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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 18 Aug 2013 10:07:12 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/18/t1376834885jz8zsifmgvftv5p.htm/, Retrieved Sun, 05 May 2024 22:37:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211187, Retrieved Sun, 05 May 2024 22:37:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJespers Eva
Estimated Impact149

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Tijdreeks A - Stap 3] [2013-08-18 09:07:17] [b1b8dc218b2120b615e99c976a670bd0]
- RMPD  [Harrell-Davis Quantiles] [Tijdreeks A - Sta...] [2013-08-18 11:01:33] [b1b8dc218b2120b615e99c976a670bd0]
- RMP     [Mean Plot] [Tijdreeks A - Sta...] [2013-08-18 13:01:51] [b1b8dc218b2120b615e99c976a670bd0]
- RM          [Standard Deviation-Mean Plot] [Tijdreeks A - Sta...] [2013-08-18 14:07:12] [987ccabfb1247e6edeac48c68eb55107] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2443.6
2460.2
2448.2
2470.4
2484.7
2466.8
2487.9
2508.4
2510.5
2497.4
2532.5
2556.8
2561
2547.3
2541.5
2558.5
2587.9
2580.5
2579.6
2589.3
2595
2595.6
2588.8
2591.7
2601.7
2585.4
2573.3
2597.4
2600.6
2570.6
2569.4
2584.9
2608.8
2617.2
2621
2540.5
2554.5
2601.9
2623
2640.7
2640.7
2619.8
2624.2
2638.2
2645.7
2679.6
2669
2664.6
2663.3
2667.4
2653.2
2630.8
2626.6
2641.9
2625.8
2606
2594.4
2583.6
2588.7
2600.3
2579.5
2576.6
2597.8
2595.6
2599
2621.7
2645.6
2644.2
2625.6
2624.6
2596.2
2599.5
2584.1
2570.8
2555
2574.5
2576.7
2579
2588.7
2601.1
2575.7
2559.5
2561.1
2528.3
2514.7
2558.5
2553.3
2577.1
2566
2549.5
2527.8
2540.9
2534.2
2538
2559
2554.9
2575.5
2546.5
2561.6
2546.6
2502.9
2463.1
2472.6
2463.5
2446.3
2456.2
2471.5
2447.5
2428.6
2420.2
2414.9
2420.2
2423.8
2407
2388.7
2409.6
2392
2380.2
2423.3
2451.6
2440.8
2432.9
2413.6
2391.6
2358.1
2345.4
2384.4
2384.4
2384.4
2418.7
2420
2493.1
2493.1
2492.8

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'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211187&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211187&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'Sir Maurice George Kendall' @ kendall.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12488.9534.1280609682787113.2
22576.3916666666719.189365347093754.0999999999999
32589.2333333333323.214937719781580.5
42633.4916666666733.3729192973021125.1
52623.529.068008031323683.8000000000002
62608.82523.036616110405269
72571.2083333333318.661601720856572.7999999999997
82547.82517.418439811146962.4000000000001
92496.1548.1233358626088129.2
102413.3416666666719.579277465233771.4000000000001
112405.6166666666739.8954960623452147.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2488.95 & 34.1280609682787 & 113.2 \tabularnewline
2 & 2576.39166666667 & 19.1893653470937 & 54.0999999999999 \tabularnewline
3 & 2589.23333333333 & 23.2149377197815 & 80.5 \tabularnewline
4 & 2633.49166666667 & 33.3729192973021 & 125.1 \tabularnewline
5 & 2623.5 & 29.0680080313236 & 83.8000000000002 \tabularnewline
6 & 2608.825 & 23.0366161104052 & 69 \tabularnewline
7 & 2571.20833333333 & 18.6616017208565 & 72.7999999999997 \tabularnewline
8 & 2547.825 & 17.4184398111469 & 62.4000000000001 \tabularnewline
9 & 2496.15 & 48.1233358626088 & 129.2 \tabularnewline
10 & 2413.34166666667 & 19.5792774652337 & 71.4000000000001 \tabularnewline
11 & 2405.61666666667 & 39.8954960623452 & 147.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211187&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]2488.95[/C][C]34.1280609682787[/C][C]113.2[/C][/ROW]
[ROW][C]2[/C][C]2576.39166666667[/C][C]19.1893653470937[/C][C]54.0999999999999[/C][/ROW]
[ROW][C]3[/C][C]2589.23333333333[/C][C]23.2149377197815[/C][C]80.5[/C][/ROW]
[ROW][C]4[/C][C]2633.49166666667[/C][C]33.3729192973021[/C][C]125.1[/C][/ROW]
[ROW][C]5[/C][C]2623.5[/C][C]29.0680080313236[/C][C]83.8000000000002[/C][/ROW]
[ROW][C]6[/C][C]2608.825[/C][C]23.0366161104052[/C][C]69[/C][/ROW]
[ROW][C]7[/C][C]2571.20833333333[/C][C]18.6616017208565[/C][C]72.7999999999997[/C][/ROW]
[ROW][C]8[/C][C]2547.825[/C][C]17.4184398111469[/C][C]62.4000000000001[/C][/ROW]
[ROW][C]9[/C][C]2496.15[/C][C]48.1233358626088[/C][C]129.2[/C][/ROW]
[ROW][C]10[/C][C]2413.34166666667[/C][C]19.5792774652337[/C][C]71.4000000000001[/C][/ROW]
[ROW][C]11[/C][C]2405.61666666667[/C][C]39.8954960623452[/C][C]147.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211187&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
12488.9534.1280609682787113.2
22576.3916666666719.189365347093754.0999999999999
32589.2333333333323.214937719781580.5
42633.4916666666733.3729192973021125.1
52623.529.068008031323683.8000000000002
62608.82523.036616110405269
72571.2083333333318.661601720856572.7999999999997
82547.82517.418439811146962.4000000000001
92496.1548.1233358626088129.2
102413.3416666666719.579277465233771.4000000000001
112405.6166666666739.8954960623452147.7






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha123.510998851429
beta-0.0376659097261269
S.D.0.0399746825534466
T-STAT-0.942244123534119
p-value0.370670535416216

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 123.510998851429 \tabularnewline
beta & -0.0376659097261269 \tabularnewline
S.D. & 0.0399746825534466 \tabularnewline
T-STAT & -0.942244123534119 \tabularnewline
p-value & 0.370670535416216 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211187&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]123.510998851429[/C][/ROW]
[ROW][C]beta[/C][C]-0.0376659097261269[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0399746825534466[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.942244123534119[/C][/ROW]
[ROW][C]p-value[/C][C]0.370670535416216[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211187&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)
alpha123.510998851429
beta-0.0376659097261269
S.D.0.0399746825534466
T-STAT-0.942244123534119
p-value0.370670535416216






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha24.5726349716639
beta-2.7172683344442
S.D.3.49082567406549
T-STAT-0.778402758588518
p-value0.45630781493074
Lambda3.7172683344442

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 24.5726349716639 \tabularnewline
beta & -2.7172683344442 \tabularnewline
S.D. & 3.49082567406549 \tabularnewline
T-STAT & -0.778402758588518 \tabularnewline
p-value & 0.45630781493074 \tabularnewline
Lambda & 3.7172683344442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211187&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]24.5726349716639[/C][/ROW]
[ROW][C]beta[/C][C]-2.7172683344442[/C][/ROW]
[ROW][C]S.D.[/C][C]3.49082567406549[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.778402758588518[/C][/ROW]
[ROW][C]p-value[/C][C]0.45630781493074[/C][/ROW]
[ROW][C]Lambda[/C][C]3.7172683344442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211187&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211187&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)
alpha24.5726349716639
beta-2.7172683344442
S.D.3.49082567406549
T-STAT-0.778402758588518
p-value0.45630781493074
Lambda3.7172683344442


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')