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hcistats:correlation [2014/07/23 05:17]
Koji Yatani [Effect size]
hcistats:correlation [2014/08/14 05:24] (current)
Koji Yatani
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 **If your x and y are not symmetrical,​ in other words, if you controlled only either of them (we usually define it as x), you must use regression**. This is because the relationship between x and y should be described by saying how x explains y, and not how y explains x. For example, you got data of target acquisition tasks (target sizes and performance time). In this kind of studies, you likely controlled target sizes. So, you should do regression, and see how well target sizes can predict the performance time. **If your x and y are not symmetrical,​ in other words, if you controlled only either of them (we usually define it as x), you must use regression**. This is because the relationship between x and y should be described by saying how x explains y, and not how y explains x. For example, you got data of target acquisition tasks (target sizes and performance time). In this kind of studies, you likely controlled target sizes. So, you should do regression, and see how well target sizes can predict the performance time.
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 +~~DISCUSSION:​open~~
hcistats/correlation.txt ยท Last modified: 2014/08/14 05:24 by Koji Yatani