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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 09 Dec 2009 11:33:08 -0700
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/Dec/09/t1260383639u0vxca8tzo2wim3.htm/, Retrieved Mon, 29 Apr 2024 16:34:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65128, Retrieved Mon, 29 Apr 2024 16:34:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [cs.shw.paper.univ...] [2009-12-09 17:46:01] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Explorative Data Analysis] [cs.shw.paper.edab...] [2009-12-09 18:33:08] [47f146dd9fb230449e079c6cbc92f5f5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1213.8
1245.6
1306.3
1255.8
1257.6
1287.8
1300.4
1320.9
1370.8
1327.3
1320
1345.3
1346.7
1395.4
1462
1491.6
1461.8
1477.9
1490.3
1521.1
1561.9
1552.6
1523.6
1548.3
1552.4
1587
1621.3
1648.7
1641.8
1650.6
1688.6
1670.7
1682.2
1678.9
1650.6
1662.4
1664.5
1683.2
1736.2
1747.6
1749
1759.7
1793.6
1817.4
1858.4
1839.9
1809.1
1877.7
1880.3
1930.9
2039.3
1992.7
1987.8
1984.4
2016.5
2016.7
2064.1
2031.5
2000.3
2057.8
2041.2
2093.2
2158.3
2128.8
2131.9
2170.3
2190.8
2217.7
2254.4
2223.3
2210.5
2250.8
2249.1
2288.6
2329.2
2313.8
2309.8
2345.9
2361.3
2372
2410.4
2398.5
2362.3
2419.1
2421.6
2465
2480.5
2506.1
2506.6
2525.8
2550
2578.3
2807.8
2815.3
2767.7
2815.4
2838.8
2864
2948.6
2922.8
2917.2
2936.8
2993.4
3007.8
3046.3
3011.5
2958.6
3019.8
2998.5
3040.4
3166
3110
3099.2
3150.3
3163.6
3182.6
3244.4
3223.2
3143.6
3217
3182.3
3217.2
3262.5
3227.9
3171.6
3219
3195.4
3221.6
3262.1
3179.5
3133.6
3219.2
3245
3265.3
3312.5
3383.6
3386.3
3411.1
3467.2
3487.7
3575.5
3571.5
3582.3
3637.1
3685
Dataseries Y:
Download CSV
Histogram 
2430.47
2516.3
2633.63
2799.84
3001.93
3229.29
3173.02
3322.08
3417.88
3486.95
3016.22
2709.61
2914.87
3203.08
3320.25
3446.25
3456.85
3566.53
3763.67
3607.75
3747.38
3623.91
3699.76
3629.61
3911.52
4281.47
4742.42
4522.42
4879.79
5059.11
5093.19
4941.81
4832.67
4876.18
5018.07
4780.34
4953.59
4622.32
4557.13
4560.03
4105.66
4004.89
4277.26
4245.98
4057.64
3931.42
3637.15
3339.91
3465.74
3571.25
3706.93
3584.17
3552.11
3695.24
3510
3357.7
3060.91
2736.98
2709.45
2314.96
2561.29
2663.49
2407.87
2237.74
2165.44
2098.89
2318.54
2315.49
2395.47
2474.07
2479.57
2386.92
2537.84
2567.13
2660.37
2696.28
2748.5
2663.32
2707.69
2669.36
2687.68
2650.24
2620.03
2668.47
2692.06
2737.67
2774.77
2819.19
2892.56
2866.08
2817.41
2934.75
3036.54
3139.5
3114.31
3261.3
3201.79
3264.53
3349.1
3446.17
3469.48
3507.13
3536.2
3359.05
3378.85
3449.15
3522.89
3551.04
3669.15
3602
3697.22
3760.9
3665.08
3708.8
3858.21
3933.16
3946.98
3794.29
3765.56
3820.33
3885.12
3752.67
3683.79
3240.75
3188.82
3017.98
3237.2
3182.53
2906.42
2881.35
2915.64
2635.13
2331.43
2159.04
2065.46
1983.48
1770.41
1815.99
2026.97
2124.81
2098.28
2291.39
2401.57
2453.89
2409.53

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=65128&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=65128&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65128&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






Model: Y[t] = c + b X[t] + e[t]
c4132.23578179950
b-0.372171457830325

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 4132.23578179950 \tabularnewline
b & -0.372171457830325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65128&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]4132.23578179950[/C][/ROW]
[ROW][C]b[/C][C]-0.372171457830325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65128&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65128&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:

Model: Y[t] = c + b X[t] + e[t]
c4132.23578179950
b-0.372171457830325






Descriptive Statistics about e[t]
# observations145
minimum-1250.02406628504
Q1-593.109401140098
median-15.6735842720661
mean-1.25269526552662e-13
Q3518.022260069792
maximum1589.40294189278

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 145 \tabularnewline
minimum & -1250.02406628504 \tabularnewline
Q1 & -593.109401140098 \tabularnewline
median & -15.6735842720661 \tabularnewline
mean & -1.25269526552662e-13 \tabularnewline
Q3 & 518.022260069792 \tabularnewline
maximum & 1589.40294189278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65128&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]145[/C][/ROW]
[ROW][C]minimum[/C][C]-1250.02406628504[/C][/ROW]
[ROW][C]Q1[/C][C]-593.109401140098[/C][/ROW]
[ROW][C]median[/C][C]-15.6735842720661[/C][/ROW]
[ROW][C]mean[/C][C]-1.25269526552662e-13[/C][/ROW]
[ROW][C]Q3[/C][C]518.022260069792[/C][/ROW]
[ROW][C]maximum[/C][C]1589.40294189278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65128&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65128&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:

Descriptive Statistics about e[t]
# observations145
minimum-1250.02406628504
Q1-593.109401140098
median-15.6735842720661
mean-1.25269526552662e-13
Q3518.022260069792
maximum1589.40294189278


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t]   bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
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,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')