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September 25, 2010

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anon

Any chance you could post a translation of that last para into English? For readers who don't do statistics, it would be helpful to know: what does your data show, and how does it matter? Thanks.

Alfred Brophy

Focusing on the box on top row and the second column in from the left, that plot shows the relationship between the Sisk/Leiter scores and the US News peer scores. As you move upward the Sisk/Leiter scores increase and as you move to the right, the US News peer assessment scores increase. Schools on the upper right have higher scores on both Sisk/Leiter and US News than schools on the lower left.

The relationship between the two sets of scores does not follow a straight line. The schools cluster along the bottom left, then move upwards as you move right -- rather dramatically at the far right. Eye-balling you can see the curve in the line.

The usual measure of correlation assumes a straight-line relationship between the variables. The correlation coefficient using a straight line was .80. But then I ran another correlation, which accommodates a curved line (aka a two degree polynomial). Unsurprisingly, because that follows the data point more closely, that yielded a correlation of .91.

Turning now to the last sentence of the paragraph: the square of the correlation coefficient is a particularly useful measure because it represents the percentage of agreement between the two sets of scores. The straight line correlation accounts for 64% and the curved correlation for 84%.

I think this is important because it shows the high degree of agreement between the Sisk/Leiter citation data and the US News peer assessment scores. Thanks for asking; I'm going to post some more on this.

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