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Data:
0.819543936 0.62324929 0.698970004 1.426511261 0.812913357 0.505149978 0.908485019 1.053078443 0.698970004 0.698970004 1.432969291 0.73239376 1.130333768 0.812913357 0.916453949 0.748188027 1.096910013 1.017033339 1.021189299 1.130333768 1.017033339 0.740362689 1.079181246 1.049218023 1.096910013 1.903089987 0.505149978 0.748188027 1.209515015 1.380211242 1 1.311753861 1.021189299 1.161368002 1.873553094 1.041392685 1.161368002 0.740362689 1.079181246 0.857332496 0.716003344 0.505149978 0.740362689 1.255272505 1.447158031 0.414973348 0.414973348 0.716003344 0.886490725 0.72427587 1.120573931 1.33243846 0.662757832 0.748188027 0.653212514 1.07809415 0.892094603 1.139879086 1.1775365 1.250420002 1.176091259 1.477121255 0.903089987 0.892094603 0.748188027 0.977723605 1.017033339 0.880813592 0.944482672 1.017033339 1.033423755 1.301029996 1.017033339 1.342422681 0.556302501 1.06069784 0.875061263 0.913813852 0.62324929 0.505149978 1.021189299 1.301029996 0.62324929 0.929418926 1.008600172 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1.531478917 0.431363764 0.653212514 1.079181246 1.130333768 1.161368002 0.740362689 1.062581984 1.698970004 0.929418926 0.929418926 0.875061263 1.130333768 0.740362689 0.857332496 0.740362689 1.176091259 0.755874856 0.439332694 1.105510185 0.414973348 0.740362689 0.414973348 0.643452676 1.164352856 1 1.653212514 0.423245874 1.414973348 1.021189299 1.342422681 1.544068044 1.206825876 1.146128036 0.84509804 1.06069784 1.047274867 1.537819095 0.602059991 0.740362689 1.008600172 0.924279286 0.875061263 0.447158031 0.812913357 1.431363764 1.041392685 0.505149978 1.155336037 0.875061263 1.161368002 0.439332694 0.944482672 1.079181246 1.361727836 0.752048448 1.071882007 0.755874856 1.047274867 1.290034611 0.439332694 1.230448921 1.147676324 0.439332694 0.916453949 1.307496038 0.439332694 0.439332694 0.924279286 1.113943352 1.079181246 0.255272505 0.894316063 0.653212514 0.757396029 1.214843848 0.929418926 0.77815125 0.477121255 0.763427994 1.064457989 0.740362689 1.206825876 0.544068044 1.176091259 0.477121255 1.079181246 0.477121255 1.102090526 1.079181246 0.944482672 1.078456818 0.77815125 0.954242509 1.255272505 1.033423755 0.77815125 0.954242509 1.361727836 0.928395852 0.806179974 0.819543936 1.139879086 1.811575006 1 0.602059991 1 0.447158031 1.301029996 0.477121255 0.255272505 0.954242509 0.903089987 0.838849091 1.079181246 0.255272505 0.477121255 1 1.320146286 1.093421685 0.477121255 1.033423755 0.477121255 0.477121255 0.954242509 1.139879086 0.77815125 1.235528447 0.477121255 0.477121255 1.274157849 0.954242509 1 0.602059991 0.903089987 1.06069784 1.158362492 1.041392685 1.243038049 0.51851394 1.330413773 0.819543936 0.819543936 0.995635195 0.819543936 1.372912003 0.77815125 1.041392685 0.77815125 1.176091259 0.505149978 1.176091259 1 0.954242509 0.51851394 0.45484486 0.995635195 0.806179974 0.991226076 0.963787827 0.51851394 0.748188027 0.982271233 0.414973348 1.079181246 1.178976947 0.447158031 1.049218023 0.498310554 0.447158031 1 0.698970004 1.184691431 1.301029996 0.698970004 1.100370545 0.819543936 0.51851394 0.995635195 1.740362689 0.51851394 0.653212514 1.342422681 0.352182518 0.69019608 0.698970004 1.089905111 1.40654018 1 1.021189299 0.447158031 1.462397998 0.924279286 1.146128036 0.954242509 0.51851394 0.51851394 0.84509804 0.954242509 1.308564414 0.352182518 1 1.426511261 0.498310554 0.498310554 1.234264124 0.498310554 0.755874856 0.995635195 1.181843588 0.477121255 1.11058971 0.447158031 1.008600172 1 0.579783597 0.267171728 1.516535374 0.966141733 1.400537989 0.720159303 1.358886204 0.77815125 0.477121255 1.002166062 1.190331698 0.819543936 0.892094603 0.556302501 0.982271233 0.477121255 0.51851394 1.176091259 0.875061263 0.643452676 1.152288344 1.949390007 1.301029996 0.681241237 0.788875116 0.531478917 0.819543936 1.480725379 1.008600172 1.079181246 0.477121255 0.176091259 0.544068044 0.544068044 0.447158031 0.544068044 0.204119983 0.875061263 0.812913357 0.77815125 0.380211242 1.851258349 1.206825876 0.176091259 0.397940009 0.72427587 0.380211242 1.056904851 0.491361694 0.491361694 1.079181246 1.250175948 0.477121255 0.903089987 1.161368002 0.875061263 0.602059991 0.51851394 1.047274867 1.008600172 0.929418926 0.975431809 1.29666519 0.544068044 1.002166062 0.525044807 0.531478917 0.342422681 1.243038049 0.812913357 0.653212514 1.008600172 0.795880017 0.079181246 1.305351369 0.648360011 0.648360011 1.064457989 0.819543936 0.908485019 0.716003344 1.245512668 0.913813852 0.662757832 0.477121255 0.477121255 1.477121255 0.924279286 1.702861171 0.531478917 0.380211242 0.740362689 0.67669361 0.838849091
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R Code
x <- x[!is.na(x)] bitmap(file='test1.png') par1 <- as.numeric(par1) myhist<-hist(x, breaks=par1, col=2, xlab=xlab, main=main) dev.off() bitmap(file='test2.png') qqnorm(x) qqline(x, col=2) dev.off() bitmap(file='test3.png') plot(density(x), xlab=xlab, main=main) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,signif(mean(x), 6)) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm','formula','click to see the formula')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,signif(sd(x), 6)) a<-table.element(a,hyperlink('http://www.xycoon.com/unbiased1.htm','formula','click to see the formula')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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