Landing : Athabascau University

Take a Statistics MOOC this summer??

Lloyd Rieber from University of Georgia is repeating his popular MOOC on Statistcis in Education next month. He writes:

I am again offering my MOOC on introductory uses of statistics in education. This section will run from July 7-August 12, 2014 on < >

Here's a link to the course site:

The course is free.

I made a short 3-minute 'mash-up' of a selection of the course's videos to give people a taste of the course:

Also, all of the course videos are available on YouTube – here is a link to the playlist:

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 in education.  

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 at the end 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).




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