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<blockquote data-quote="takethepoints" data-source="post: 196476" data-attributes="member: 265"><p>You are making a rookie mistake in data analysis: you're using averages to compare cases. If the averages and the medians in any distribution are close to each other, then, by all means use, the arithmetic average (the mean). If they aren't, then the usual reason is far outliers that are distorting the levels. When that happens, you use the medians since they are a lot more resistant. You are clinging to the averages like a drunk clings to a lamppost: for support, not illumination. (I stole that line from an Oxford debate I saw once on youtube.) When there are far outliers, eliminate them, use the medians and you'll always get a better view of the actual level of any distribution.</p><p></p><p>As for Laskey, here's his summary, leaving out the games where he didn't play:</p><p> </p><p> <span style="font-family: 'Courier New'">Min. 1st Qu. Median Mean 3rd Qu. Max. </span></p><p><span style="font-family: 'Courier New'"> 3.300 4.600 4.700 4.944 5.400 7.200 </span></p><p><span style="font-family: 'Courier New'"></span></p><p><span style="font-family: 'Georgia'">As you will probably notice, the mean and median of this distribution are pretty much identical. No need to leave out his best game (Ugag) because it isn't a far outlier. He gave us pretty much the same production in every game, right about 5 ypc. This is how such performances should be evaluated; by how much the <em>real</em> level was. For Marshall it was about 4.3 ypc, for Laskey about 4.7.</span></p><p><span style="font-family: 'Georgia'"></span></p><p><span style="font-family: 'Georgia'">As I said before, Marshall did ok for a freshman. There's no reason to inflate his figures. By the same token, however, and, like I said before, I think he would be more productive out on the edge. That's up to Coach.</span></p></blockquote><p></p>
[QUOTE="takethepoints, post: 196476, member: 265"] You are making a rookie mistake in data analysis: you're using averages to compare cases. If the averages and the medians in any distribution are close to each other, then, by all means use, the arithmetic average (the mean). If they aren't, then the usual reason is far outliers that are distorting the levels. When that happens, you use the medians since they are a lot more resistant. You are clinging to the averages like a drunk clings to a lamppost: for support, not illumination. (I stole that line from an Oxford debate I saw once on youtube.) When there are far outliers, eliminate them, use the medians and you'll always get a better view of the actual level of any distribution. As for Laskey, here's his summary, leaving out the games where he didn't play: [FONT=Courier New]Min. 1st Qu. Median Mean 3rd Qu. Max. 3.300 4.600 4.700 4.944 5.400 7.200 [/FONT] [FONT=Georgia]As you will probably notice, the mean and median of this distribution are pretty much identical. No need to leave out his best game (Ugag) because it isn't a far outlier. He gave us pretty much the same production in every game, right about 5 ypc. This is how such performances should be evaluated; by how much the [I]real[/I] level was. For Marshall it was about 4.3 ypc, for Laskey about 4.7. As I said before, Marshall did ok for a freshman. There's no reason to inflate his figures. By the same token, however, and, like I said before, I think he would be more productive out on the edge. That's up to Coach.[/FONT] [/QUOTE]
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