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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 computationSun, 01 Nov 2009 08:14:00 -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/Nov/01/t1257088556qyd3gj2wykn53bt.htm/, Retrieved Mon, 06 May 2024 15:13:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52338, Retrieved Mon, 06 May 2024 15:13:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Shwws5v1] [2009-11-01 15:14:00] [93b66894f6318f3da4fcda772f2ffa6f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1,527069369
-1,543374062
-1,749411243
-1,984362504
-2,096863827
-2,130831937
-2,327358048
-2,269097638
-1,977733622
-1,639143732
-1,587676945
-1,708495354
-1,531372252
-1,826647701
-1,405551196
-1,428649511
-1,081742534
-0,92130499
-0,997393557
-0,998808959
-1,061475023
-1,223600771
-2,08296827
-2,28617994
-2,785701594
-3,810231187
-4,554652717
-4,762918418
-5,315378939
-5,935502878
-6,172790721
-5,606202641
-5,87931154
-5,050443555
-4,325106136
-4,008199159
-3,888631411
-3,712640323
-2,205439375
-2,033535044
-1,427600633
-0,420569718
-0,260621103
-0,766015199
-0,208722064
Dataseries Y:
Download CSV
Histogram 
-93,77360523
-93,73306095
-103,1358493
-114,0870047
-115,5549183
-117,6437844
-126,5568902
-127,2161645
-115,1845555
-109,2791818
-109,4382293
-116,8531948
-108,2587736
-115,8829226
-96,19798101
-95,46720995
-86,5947845
-80,67913874
-83,53659877
-89,11287953
-94,71811708
-106,1183654
-145,5773415
-155,5792227
-176,9022139
-215,8126868
-255,5621618
-264,1545419
-294,3010925
-326,5270535
-336,4087986
-312,4377123
-335,55025
-315,6649002
-292,2127707
-282,1103453
-275,2843366
-248,7445657
-192,5572009
-187,7306026
-166,0571578
-125,4087714
-119,8134431
-148,9118987
-127,2784992

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52338&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52338&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52338&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Model: Y[t] = c + b X[t] + e[t]
c-51.8537026456191
b46.8034060469103

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -51.8537026456191 \tabularnewline
b & 46.8034060469103 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52338&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-51.8537026456191[/C][/ROW]
[ROW][C]b[/C][C]46.8034060469103[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52338&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52338&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]
c-51.8537026456191
b46.8034060469103






Descriptive Statistics about e[t]
# observations45
minimum-65.6558930420397
Q1-23.1266505108797
median9.46480136203329
mean9.59109335162288e-17
Q321.4403049817275
maximum34.4391534657784

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 45 \tabularnewline
minimum & -65.6558930420397 \tabularnewline
Q1 & -23.1266505108797 \tabularnewline
median & 9.46480136203329 \tabularnewline
mean & 9.59109335162288e-17 \tabularnewline
Q3 & 21.4403049817275 \tabularnewline
maximum & 34.4391534657784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52338&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]45[/C][/ROW]
[ROW][C]minimum[/C][C]-65.6558930420397[/C][/ROW]
[ROW][C]Q1[/C][C]-23.1266505108797[/C][/ROW]
[ROW][C]median[/C][C]9.46480136203329[/C][/ROW]
[ROW][C]mean[/C][C]9.59109335162288e-17[/C][/ROW]
[ROW][C]Q3[/C][C]21.4403049817275[/C][/ROW]
[ROW][C]maximum[/C][C]34.4391534657784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52338&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52338&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]
# observations45
minimum-65.6558930420397
Q1-23.1266505108797
median9.46480136203329
mean9.59109335162288e-17
Q321.4403049817275
maximum34.4391534657784


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 10 ;
Parameters (R input):
par1 = 0 ; par2 = 10 ;
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')