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It's the effect size, stupid: what effect size is and why it is important

It's the effect size, stupid: what effect size is and why it is important
It's the Effect Size, StupidWhat effect size is and why it is important Robert CoeSchool of Education, University of Durham, email Paper presented at the Annual Conference of the British Educational Research Association, University of Exeter, England, 12-14 September 2002 Abstract Effect size is a simple way of quantifying the difference between two groups that has many advantages over the use of tests of statistical significance alone. Effect size emphasises the size of the difference rather than confounding this with sample size. 'Effect size' is simply a way of quantifying the size of the difference between two groups. The routine use of effect sizes, however, has generally been limited to meta-analysis - for combining and comparing estimates from different studies - and is all too rare in original reports of educational research (Keselman et al., 1998). 1. The average score was 15.2 for the morning group, 17.9 for the afternoon group: a difference of 2.7. (a) (b) 2.

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The Cult of Outstanding™: the problem with ‘outstanding’ lessons First of all I need to come clean. Up until pretty recently I was a fully paid up member of the Cult of Outstanding™. Last January I considered myself to be a teacher at the height of my powers. In the spirit of self-congratulation I posted a blog entitled Anatomy of an Outstanding Lesson in which I detailed a lesson which I confidently supposed was the apotheosis of great teaching, and stood back to receive plaudits. And indeed they were forthcoming. Matlab Matlab is a tool for doing numerical computations with matrices and vectors. It can also display information graphically. The best way to learn what Matlab can do is to work through some examples at the computer. After reading the " getting started " section, you can use the tutorial below for this. Getting started

Style Anomaly: Value versus Growth - June 23, 2011 This page is temporarily not available. Please check later as it should be available shortly. If you have any questions, please email customer support at or call 800-767-3771 ext. 9339. Summer is heating up and some of the greatest baseball rivalries are in full swing. Classroom observation: it’s harder than you think - CEM Blog - Centre for Evaluation and Monitoring Professor Robert Coe We’ve all done it: observed another teacher’s lesson and made a judgement about how effective the teaching was. Instinctively it feels valid. I am a good teacher; I’ll know a good lesson when I see one. We’ve all experienced it from the other side – being observed – but this time the feeling may be more mixed.

HyperStat Online: An Introductory Statistics Textbook and Online Tutorial for Help in Statistics Courses Recommend HyperStat to your friends on Facebook Click here for more cartoons by Ben Shabad. Other Sources Stat Primer by Bud Gerstman of San Jose State University A Cautionary Tale of Educational Evidence Let me first say that I am a big fan of educational research and undertaking trials in schools. Of course, we are not doctors and surgeons dealing with the clear boundaries of sickness and health, or the obvious dichotomy between medicine and placebo. We can, however, design far more robust trials that help us work out what works best in our classrooms. I think we have a moral imperative to do our best to do so. The pursuit of evidence in education could be better and I’m hopeful we can make this happen. I think that even undertaking the process of controlled trials in the classroom, and attempting to isolate one variable in a fistful of complex variables, has value regardless of the results and we learn much from the process.

StatPrimer © B. Gerstman 2003 StatPrimer (Version 6.4) B. Burt Gerstman (email) Part A (Introductory) (1) Measurement and sampling [Exercises] (2) Frequency distributions [Exercises] Capital Ideas - Rethinking Stock Returns New Evidence on Value Versus Growth Research by Eugene F. Fama "Value Versus Growth: The International Evidence," a 1997 working paper co-written by finance professor Eugene Fama of the University of Chicago Graduate School of Business and Kenneth R. French, a former Chicago faculty member now at the Yale School of Management, argues that the conventional wisdom is wrong.