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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, 28 Oct 2009 10:44:36 -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/28/t1256748520tcjg5rmycynfc25.htm/, Retrieved Mon, 06 May 2024 04:05:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51547, Retrieved Mon, 06 May 2024 04:05:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws4v2
Estimated Impact137

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]
- RMPD  [Bivariate Explorative Data Analysis] [] [2009-10-28 15:16:32] [5482608004c1d7bbf873930172393a2d]
-    D      [Bivariate Explorative Data Analysis] [] [2009-10-28 16:44:36] [efdfe680cd785c4af09f858b30f777ec] [Current]
- RMPD        [Trivariate Scatterplots] [] [2009-11-03 17:57:36] [5482608004c1d7bbf873930172393a2d]
- RMPD          [Bivariate Explorative Data Analysis] [] [2009-11-03 18:16:45] [5482608004c1d7bbf873930172393a2d]
-                 [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 10:51:00] [aba88da643e3763d32ff92bd8f92a385]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 10:53:38] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D            [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-11-04 10:53:21] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 10:55:14] [b03a417d80508f12cef0f78b0fc3a1dd]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 10:55:14] [aba88da643e3763d32ff92bd8f92a385]
- RMPD          [Bivariate Explorative Data Analysis] [] [2009-11-03 18:19:20] [5482608004c1d7bbf873930172393a2d]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 10:59:12] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D            [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-11-04 10:59:07] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 10:59:59] [aba88da643e3763d32ff92bd8f92a385]
- RMPD          [Bivariate Explorative Data Analysis] [] [2009-11-03 18:33:00] [5482608004c1d7bbf873930172393a2d]
-    D            [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-11-04 11:34:19] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-04 11:34:29] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D            [Bivariate Explorative Data Analysis] [Workshop 5, Bivar...] [2009-11-04 11:44:07] [aba88da643e3763d32ff92bd8f92a385]
-   PD          [Trivariate Scatterplots] [workshop 5 totale...] [2009-11-04 10:34:43] [af8eb90b4bf1bcfcc4325c143dbee260]
-   PD          [Trivariate Scatterplots] [Workshop 5 Trivia...] [2009-11-04 10:33:16] [b6394cb5c2dcec6d17418d3cdf42d699]
-   PD          [Trivariate Scatterplots] [Workshop 5, Triva...] [2009-11-04 10:37:52] [aba88da643e3763d32ff92bd8f92a385]
- RMPD        [Partial Correlation] [] [2009-11-03 18:08:02] [5482608004c1d7bbf873930172393a2d]
-    D          [Partial Correlation] [Workshop 5, Parti...] [2009-11-04 10:44:56] [aba88da643e3763d32ff92bd8f92a385]
-    D          [Partial Correlation] [Workshop 5 Partia...] [2009-11-04 10:47:33] [b6394cb5c2dcec6d17418d3cdf42d699]
F    D          [Partial Correlation] [workshop 5 partia...] [2009-11-04 10:47:06] [af8eb90b4bf1bcfcc4325c143dbee260]
-    D          [Partial Correlation] [WS5 Partial Corre...] [2009-11-04 16:44:56] [1b4c3bbe3f2ba180dd536c5a6a81a8e6]
- RMPD          [Bivariate Explorative Data Analysis] [WS5 Bivariate EDA...] [2009-11-04 17:16:47] [1b4c3bbe3f2ba180dd536c5a6a81a8e6]
- RMPD          [Bivariate Explorative Data Analysis] [WS5 Bivariate EDA...] [2009-11-04 17:21:54] [1b4c3bbe3f2ba180dd536c5a6a81a8e6]
- RMPD          [Bivariate Explorative Data Analysis] [WS5 Bivariate EDA...] [2009-11-04 17:21:54] [1b4c3bbe3f2ba180dd536c5a6a81a8e6]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2534
2605
2682
2755
2760
2735
2659
2654
2670
2785
2845
2723
2746
2767
2940
2977
2993
2892
2824
2771
2686
2738
2723
2731
2632
2606
2605
2646
2627
2535
2456
2404
2319
2519
2504
2382
2394
2381
2501
2532
2515
2429
2389
2261
2272
2439
2373
2327
2364
2388
2553
2663
2694
2679
2611
2580
2627
2732
2707
2633
Dataseries Y:
Download CSV
Histogram 
6675
6539
6699
6962
6981
7024
6940
6774
6671
6965
6969
6822
6878
6691
6837
7018
7167
7076
7171
7093
6971
7142
7047
6999
6650
6475
6437
6639
6422
6272
6232
6003
5673
6050
5977
5796
5752
5609
5839
6069
6006
5809
5797
5502
5568
5864
5764
5615
5615
5681
5915
6334
6494
6620
6578
6495
6538
6737
6651
6530

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=51547&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=51547&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51547&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-631.220492112644
b2.70966569223487

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -631.220492112644 \tabularnewline
b & 2.70966569223487 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51547&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-631.220492112644[/C][/ROW]
[ROW][C]b[/C][C]2.70966569223487[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51547&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51547&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-631.220492112644
b2.70966569223487






Descriptive Statistics about e[t]
# observations60
minimum-498.196643057866
Q1-142.274952401133
median15.0235578304008
mean-1.76888596363038e-14
Q3129.454427890291
maximum439.927627989468

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -498.196643057866 \tabularnewline
Q1 & -142.274952401133 \tabularnewline
median & 15.0235578304008 \tabularnewline
mean & -1.76888596363038e-14 \tabularnewline
Q3 & 129.454427890291 \tabularnewline
maximum & 439.927627989468 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51547&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]-498.196643057866[/C][/ROW]
[ROW][C]Q1[/C][C]-142.274952401133[/C][/ROW]
[ROW][C]median[/C][C]15.0235578304008[/C][/ROW]
[ROW][C]mean[/C][C]-1.76888596363038e-14[/C][/ROW]
[ROW][C]Q3[/C][C]129.454427890291[/C][/ROW]
[ROW][C]maximum[/C][C]439.927627989468[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51547&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51547&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-498.196643057866
Q1-142.274952401133
median15.0235578304008
mean-1.76888596363038e-14
Q3129.454427890291
maximum439.927627989468


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')