Standard Deviation Mean Plot australische chocoladeproductie

*Unverified author*

R Software Module: /rwasp_smp.wasp (opens new window with default values)

Title produced by software: Standard Deviation-Mean Plot

Date of computation: Mon, 09 May 2011 15:33:00 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/09/t130495503054lm2t63p0p6ps4.htm/, Retrieved Mon, 09 May 2011 17:30:32 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W83

Dataseries X:

» Textbox « » Textfile « » CSV «

7992 6114 5965 8460 8323 6333 5675 10090 9035 6976 6459 10896 9978 7466 7199 10977 9412 6341 7784 11911 10079 7721 8197 12038 11963 8033 8618 13625 11734 8895 8727 13974 12583 9525 9662 15490 13839 10047 9788 14978 13045 9489 8741 13149 14106 9998 10034 15081 13266 9997 9027 14324 13149 11209 10332 15354 13800 11786 10550 16114 13255 11403 10269 14009 15847 12967 11328 15814 18626 13219 13818 18062 15722 12111 11702 15589 14852 13612 12380 15501 16322 12157 11124 14621 14035 11159 10944 15824 14378 11816 12233 17344 16812 12181 13275 18458 17375 14609 13323 18327 16053 15070 13806 18245 17461 14999 16022 20564 16372 15854 15115 18207 19488 16644 18631 21093 22212 19762 19403 21227 23176 20823 20647 21336 23458 22003 21647 26416 25226 24723 19945 24040 25034 24885 21168 23541 26019 24657 20599 24534 28717 26138 22968 26577 28660 30430 27356 25454 30194

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Herman Ole Andreas Wold' @ www.yougetit.org Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 7132.75 1278.20117743648 2495 2 7605.25 2002.80076809119 4415 3 8341.5 2034.27374427993 4437 4 8905 1864.19508993381 3778 5 8862 2388.61368440636 5570 6 9508.75 1969.68937906463 4317 7 10559.75 2678.29091959779 5592 8 10832.5 2507.90490250328 5247 9 11815 2826.95112562398 5965 10 12163 2636.36631243333 5190 11 11106 2319.5893314694 4408 12 12304.75 2672.66825164167 5083 13 11653.5 2541.27402431667 5297 14 12511 2231.06387178852 5022 15 13062.5 2435.68381910844 5564 16 12234 1707.32266038575 3740 17 13989 2229.2146599195 4519 18 15931.25 2806.17763455321 5407 19 13781 2171.5958801459 4020 20 14086.25 1381.31492305943 3121 21 13556 2356.32524636703 5198 22 12990.5 2356.71077280745 4880 23 13942.75 2530.10241887557 5528 24 15181.5 2945.71581566632 6277 25 15908.5 2336.18456748035 5004 26 15793.5 1875.34894530769 4439 27 17261.5 2422.22851935981 5565 28 16387 1318.42051966232 3092 29 18964 1852.97112767577 4449 30 20651 1305.92521480622 2809 31 21495.5 1157.83260160238 2529 32 23381 2169.69997925981 4769 33 23483.5 2408.55011711749 5281 34 23657 1790.03631248084 3866 35 23952.25 2334.58395651131 5420 36 26100 2372.55741061553 5749 37 27975 2100.38504406533 4976 Regression: S.E.(k) = alpha + beta * Mean(k) alpha 2316.38111622882 beta -0.00967450504415018 S.D. 0.014169885072934 T-STAT -0.682751129903625 p-value 0.499258589419991 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha 8.11117671175802 beta -0.0474858791962382 S.D. 0.113865965960912 T-STAT -0.417033121315103 p-value 0.679201083720846 Lambda 1.04748587919624

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/09/t130495503054lm2t63p0p6ps4/179du1304955179.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t130495503054lm2t63p0p6ps4/179du1304955179.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t130495503054lm2t63p0p6ps4/21guq1304955179.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/09/t130495503054lm2t63p0p6ps4/21guq1304955179.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) arr <- array(NA,dim=c(par1,np)) j <- 0 k <- 1 for (i in 1:(np*par1)) { j = j + 1 arr[j,k] <- x[i] if (j == par1) { j = 0 k=k+1 } } arr arr.mean <- array(NA,dim=np) arr.sd <- array(NA,dim=np) arr.range <- array(NA,dim=np) for (j in 1:np) { arr.mean[j] <- mean(arr[,j],na.rm=TRUE) arr.sd[j] <- sd(arr[,j],na.rm=TRUE) arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) } arr.mean arr.sd arr.range (lm1 <- lm(arr.sd~arr.mean)) (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) (lm2 <- lm(arr.range~arr.mean)) bitmap(file='test1.png') plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') dev.off() bitmap(file='test2.png') plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Section',header=TRUE) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,'Standard Deviation',header=TRUE) a<-table.element(a,'Range',header=TRUE) a<-table.row.end(a) for (j in 1:np) { a<-table.row.start(a) a<-table.element(a,j,header=TRUE) a<-table.element(a,arr.mean[j]) a<-table.element(a,arr.sd[j] ) a<-table.element(a,arr.range[j] ) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lnlm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Lambda',header=TRUE) a<-table.element(a,1-lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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