I imagine that when you divide karma by months in the community (while still restricting yourself to the top ten percent of absolute karma) the MoR contributors will look better. I’ll do it tonight if you don’t.
They do a bit better at the top; the sample size at “top 10%” is getting small enough that tests are losing power, though:
R> lw <- read.csv("lw-survey/2012.csv") R> R> hpmor <- lw[as.character(lw$Referrals) == "Referred by Harry Potter and the Methods of Rationality",] R> other <- lw[as.character(lw$Referrals) != "Referred by Harry Potter and the Methods of Rationality",] R> R> hpmor <- hpmor[order(hpmor$KarmaScore, decreasing=TRUE),][1:25,] R> other <- other[order(other$KarmaScore, decreasing=TRUE),][1:83,] R> R> hpmortime <- hpmor$KarmaScore / as.numeric(as.character(hpmor$TimeinCommunity)) R> hpmortime <- hpmortime[!is.na(hpmortime) & !is.nan(hpmortime) & !is.infinite(hpmortime) ] R> othertime <- other$KarmaScore / as.numeric(as.character(other$TimeinCommunity)) R> othertime <- othertime[!is.na(othertime) & !is.nan(othertime) & !is.infinite(othertime) ] R> R> sort(hpmortime, decreasing=TRUE) [1] 506.78 300.00 283.96 203.62 138.46 133.95 117.61 115.92 72.22 66.67 59.09 50.00 36.92 [14] 35.05 35.00 33.90 28.60 26.67 24.82 23.96 20.36 19.28 17.71 11.91 R> sort(othertime, decreasing=TRUE) [1] 1895.36 647.88 456.97 338.89 263.16 250.00 250.00 235.71 184.90 183.33 173.91 166.67 [13] 165.00 146.93 146.65 145.83 142.86 133.33 133.33 133.33 125.00 125.00 125.00 116.45 [25] 102.73 100.00 97.22 84.38 83.33 83.33 83.33 83.33 75.00 75.00 74.51 72.00 [37] 69.60 68.88 66.67 66.67 63.33 61.11 60.71 60.34 58.33 57.14 55.95 53.43 [49] 52.17 50.00 50.00 50.00 50.00 48.48 46.46 44.12 43.75 41.67 41.43 40.00 [61] 39.66 36.36 35.91 33.33 33.33 31.67 31.32 30.00 30.00 30.00 27.50 27.47 [73] 26.95 25.33 25.00 25.00 24.06 23.33 22.73 18.25 16.67 16.67 R> R> t.test(hpmortime,othertime) Welch Two Sample t-test data: hpmortime and othertime t = -0.544, df = 72.4, p-value = 0.5881 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -87.52 49.99 sample estimates: mean of x mean of y 98.44 117.20
I imagine that when you divide karma by months in the community (while still restricting yourself to the top ten percent of absolute karma) the MoR contributors will look better. I’ll do it tonight if you don’t.
They do a bit better at the top; the sample size at “top 10%” is getting small enough that tests are losing power, though: