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Description of Statistical Computation

Author's title

Opgave 8 Oefening 3 - Wisselkoers Euro in Dollar - Standard Deviation Mean ...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 27 May 2009 13:02:29 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/27/t1243451040j3g6nzakt7q7npl.htm/, Retrieved Fri, 03 May 2024 03:44:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40490, Retrieved Fri, 03 May 2024 03:44:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Opgave 8 Oefening...] [2009-05-27 19:02:29] [69a8397eb9368d6355c6053ed100f2c7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.1608
1.1208
1.0883
1.0704
1.0628
1.0378
1.0353
1.0604
1.0501
1.0706
1.0338
1.0110
1.0137
0.9834
0.9643
0.9470
0.9060
0.9492
0.9397
0.9041
0.8721
0.8552
0.8564
0.8973
0.9383
0.9217
0.9095
0.8920
0.8742
0.8532
0.8607
0.9005
0.9111
0.9059
0.8883
0.8924
0.8833
0.8700
0.8758
0.8858
0.9170
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.2490
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.2020
1.2271
1.2770
1.2650
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.4570
1.4718
1.4748
1.5527
1.5750
1.5557
1.5553
1.5770
1.4975
1.4369
1.3322
1.2732
1.3449
1.3239

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40490&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40490&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40490&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.066841666666670.0411354405555230.149800000000000
20.9240333333333330.05048741217252860.1585
30.895650.02452874010032090.0851
40.9449083333333330.05482170204537170.1483
51.13090.04972414814846910.1664
61.243333333333330.04244370246323800.1423
71.2447750.05156309682850180.1415
81.255658333333330.03886141948311230.1275
91.370633333333330.05467872003112750.1685
101.470583333333330.1040878198562360.3038

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.06684166666667 & 0.041135440555523 & 0.149800000000000 \tabularnewline
2 & 0.924033333333333 & 0.0504874121725286 & 0.1585 \tabularnewline
3 & 0.89565 & 0.0245287401003209 & 0.0851 \tabularnewline
4 & 0.944908333333333 & 0.0548217020453717 & 0.1483 \tabularnewline
5 & 1.1309 & 0.0497241481484691 & 0.1664 \tabularnewline
6 & 1.24333333333333 & 0.0424437024632380 & 0.1423 \tabularnewline
7 & 1.244775 & 0.0515630968285018 & 0.1415 \tabularnewline
8 & 1.25565833333333 & 0.0388614194831123 & 0.1275 \tabularnewline
9 & 1.37063333333333 & 0.0546787200311275 & 0.1685 \tabularnewline
10 & 1.47058333333333 & 0.104087819856236 & 0.3038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40490&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]1.06684166666667[/C][C]0.041135440555523[/C][C]0.149800000000000[/C][/ROW]
[ROW][C]2[/C][C]0.924033333333333[/C][C]0.0504874121725286[/C][C]0.1585[/C][/ROW]
[ROW][C]3[/C][C]0.89565[/C][C]0.0245287401003209[/C][C]0.0851[/C][/ROW]
[ROW][C]4[/C][C]0.944908333333333[/C][C]0.0548217020453717[/C][C]0.1483[/C][/ROW]
[ROW][C]5[/C][C]1.1309[/C][C]0.0497241481484691[/C][C]0.1664[/C][/ROW]
[ROW][C]6[/C][C]1.24333333333333[/C][C]0.0424437024632380[/C][C]0.1423[/C][/ROW]
[ROW][C]7[/C][C]1.244775[/C][C]0.0515630968285018[/C][C]0.1415[/C][/ROW]
[ROW][C]8[/C][C]1.25565833333333[/C][C]0.0388614194831123[/C][C]0.1275[/C][/ROW]
[ROW][C]9[/C][C]1.37063333333333[/C][C]0.0546787200311275[/C][C]0.1685[/C][/ROW]
[ROW][C]10[/C][C]1.47058333333333[/C][C]0.104087819856236[/C][C]0.3038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40490&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40490&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.066841666666670.0411354405555230.149800000000000
20.9240333333333330.05048741217252860.1585
30.895650.02452874010032090.0851
40.9449083333333330.05482170204537170.1483
51.13090.04972414814846910.1664
61.243333333333330.04244370246323800.1423
71.2447750.05156309682850180.1415
81.255658333333330.03886141948311230.1275
91.370633333333330.05467872003112750.1685
101.470583333333330.1040878198562360.3038






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0247097466146087
beta0.0657667655398022
S.D.0.0293185787195703
T-STAT2.24317713927594
p-value0.0551513617194521

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0247097466146087 \tabularnewline
beta & 0.0657667655398022 \tabularnewline
S.D. & 0.0293185787195703 \tabularnewline
T-STAT & 2.24317713927594 \tabularnewline
p-value & 0.0551513617194521 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40490&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0247097466146087[/C][/ROW]
[ROW][C]beta[/C][C]0.0657667655398022[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0293185787195703[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.24317713927594[/C][/ROW]
[ROW][C]p-value[/C][C]0.0551513617194521[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40490&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40490&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0247097466146087
beta0.0657667655398022
S.D.0.0293185787195703
T-STAT2.24317713927594
p-value0.0551513617194521






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.19694741535954
beta1.25356511388591
S.D.0.598236985809584
T-STAT2.09543231799599
p-value0.0694290451843569
Lambda-0.253565113885913

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.19694741535954 \tabularnewline
beta & 1.25356511388591 \tabularnewline
S.D. & 0.598236985809584 \tabularnewline
T-STAT & 2.09543231799599 \tabularnewline
p-value & 0.0694290451843569 \tabularnewline
Lambda & -0.253565113885913 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40490&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.19694741535954[/C][/ROW]
[ROW][C]beta[/C][C]1.25356511388591[/C][/ROW]
[ROW][C]S.D.[/C][C]0.598236985809584[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.09543231799599[/C][/ROW]
[ROW][C]p-value[/C][C]0.0694290451843569[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.253565113885913[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40490&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40490&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.19694741535954
beta1.25356511388591
S.D.0.598236985809584
T-STAT2.09543231799599
p-value0.0694290451843569
Lambda-0.253565113885913


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
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')