Lloyd P. Rieber
* Director, Innovation in Teaching & Technology for
* the College of Education
* Professor, Department of Career & Information
* 203 River’s Crossing
* The University of Georgia
* Athens, Georgia 30602-7144 USA
* Phone: 706-542-3986
* FAX: 706-542-4054
* Email: email@example.com