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Opgave 8 - S.D. Mean Plot - Nathaile Sysmans

*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: Tue, 10 May 2011 13:35:36 +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/10/t1305034340t4ry4hd91fwqr5o.htm/, Retrieved Tue, 10 May 2011 15:32:22 +0200
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W83
 
Dataseries X:
» Textbox « » Textfile « » CSV «
131676 135050 129070 137792 139762 142917 144198 142648 152170 136022 138142 138135 135027 132911 133976 137012 119610 118106 120383 133185 131416 134248 134397 127728 131837 125955 134187 143291 145074 149812 144668 147253 145568 155564 155872 156323 158010 155598 154785 157294 162938 157283 166074 169282 172552 174055 175409 173696 171283 173322 170717 174229 175339 173511 175839 173816 173990 174777 174819 176726 176199 180952 176663 182346 180605 182497 187856 190020 190108 193288 193230 199068 195076 191563 191067 186665 185508 184371 183046 175714 175768 171029 170465 170102 156389 124291 99360 86675 85056 128236 164257 162401 152779 156005 153387 153190 148840 144211 145953 145542 150271 147489 143824 134754 131736 126304 125511 125495 130133 126257 110323 98417 105749 120665 124075 127245 146731 144979 148210 144670 142970 142524 146142 146522 148128 148798 150181 152388 1556 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.org


Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11333973818.079971224638722
2142381.251872.541477066224436
3141117.257435.7421227922316148
4134731.51748.618597636434101
51228216973.7146007944215079
6131947.253129.378146426756669
7133817.57202.4305851103717336
8146701.752363.841559129265144
9153331.755185.2097594986510755
10156421.751487.825342572173225
11163894.255112.1489529029411999
121739281177.099542661252857
13172387.751660.813329867833512
14174626.251137.110775899462328
151750781162.945971803222736
161790403071.741634100546147
17185244.54423.386673880859415
18193923.53737.589374628168960
19191092.753449.30180133128411
20182159.754413.371226549319794
211718412645.636029388775666
22116678.7530740.930482284869714
23134987.537179.479362501479201
24153840.251465.225210220833226
25146136.51949.663646204994629
26144084.56757.4525032243715517
27127261.53006.810547185626241
28116282.514674.453209574831716
29119433.59510.4361449234621496
30146147.51647.500834597663540
31144539.52083.577292382823998
32149873.751881.554034125344260
33157534.52432.842165040725142
34156940.252855.565136711126033
35144652.754603.204925194339802
36136021.255212.5094644198711694
37121105.751646.626323729833882
38123815.51337.093489625912844
39116962.52609.885885117076099
40118508.251515.373303842983279
411232442404.525178352965584
42115166.25685.8407857027271638
43114200579.4854039001611414
44114248.53136.545073803346777


Regression: S.E.(k) = alpha + beta * Mean(k)
alpha14839.1888043318
beta-0.0687019968936686
S.D.0.0450844947204806
T-STAT-1.52384976962954
p-value0.135041284577757


Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha16.3780638876129
beta-0.70371884967156
S.D.0.837402004645808
T-STAT-0.84035964299991
p-value0.405465479359852
Lambda1.70371884967156
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2011/May/10/t1305034340t4ry4hd91fwqr5o/124qp1305034534.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/10/t1305034340t4ry4hd91fwqr5o/124qp1305034534.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/10/t1305034340t4ry4hd91fwqr5o/241fz1305034534.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/10/t1305034340t4ry4hd91fwqr5o/241fz1305034534.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')
 




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Software written by Ed van Stee & Patrick Wessa


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