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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 08:57:24 -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/t1256741909fuedng62c2jhhsh.htm/, Retrieved Mon, 06 May 2024 03:19:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51381, Retrieved Mon, 06 May 2024 03:19:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsln Y[t] = c + b ln X[t] + e[t] cvm
Estimated Impact118

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] [Workshop 4: Part ...] [2009-10-28 14:53:34] [03d5b865e91ca35b5a5d21b8d6da5aba]
-    D    [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 14:57:24] [a5ada8bd39e806b5b90f09589c89554a] [Current]
-    D      [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 15:10:24] [03d5b865e91ca35b5a5d21b8d6da5aba]
-    D      [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 15:14:02] [03d5b865e91ca35b5a5d21b8d6da5aba]
-    D        [Bivariate Explorative Data Analysis] [Workshop 4: Part ...] [2009-10-28 15:21:40] [03d5b865e91ca35b5a5d21b8d6da5aba]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519,8622445
535,3388599
601,2979826
589,7562418
571,7244696
569,2697397
547,4548004
551,5261802
578,9954301
567,0140671
553,7261802
591,518182
506,3011098
533,0479684
598,9424426
573,1043459
588,2562418
570,4333307
553,4215901
565,5498382
595,5161661
560,200865
581,5291007
594,0562418
506,0805807
540,2180184
590,1165031
596,0964686
581,9551603
558,1387446
562,1387446
559,8944185
586,7789998
555,0362368
563,3751829
587,7759383
522,0173321
547,9559209
580,9413968
610,9060133
582,2020143
547,1117561
568,3633973
570,1262601
568,9688714
591,8880552
565,918767
575,897135
543,1117561
526,5163276
588,5787988
583,5244696
535,9474061
526,3459532
508,4268452
525,4542799
553,1177226
532,6388599
528,5480492
558,1548364
490,4666761
Dataseries Y:
Download CSV
Histogram 
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102
106
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100
110,7
112,8
109,8
117,3
109,1
115,9
96
99,8
116,8
115,7
99,4
94,3
91
93,2
103,1
94,1
91,8
102,7
82,6

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51381&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51381&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c-80.0272799495916
b0.328732662006928

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -80.0272799495916 \tabularnewline
b & 0.328732662006928 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51381&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-80.0272799495916[/C][/ROW]
[ROW][C]b[/C][C]0.328732662006928[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51381&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-80.0272799495916
b0.328732662006928






Descriptive Statistics about e[t]
# observations61
minimum-5.6074290770275
Q1-3.42904166044200
median0.497002320074879
mean7.96408704011975e-17
Q32.78862825519221
maximum6.74416598753193

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -5.6074290770275 \tabularnewline
Q1 & -3.42904166044200 \tabularnewline
median & 0.497002320074879 \tabularnewline
mean & 7.96408704011975e-17 \tabularnewline
Q3 & 2.78862825519221 \tabularnewline
maximum & 6.74416598753193 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51381&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]-5.6074290770275[/C][/ROW]
[ROW][C]Q1[/C][C]-3.42904166044200[/C][/ROW]
[ROW][C]median[/C][C]0.497002320074879[/C][/ROW]
[ROW][C]mean[/C][C]7.96408704011975e-17[/C][/ROW]
[ROW][C]Q3[/C][C]2.78862825519221[/C][/ROW]
[ROW][C]maximum[/C][C]6.74416598753193[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51381&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51381&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-5.6074290770275
Q1-3.42904166044200
median0.497002320074879
mean7.96408704011975e-17
Q32.78862825519221
maximum6.74416598753193


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')