13:13 Feb 22, 2017 |
Spanish to English translations [PRO] Science - Mathematics & Statistics / Results of experiment | |||||||
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| Selected response from: Samantha Cook United States Local time: 08:36 | ||||||
Grading comment
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Summary of answers provided | ||||
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4 +1 | statistically significant differences and an effect size of medium or larger |
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Discussion entries: 3 | |
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statistically significant differences and an effect size of medium or larger Explanation: Here a basically literal translation is correct. If you're not familiar with the terms it probably sounds strange, but statistical significance and effect size are two different ways to measure the effect of some treatment. Statistical significance here is related to the likelihood that an observed difference in outcomes between two groups was due to random chance. If unlikely, the conclusion is that the observed difference must be due to the treatment being studied, and the difference is deemed statistically significant. Effect size is a way to quantify how large or how important the effect of a treatment is. It can be measured in various ways, and Cohen proposed a scale (arbitrary but used quite often in some fields) where an effect size of 0.2 is considered "small," 0.5 is considered "medium," and 0.8 is considered "large." Since they are measured differently, it's possible to have a statistically significant outcome whose effect size is small or, conversely, an outcome that is not statistically significant but whose effect size is large. The text is focusing on those that are both statistically significant and have large effect size as a way of highlighting the "most important" outcome variables. Some references for effect sizes: -------------------------------------------------- Note added at 5 hrs (2017-02-22 19:06:12 GMT) -------------------------------------------------- No problem Lucy, glad to help! https://en.wikipedia.org/wiki/Effect_size Reference: http://staff.bath.ac.uk/pssiw/stats2/page2/page14/page14.htm... |
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