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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 computationThu, 29 Oct 2009 10:59:59 -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/29/t1256835639scp5t7fcxnqr2xa.htm/, Retrieved Sun, 28 Apr 2024 23:28:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52020, Retrieved Sun, 28 Apr 2024 23:28:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [Workshop 5 correl...] [2009-10-29 15:05:45] [eaf42bcf5162b5692bb3c7f9d4636222]
- RMPD  [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-10-29 16:50:15] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D      [Bivariate Explorative Data Analysis] [workshop 5 verban...] [2009-10-29 16:59:59] [78d370e6d5f4594e9982a5085e7604c6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.628621083
0.318767883
0.041703886
0.02627228
0.328491871
0.820417862
0.510858263
0.25806906
0.615426657
0.87940785
0.84911425
0.900729052
0.213224654
0.308673849
0.627499448
0.366618647
0.109425439
-0.57940016
-0.314831766
-0.089969772
-0.409676171
-0.684373776
-0.656282179
-1.065988578
-1.075401378
-0.799218182
-0.650686183
-0.634209387
-0.532136596
-0.478760192
-0.523898198
-1.020374994
-1.009494193
-0.9356598
-1.1852194
-0.7958066
-0.072853008
0.61628378
0.758796971
1.122778165
1.290153351
2.031198541
1.788702938
2.838280126
3.422114519
3.52330651
3.008297715
3.074334111
2.332278908
0.755214912
0.243012909
-0.070069894
-0.464473899
-1.764491488
-1.78595949
-2.752876686
-3.476123879
-4.055830278
-3.158472681
-3.565536678
Dataseries Y:
Download CSV
Histogram 
0.3307415885252
0.0294054201834
-0.2973179466524
-0.2478797180063
-0.1770627958916
-0.0035735370933
0.0924179578814
0.0178051563753
0.2418561865275
0.1966390885407
0.1993114252243
0.1846135734646
0.1618987116543
0.2033199302497
0.2140092769839
0.2220262870347
0.2874985357822
0.2768091890479
0.3262474176940
0.3730133096566
0.4703409729730
0.3130983599102
0.0304685483534
-0.0722037883302
-0.0775484616973
-0.0428080848109
-0.0294464013930
-0.0973783611901
-0.1252252707336
-0.1559571425947
-0.0091912506322
0.1587407091649
0.0507236991142
-0.2931572305307
-0.5971657355561
-0.8918210621890
-1.0276849817832
-0.7288085244910
-0.5606639390598
-0.4058810370466
-0.3909705596529
-0.5094642908039
-0.6867494289936
-0.5918814767267
-0.6357624063717
-0.2555923058645
0.0989779705148
0.3350545157430
0.1537608725281
-0.0729624943077
-0.2529199691809
-0.0248604340034
0.4152246162502
0.5243651690087
0.6377268524266
0.6096673172491
0.4482035735269
0.4455312368433
0.5695822669955
0.6428589001598

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52020&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52020&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 time5 seconds
R Server'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c7.25022561962494e-12
b-0.108728115388346

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 7.25022561962494e-12 \tabularnewline
b & -0.108728115388346 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52020&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]7.25022561962494e-12[/C][/ROW]
[ROW][C]b[/C][C]-0.108728115388346[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52020&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]
c7.25022561962494e-12
b-0.108728115388346






Descriptive Statistics about e[t]
# observations60
minimum-1.03560615205066
Q1-0.21263328539519
median0.0468308889862633
mean-1.29218828924064e-17
Q30.284819613659866
maximum0.669321069698887

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.03560615205066 \tabularnewline
Q1 & -0.21263328539519 \tabularnewline
median & 0.0468308889862633 \tabularnewline
mean & -1.29218828924064e-17 \tabularnewline
Q3 & 0.284819613659866 \tabularnewline
maximum & 0.669321069698887 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52020&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]-1.03560615205066[/C][/ROW]
[ROW][C]Q1[/C][C]-0.21263328539519[/C][/ROW]
[ROW][C]median[/C][C]0.0468308889862633[/C][/ROW]
[ROW][C]mean[/C][C]-1.29218828924064e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.284819613659866[/C][/ROW]
[ROW][C]maximum[/C][C]0.669321069698887[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52020&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52020&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-1.03560615205066
Q1-0.21263328539519
median0.0468308889862633
mean-1.29218828924064e-17
Q30.284819613659866
maximum0.669321069698887


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')