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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 computationWed, 04 Nov 2009 09:11:12 -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/04/t1257354146j786lnk3wjowi4x.htm/, Retrieved Mon, 29 Apr 2024 08:46:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53724, Retrieved Mon, 29 Apr 2024 08:46:35 +0000
QR Codes:

Original text written by user:bivariate eda van de 2 uitgezuiverde reeksen x en y
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS5 et= c + b*e't...] [2009-11-04 16:11:12] [85defb7a20869746625978e6577e6e44] [Current]
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Dataseries X:
-15975.67604
-14514.8268
-12591.1438
-14717.13276
-7304.58168
-3366.39172
1869.75072
739.1108
9434.7392
6513.61384
4098.975
1722.70552
1246.28364
-1119.50704
1035.24612
1475.90432
1430.10088
2227.26764
3082.96116
2130.3416
2343.5122
2394.64196
1479.49948
2361.13668
2329.83848
4045.326
5874.74956
6620.93012
7590.9036
7364.18576
8324.84448
9076.68984
5808.96428
6877.20116
5692.935
2797.38888
1059.81904
-2037.97004
-4867.37424
-7569.57136
-6467.31848
-6381.37648
-7000.7376
-7183.33452
-6764.14456
-7865.50736
-7432.70284
-6092.07008
-4929.9784
-3041.54276
563.45944
2291.88628
4155.45556
3729.79628
2979.27116
3049.03092
2785.15356
3285.4484
3563.5296
2634.7742
1056.15632
2286.0812
1908.63672
-634.99884
-1767.1126
-1276.34392
-1126.308
-1312.72048
Dataseries Y:
-12011.80885
-10860.90867
-10228.25785
-12424.73337
-7256.044942
-2980.778143
1568.402868
2431.21277
8987.59798
7192.509546
4225.956625
1131.693238
389.361541
18.071624
1841.188503
3030.184708
2682.350922
4633.906141
433.775579
2660.61504
1231.438555
992.126599
-1180.079863
2276.504567
999.267362
1405.38915
1875.714789
2539.425603
4410.75159
6444.507944
6246.810012
6660.416446
552.610757
5091.606579
6322.305625
965.548122
448.773176
-4151.573701
-5533.456056
-7863.953584
-8428.502362
-10017.78131
-9519.20294
-7903.983213
-7442.716414
-10586.13198
-10721.66102
-7795.701652
-5291.51796
1982.943881
1849.243686
-8226.493693
-3433.050061
2997.316557
4610.970829
5846.987123
2276.469889
900.71921
1311.70974
3881.267605
6436.101008
12509.70403
3579.017518
-742.598421
7104.168935
2929.460802
5862.6908
10831.91509




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=53724&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=53724&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53724&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Model: Y[t] = c + b X[t] + e[t]
c0.0233454296212197
b0.852799047062178

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0233454296212197 \tabularnewline
b & 0.852799047062178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53724&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0233454296212197[/C][/ROW]
[ROW][C]b[/C][C]0.852799047062178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53724&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53724&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]
c0.0233454296212197
b0.852799047062178







Descriptive Statistics about e[t]
# observations68
minimum-10181.0354739885
Q1-1808.83214381397
median-269.273547023204
mean1.50206644508109e-15
Q31479.83916440833
maximum11951.3785189734

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 68 \tabularnewline
minimum & -10181.0354739885 \tabularnewline
Q1 & -1808.83214381397 \tabularnewline
median & -269.273547023204 \tabularnewline
mean & 1.50206644508109e-15 \tabularnewline
Q3 & 1479.83916440833 \tabularnewline
maximum & 11951.3785189734 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53724&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]68[/C][/ROW]
[ROW][C]minimum[/C][C]-10181.0354739885[/C][/ROW]
[ROW][C]Q1[/C][C]-1808.83214381397[/C][/ROW]
[ROW][C]median[/C][C]-269.273547023204[/C][/ROW]
[ROW][C]mean[/C][C]1.50206644508109e-15[/C][/ROW]
[ROW][C]Q3[/C][C]1479.83916440833[/C][/ROW]
[ROW][C]maximum[/C][C]11951.3785189734[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53724&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53724&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]
# observations68
minimum-10181.0354739885
Q1-1808.83214381397
median-269.273547023204
mean1.50206644508109e-15
Q31479.83916440833
maximum11951.3785189734



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')