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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 06:38:06 -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/t1257169226e4cr2kv05yvlz6e.htm/, Retrieved Fri, 03 May 2024 19:25:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52608, Retrieved Fri, 03 May 2024 19:25:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [bivar EDA Xt = pr...] [2009-11-02 13:38:06] [b08f24ccf7d7e0757793cda532be96b3] [Current]
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Dataseries X:
88.7233
91.9441
87.6443
92.3349
86.7446
90.4944
90.0456
90.2818
95.7701
94.2684
92.6972
88.3027
92.262
95.3634
97.9526
95.5567
94.2145
94.6263
90.8046
91.1568
90.99
93.2625
92.6989
87.1384
94.8365
99.3737
98.8442
98.1394
96.5231
99.9541
92.8272
96.4591
99.2824
97.5254
98.1819
97.8293
99.0573
105.7607
105.4583
107.8701
107.5543
104.2246
101.322
100.3369
106.9387
108.0687
106.1259
105.9
109.7624
111.8431
110.758
108.6872
106.4739
105.1487
98.9033
101.3615
107.2762
104.6946
106.2082
101.3239
Dataseries Y:
82.3975
86.3819
86.1038
84.5059
82.7593
83.6718
74.8676
77.8998
81.6094
80.2569
78.934
76.8461
76.4379
83.14
84.6699
83.9001
84.4128
84.5982
76.5504
77.3826
80.4645
81.7259
81.1172
79.0921
82.5387
87.1251
89.2859
88.3042
89.4752
88.2355
81.8561
83.0776
87.1477
90.7124
89.762
88.3862
91.2844
94.0694
97.8276
96.8148
97.3319
98.5312
91.1703
91.3694
95.5428
97.6763
97.7141
96.3445
100.025
102.3597
105.204
102.4316
103.4731
104.1694
93.5787
99.1232
103.4544
105.7473
104.2672
103.1026




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52608&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52608&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52608&T=0

As an alternative you can also use a 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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Model: Y[t] = c + b X[t] + e[t]
c-25.3749582172528
b1.16671365917085

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -25.3749582172528 \tabularnewline
b & 1.16671365917085 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52608&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-25.3749582172528[/C][/ROW]
[ROW][C]b[/C][C]1.16671365917085[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52608&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52608&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c-25.3749582172528
b1.16671365917085







Descriptive Statistics about e[t]
# observations60
minimum-5.83047740516828
Q1-3.01400920755333
median-0.766193459480085
mean-1.74238517132904e-16
Q32.30382988477252
maximum10.2615800867914

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -5.83047740516828 \tabularnewline
Q1 & -3.01400920755333 \tabularnewline
median & -0.766193459480085 \tabularnewline
mean & -1.74238517132904e-16 \tabularnewline
Q3 & 2.30382988477252 \tabularnewline
maximum & 10.2615800867914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52608&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]-5.83047740516828[/C][/ROW]
[ROW][C]Q1[/C][C]-3.01400920755333[/C][/ROW]
[ROW][C]median[/C][C]-0.766193459480085[/C][/ROW]
[ROW][C]mean[/C][C]-1.74238517132904e-16[/C][/ROW]
[ROW][C]Q3[/C][C]2.30382988477252[/C][/ROW]
[ROW][C]maximum[/C][C]10.2615800867914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52608&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52608&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations60
minimum-5.83047740516828
Q1-3.01400920755333
median-0.766193459480085
mean-1.74238517132904e-16
Q32.30382988477252
maximum10.2615800867914



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')