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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 computationMon, 02 Nov 2009 07:58:53 -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/02/t1257174005jzrvoge2iozk4td.htm/, Retrieved Sat, 04 May 2024 03:40:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52695, Retrieved Sat, 04 May 2024 03:40:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-   PD  [Bivariate Data Series] [Reproduction Part 1] [2009-10-26 18:51:43] [96e597a9107bfe8c07649cce3d4f6fec]
- RMPD    [Bivariate Explorative Data Analysis] [JJ Workshop 4, De...] [2009-10-26 19:42:48] [96e597a9107bfe8c07649cce3d4f6fec]
-    D      [Bivariate Explorative Data Analysis] [JJ Workshop 4, de...] [2009-10-27 18:56:34] [96e597a9107bfe8c07649cce3d4f6fec]
- RM D        [Bivariate Explorative Data Analysis] [JJ Workshop 5, mo...] [2009-11-02 13:36:21] [96e597a9107bfe8c07649cce3d4f6fec]
-    D            [Bivariate Explorative Data Analysis] [JJ Workshop 5, mo...] [2009-11-02 14:58:53] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-11.152
-1.5796
13.16
11.1072
-5.6192
-3.8776
13.7234
7.109
10.9492
7.6378
2.6788
2.4724
-10.7344
0.574
15.1298
4.6936
-11.3734
-18.5268
1.4216
-4.6246
-4.2308
8.5854
-2.922
0.5006
-9.2324
0.2036
5.65
4.1602
-15.015
-20.315
2.9446
-6.449
-7.137
3.139
-9.8002
-4.357
-6.117
0.6406
0.589
2.3694
-15.0224
-19.9452
6.3754
-5.8596
-3.3378
-1.0326
-4.4502
-4.275
-3.768
11.3846
18.4804
18.5824
-4.7104
-2.5836
5.172
4.139
9.136
15.4814
1.9896
2.7668
Dataseries Y:
Download CSV
Histogram 
-1911,724
-1092,9502
2107,62
1781,9164
-2191,0104
-3196,1112
1042,9483
-510,7845
1350,1454
-310,0889
528,2906
213,2038
-1599,2628
1127,863
3179,2851
938,3232
-867,7033
-3318,9066
1899,2492
-28,0477
-706,9446
2361,3973
-531,939
-326,1803
-1150,7638
1250,9782
2070,885
1756,2899
-1364,0325
-4171,1225
1808,3077
598,8945
-1071,6315
2335,7905
-846,1699
-1114,4615
-301,8415
1165,2397
581,1755
2189,5053
-1432,1288
-3959,7774
2481,9723
-904,7102
-68,7611
292,8563
-1419,0249
-1625,1425
-95,996
360,3377
1786,0998
2683,3188
-953,3848
-2681,8982
2139,734
-776,0495
258,852
2343,5493
-914,6248
-1193,5834

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=52695&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=52695&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52695&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]
c12.7660106843016
b150.694009225267

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 12.7660106843016 \tabularnewline
b & 150.694009225267 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52695&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]12.7660106843016[/C][/ROW]
[ROW][C]b[/C][C]150.694009225267[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52695&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52695&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]
c12.7660106843016
b150.694009225267






Descriptive Statistics about e[t]
# observations60
minimum-2624.54612051240
Q1-892.490279755175
median1.70500841952589
mean-7.105427357601e-14
Q3846.54345983704
maximum1849.99599435758

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -2624.54612051240 \tabularnewline
Q1 & -892.490279755175 \tabularnewline
median & 1.70500841952589 \tabularnewline
mean & -7.105427357601e-14 \tabularnewline
Q3 & 846.54345983704 \tabularnewline
maximum & 1849.99599435758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52695&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]-2624.54612051240[/C][/ROW]
[ROW][C]Q1[/C][C]-892.490279755175[/C][/ROW]
[ROW][C]median[/C][C]1.70500841952589[/C][/ROW]
[ROW][C]mean[/C][C]-7.105427357601e-14[/C][/ROW]
[ROW][C]Q3[/C][C]846.54345983704[/C][/ROW]
[ROW][C]maximum[/C][C]1849.99599435758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52695&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52695&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]
# observations60
minimum-2624.54612051240
Q1-892.490279755175
median1.70500841952589
mean-7.105427357601e-14
Q3846.54345983704
maximum1849.99599435758


Figures (Output of Computation)

Input Parameters & R Code

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')