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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 13:26:56 -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/t1257193725m58enqynaznlj77.htm/, Retrieved Sat, 04 May 2024 00:42:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52958, Retrieved Sat, 04 May 2024 00:42:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [SHW WS5 - Part 1 ...] [2009-10-29 18:22:35] [253127ae8da904b75450fbd69fe4eb21]
- RMPD    [Bivariate Explorative Data Analysis] [2 nieuwe variabelen] [2009-11-02 20:26:56] [026d431dc78a3ce53a040b5408fc0322] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-23,9125
-25,46833
-22,30836
-2,6604
-53,03698
-30,39631
-13,78842
-11,72506
-16,89164
4,05628
-46,69887
-41,29661
-25,94771
-18,74161
-16,66795
4,17272
-46,44067
-24,71058
-1,32472
-3,47795
-6,62619
4,08012
-38,81779
-30,3736
-5,99318
-14,48936
-1,46121
18,00198
-44,69371
-13,62779
15,38701
13,18509
11,69486
32,09375
-13,63824
-2,95771
14,76756
10,57155
30,94711
36,49473
-20,827
2,69198
27,69919
33,71066
30,38377
30,0553
-2,62346
19,47366
14,04519
28,61079
28,17846
48,44054
-11,52026
7,93263
43,95355
38,95402
29,191
42,95308
-13,35067
-1,23265
26,20273
Dataseries Y:
Download CSV
Histogram 
-27,765
-44,2735
-56,372
-24,67
-65,041
-67,4745
-28,269
-40,537
-48,908
31,796
-59,3465
-52,2595
-5,6045
-16,8095
-30,0925
-2,226
-78,7565
-26,061
-17,154
-27,6925
-14,6805
73,904
-44,3005
-21,71
3,969
-30,922
-0,3295
16,311
-26,0045
-19,1005
-6,7405
-7,8445
45,067
49,2225
-30,578
15,9955
38,132
-16,6675
12,4545
32,1735
-42,34
-1,289
25,6505
-0,123
26,2215
174,745
12,783
22,027
42,1505
25,7705
60,387
35,083
-19,177
10,3785
29,2325
26,409
28,46
149,656
-1,2565
-10,5575
24,6735

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=52958&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=52958&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52958&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]
c-0.0090458350390596
b1.34176958369852

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.0090458350390596 \tabularnewline
b & 1.34176958369852 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52958&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.0090458350390596[/C][/ROW]
[ROW][C]b[/C][C]1.34176958369852[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52958&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52958&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-0.0090458350390596
b1.34176958369852






Descriptive Statistics about e[t]
# observations61
minimum-45.3458923993631
Q1-16.4347757123808
median-7.71890583235328
mean-4.03792436645815e-16
Q38.34646808257899
maximum134.426758466105

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -45.3458923993631 \tabularnewline
Q1 & -16.4347757123808 \tabularnewline
median & -7.71890583235328 \tabularnewline
mean & -4.03792436645815e-16 \tabularnewline
Q3 & 8.34646808257899 \tabularnewline
maximum & 134.426758466105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52958&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-45.3458923993631[/C][/ROW]
[ROW][C]Q1[/C][C]-16.4347757123808[/C][/ROW]
[ROW][C]median[/C][C]-7.71890583235328[/C][/ROW]
[ROW][C]mean[/C][C]-4.03792436645815e-16[/C][/ROW]
[ROW][C]Q3[/C][C]8.34646808257899[/C][/ROW]
[ROW][C]maximum[/C][C]134.426758466105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52958&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52958&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]
# observations61
minimum-45.3458923993631
Q1-16.4347757123808
median-7.71890583235328
mean-4.03792436645815e-16
Q38.34646808257899
maximum134.426758466105


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')