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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 computationFri, 30 Oct 2009 05:59:44 -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/Oct/30/t1256904059kk5mlrat2ywaikd.htm/, Retrieved Mon, 29 Apr 2024 02:18:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52082, Retrieved Mon, 29 Apr 2024 02:18:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS 5 e(t) & e'(t)] [2009-10-30 11:59:44] [51d49d3536f6a59f2486a67bf50b2759] [Current]
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Dataseries X:
-8073.991497
-8361.352232
-8064.169708
-8021.760108
-7863.532168
-7780.59986
-8318.35137
-7932.439613
-8024.077152
-7828.308542
-7679.874077
-7749.626449
-7862.944357
-8165.629899
-8127.880115
-7976.35482
-8006.327368
-7969.509892
-8219.577584
-8294.102879
-8537.809836
-8012.988909
-8039.059189
-7918.60676
-8038.67704
-8360.315442
-8020.51938
-7938.856976
-8003.100291
-7776.621274
-7745.644413
-7715.575859
-7953.736106
-7636.418199
-7985.924668
-7977.633349
-8001.135506
-8539.912742
-8336.847638
-7333.285403
-7243.942631
-7198.326506
-7515.394197
-7775.304229
-7480.074565
-7422.529581
-7479.919493
-7894.269164
-8391.882703
-8288.146569
-8039.174021
-7569.078877
-7245.664964
-7293.278503
-7534.486753
-7338.437888
-7787.147432
-8697.766145
-9082.140681
-8610.956432
Dataseries Y:
461.0085031
-442.3522321
13.83029183
-667.7601076
-552.5321684
-692.5998601
-633.3513695
-395.4396126
-430.0771524
-32.30854178
158.1259228
400.3735508
493.0556435
-438.6298993
-19.88011491
-602.3548196
-371.3273681
-424.5098919
-157.5775837
-458.102879
-556.8098356
153.0110907
209.9408113
579.3932397
479.3229603
-649.315442
203.4806202
-780.856976
-201.1002914
23.37872603
-161.6444129
-162.5758586
25.26389388
570.5818013
105.0753323
421.3666506
553.8644943
-1016.912742
-164.8476375
-547.2854028
-107.9426315
-132.3265055
290.6058027
-139.3042291
172.9254352
746.4704192
650.0805075
422.7308358
925.1172975
510.8534308
912.8259792
-81.07887749
363.3350358
298.7214974
-38.48675301
380.5621124
16.85256824
388.2338547
-192.1406809
321.043568




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52082&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52082&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52082&T=0

As an alternative you can also use a 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'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c1935.52060047315
b0.243931675550217

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1935.52060047315 \tabularnewline
b & 0.243931675550217 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52082&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1935.52060047315[/C][/ROW]
[ROW][C]b[/C][C]0.243931675550217[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52082&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52082&T=1

As an alternative you can also use a QR Code:  

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

Model: Y[t] = c + b X[t] + e[t]
c1935.52060047315
b0.243931675550217







Descriptive Statistics about e[t]
# observations60
minimum-869.278118264435
Q1-357.995605773207
median6.03454139161874
mean-1.62101813453811e-14
Q3369.642371126226
maximum1036.64270579053

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -869.278118264435 \tabularnewline
Q1 & -357.995605773207 \tabularnewline
median & 6.03454139161874 \tabularnewline
mean & -1.62101813453811e-14 \tabularnewline
Q3 & 369.642371126226 \tabularnewline
maximum & 1036.64270579053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52082&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-869.278118264435[/C][/ROW]
[ROW][C]Q1[/C][C]-357.995605773207[/C][/ROW]
[ROW][C]median[/C][C]6.03454139161874[/C][/ROW]
[ROW][C]mean[/C][C]-1.62101813453811e-14[/C][/ROW]
[ROW][C]Q3[/C][C]369.642371126226[/C][/ROW]
[ROW][C]maximum[/C][C]1036.64270579053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52082&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52082&T=2

As an alternative you can also use a QR Code:  

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

Descriptive Statistics about e[t]
# observations60
minimum-869.278118264435
Q1-357.995605773207
median6.03454139161874
mean-1.62101813453811e-14
Q3369.642371126226
maximum1036.64270579053



Parameters (Session):
par1 = 0 ; par2 = 36 ;
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')