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copied!<p>what about:</p> <pre><code>> swiss$qEdu <- cut (swiss$Education, breaks = quantile (swiss$Education, c (0, .25, .5, .75, 1)), include.lowest = TRUE) > aggregate (swiss$Infant.Mortality, list (qEdu = swiss$qEdu), FUN = mean) qEdu x 1 [1,6] 19.31429 2 (6,8] 21.93636 3 (8,12] 19.38182 4 (12,53] 19.30909 </code></pre> <p>(I don't really know what your numbers are - they don't coincide with the averages I get)</p> <p>(That was before the edit...)</p> <p>(After 2nd edit:) If you want the Infant.Mortality for each of the provinces belongig to that quartile of Eduction, use <code>list ()</code> as aggregation function:</p> <pre><code>> aggregate (swiss$Infant.Mortality, list (qEdu = swiss$qEdu), FUN = list) qEdu x 1 [1,6] 20.2, 24.5, 18.7, 21.2, 22.4, 15.3, 21.0, 18.0, 15.1, 19.8, 18.3, 19.4, 20.2, 16.3 2 (6,8] 20.3, 26.6, 23.6, 24.9, 21.0, 19.1, 20.0, 23.8, 22.5, 20.0, 19.5 3 (8,12] 22.2, 22.2, 16.5, 22.7, 20.0, 18.0, 16.7, 16.3, 17.8, 20.3, 20.5 4 (12,53] 20.6, 24.4, 20.2, 10.8, 20.9, 18.1, 18.9, 23.0, 18.0, 18.2, 19.3 </code></pre> <p>or:</p> <pre><code>> Infant.Mortality <- lapply (levels (swiss$qEdu), function (x) swiss$Infant.Mortality [swiss$qEdu == x]) > names (Infant.Mortality) <- levels (swiss$qEdu) > Infant.Mortality $`[1,6]` [1] 20.2 24.5 18.7 21.2 22.4 15.3 21.0 18.0 15.1 19.8 18.3 19.4 20.2 16.3 $`(6,8]` [1] 20.3 26.6 23.6 24.9 21.0 19.1 20.0 23.8 22.5 20.0 19.5 $`(8,12]` [1] 22.2 22.2 16.5 22.7 20.0 18.0 16.7 16.3 17.8 20.3 20.5 $`(12,53]` [1] 20.6 24.4 20.2 10.8 20.9 18.1 18.9 23.0 18.0 18.2 19.3 </code></pre>

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