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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 computationWed, 04 Nov 2009 10:53:08 -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/t12573572640l6medru0vx1c2i.htm/, Retrieved Mon, 29 Apr 2024 15:24:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53765, Retrieved Mon, 29 Apr 2024 15:24:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [WS5.5] [2009-11-04 17:53:08] [dd4f17965cad1d38de7a1c062d32d75d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-14592,498
-14749,83
-11156,16
-17184,822
-16545,82
-17444,154
-17099,494
-15654,83
-11063,164
-13154,828
-13161,16
-13948,494
-10852,162
-9392,162
-4035,162
-9891,16
-9131,16
-10197,824
-11863,16
-11729,16
-7285,494
-8177,828
-7750,828
-9981,496
-7517,164
-6005,498
-1075,498
-5927,498
-4997,496
-6932,492
-10592,156
-10866,154
-6412,488
-7672,156
-6610,49
-7920,824
-6428,158
-5585,824
-133,156
-3363,49
-2202,822
-2256,486
-3363,488
-3620,154
783,514
-1380,152
-1259,818
-3304,82
-347,822
1289,178
6757,514
1001,516
745,518
1461,516
2010,842
3153,508
11929,844
14782,516
15136,518
22871,182
32275,176
36322,172
44015,504
41091,172
40859,174
41557,84
41163,17
42609,836
Dataseries Y:
Download CSV
Histogram 
-9879,41
-10788,3
-17642,546
-14437,08
-15375,902
-10005,122
-9551,41
-7988,232
-13723,944
-17598,3
-15783,122
-11085,766
-11790,766
-8022,766
-13348,3
-13524,3
-12618,012
-8935,3
-9100,3
-10968,122
-10056,944
-10411,944
-10946,588
-5283,232
-5128,054
-2249,054
-4387,054
-8762,588
-11380,656
-13290,368
-11371,902
-10899,724
-12171,368
-10352,19
-12691,012
-9346,834
-7929,012
-2859,368
-5897,19
-4573,546
-3579,258
-4843,724
-3116,902
4224,742
-2958,436
940,386
-455,08
3108,454
5254,454
3068,742
1027,208
1686,674
2374,208
5331,166
6855,344
10646,632
18059,208
20561,674
23339,386
38642,988
44831,056
40739,412
42120,056
37655,522
40053,7
41048,59
45168,768
-311562,65

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'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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53765&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53765&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'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c-4440.1897359632
b0.232772077128228

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -4440.1897359632 \tabularnewline
b & 0.232772077128228 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53765&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-4440.1897359632[/C][/ROW]
[ROW][C]b[/C][C]0.232772077128228[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53765&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-4440.1897359632
b0.232772077128228






Descriptive Statistics about e[t]
# observations68
minimum-317040.84029585
Q1-4211.1409595614
median-517.485247831313
mean3.18072365831433e-13
Q37486.11370931091
maximum41758.4859787641

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 68 \tabularnewline
minimum & -317040.84029585 \tabularnewline
Q1 & -4211.1409595614 \tabularnewline
median & -517.485247831313 \tabularnewline
mean & 3.18072365831433e-13 \tabularnewline
Q3 & 7486.11370931091 \tabularnewline
maximum & 41758.4859787641 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53765&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]-317040.84029585[/C][/ROW]
[ROW][C]Q1[/C][C]-4211.1409595614[/C][/ROW]
[ROW][C]median[/C][C]-517.485247831313[/C][/ROW]
[ROW][C]mean[/C][C]3.18072365831433e-13[/C][/ROW]
[ROW][C]Q3[/C][C]7486.11370931091[/C][/ROW]
[ROW][C]maximum[/C][C]41758.4859787641[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53765&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53765&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]
# observations68
minimum-317040.84029585
Q1-4211.1409595614
median-517.485247831313
mean3.18072365831433e-13
Q37486.11370931091
maximum41758.4859787641


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')