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tutorial9SMP

*The author of this computation has been verified*
R Software Module: /rwasp_smp.wasp (opens new window with default values)
Title produced by software: Standard Deviation-Mean Plot
Date of computation: Wed, 15 Dec 2010 16:56:05 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4.htm/, Retrieved Wed, 15 Dec 2010 17:54:05 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1,3866 1,3582 1,3332 1,3595 1,3617 1,3684 1,3394 1,3262 1,3173 1,3085 1,327 1,3182 1,293 1,291 1,2984 1,2795 1,299 1,3174 1,326 1,3111 1,2816 1,276 1,2849 1,2818 1,2829 1,2796 1,3008 1,2967 1,2938 1,2833 1,2823 1,2765 1,2634 1,2596 1,2705 1,2591 1,2798 1,2763 1,2795 1,2782 1,2644 1,2596 1,2615 1,2555 1,2555 1,2658 1,2565 1,2783 1,2786 1,2782 1,2905 1,3042 1,2942 1,313 1,3671 1,3549 1,3558 1,3507 1,3494 1,3607 1,3295 1,3193 1,3308 1,3246 1,3392 1,3425 1,3496 1,3255 1,3231 1,3273 1,3276 1,3173 1,3196 1,3058 1,2966 1,2932 1,2947 1,305 1,3232 1,3125 1,2992 1,3266 1,3275 1,3223 1,3403 1,3322 1,3363 1,3425 1,3574 1,3683 1,3623 1,3563 1,3518 1,3494 1,3612 1,369 1,3771 1,3972 1,401 1,3908 1,3901 1,3856 1,4098 1,422 1,4238 1,4207 1,4095 1,4177 1,3866 1,3959 1,4102 1,3969 1,4004 1,385 1,389 1,384 1,392 1,3932 1,3858 1,3978 1,4029 1,394 1,4096 1,4058 1,4134 1,4096 1,4049 1,4009 1,3897 1,4019 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'George Udny Yule' @ 72.249.76.132


Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.359840.01892123146098060.0534000000000001
21.331960.02335429296724700.0599000000000001
31.305520.01612798809523370.036
41.30660.01806529822615720.0465
51.281440.003311042132018220.0088999999999999
61.290840.009020698420854060.0211999999999999
71.270460.009279709047163030.0226999999999999
81.274580.008762819181062650.0206999999999999
91.25930.003867169507533870.0088999999999999
101.271480.00998784260989330.0221
111.31380.03106742667167650.0766
121.35430.004487204029236930.0113000000000001
131.328680.007424082434887160.0199000000000000
141.33360.01173413822996820.0265000000000000
151.313380.01219926227277700.0309999999999999
161.305720.01255217112694060.03
171.323180.01499389875916200.0411000000000001
181.347340.01512491322289160.0361
191.35620.005652875374532910.0129000000000001
201.387020.01356915620073700.032
211.406260.01771942436988290.0382
221.406080.01452212105720100.0341
231.39630.009891410415102560.0251999999999999
241.390560.00563808478120010.0138000000000000
251.405140.00737685569873780.0194000000000001
261.40140.007363423117002060.0199000000000000
271.395160.004662402814000580.00900000000000012
281.414980.006621706728631170.0133999999999999
291.42290.002760434748368460.00780000000000003
301.419640.01405962303904330.0330999999999999
311.43010.01093206293432310.0244
321.41860.01043910915739460.0222
331.426640.00934788746188140.0218000000000000
341.429760.004174685616905720.00959999999999983
351.43240.009620031184980680.0253000000000001
361.456660.0036087393920870.00890000000000013
371.470520.00475363019175870.0122
381.46840.009543846184845950.0233999999999999
391.461140.007750677389751160.0185000000000000
401.476720.006133269927208450.0169999999999999
411.490060.004466878104448370.0107000000000002
421.496680.006589157761049570.0145999999999999
431.476060.005821340051912430.0142
441.48880.009020254985309440.0223
451.493340.006990922685883480.0169000000000001
461.491440.007104787118556010.0153999999999999
471.503380.006882368778262340.0165000000000000
481.496780.01720354614607110.0346
491.468860.009514883078630050.0226999999999999
501.437740.01071554944928160.0281
511.4370.006292455800400980.0157000000000000
521.437820.005305845832664220.0138000000000000
531.446620.01130561807244520.0289999999999999
541.424360.01402615414146010.0309999999999999
551.408840.005992328428916460.0152000000000001
561.392940.005347242279904680.0137000000000000
571.371680.003470878851242150.00849999999999995
581.362420.006570920787834860.0159000000000000
591.355160.005287532505810240.0137000000000000
601.359040.006138648059630080.0143000000000000
611.361360.004593800169794090.0105000000000002
621.372180.004224570984135510.0105000000000000
631.344640.009502789064269510.0209999999999999
641.345060.005485708705354350.0129000000000001
651.340020.01105811918908460.0289000000000001
661.354180.006921488279264810.0183
671.33660.007111258679024410.0175000000000001
681.326880.003264506088216050.00769999999999982
691.28910.01535398970951850.0362
701.256240.01455723187972210.0348999999999999
711.237780.008744255257024430.0226999999999999
721.229560.006132536180080790.0161
731.21320.01240302382485820.0308999999999999
741.207460.01181029212170470.0307000000000002
751.233220.006029676608243620.0133000000000001
761.228480.003335715815233670.0081
771.237520.01570181518169160.0349999999999999
781.26030.004253821811030650.00930000000000009
791.281140.01785729542791970.0431000000000001
801.286780.004558179461144520.0113999999999999
811.30390.003324906013709260.0081
821.32080.003081395787626070.00769999999999982
831.291160.01547362271738590.0343
841.279820.008428641646196670.0176000000000001
851.26660.004981967482832450.0102000000000000
861.280120.007305614279442930.0194000000000001
871.273640.003990989852154460.0104000000000000
881.301020.00965152837637650.0228000000000002
891.333920.01352911674870160.0356999999999998
901.3630.01053873806487280.0266000000000000
911.388320.007381869681862490.0190000000000001
921.397540.01178613592319380.0267999999999999
931.394020.00819981707113030.0172000000000001
941.38710.004930010141977390.0123000000000000
951.405540.0121094178225050.0327000000000002
961.375040.01202301958744140.0319000000000000
971.361220.007657480003238630.0192999999999999
981.330540.01318836608530410.0349999999999999


Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0199585030612476
beta-0.00790374240592255
S.D.0.00652274424505511
T-STAT-1.21172042149504
p-value0.228593503719


Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.61550734181943
beta-0.667286454336136
S.D.0.938493281139817
T-STAT-0.71101889352442
p-value0.478796512237765
Lambda1.66728645433614
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4/1t9vp1292432162.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4/1t9vp1292432162.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4/2m1vs1292432162.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/15/t1292432044bakr3918vd677f4/2m1vs1292432162.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 <- 5
(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

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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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