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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 computationWed, 11 Nov 2009 08:34:06 -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/11/t12579537072l4tgwz023h4qvc.htm/, Retrieved Fri, 26 Apr 2024 15:00:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55696, Retrieved Fri, 26 Apr 2024 15:00:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsBouwvergunningen (BouwV) = x IndexBouwnijverheid (IndSI) = y
Estimated Impact232
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD    [Bivariate Explorative Data Analysis] [] [2009-11-11 15:34:06] [a4292616308a56e4faddaa97386e0403] [Current]
- R  D      [Bivariate Explorative Data Analysis] [] [2009-11-12 08:29:41] [639dd97b6eeebe46a3c92d62cb04fb95]
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Dataseries X:
100
108.1560276
114.0150276
102.1880309
110.3672031
96.8602511
94.1944583
99.51621961
94.06333487
97.5541476
78.15062422
81.2434643
92.36262465
96.06324371
114.0523777
110.6616666
104.9171949
90.00187193
95.7008067
86.02741157
84.85287668
100.04328
80.91713823
74.06539709
77.30281369
97.23043249
90.75515676
100.5614455
92.01293267
99.24012138
105.8672755
90.9920463
93.30624423
91.17419413
77.33295039
91.1277721
85.01249943
83.90390242
104.8626302
110.9039108
95.43714373
111.6238727
108.8925403
96.17511682
101.9740205
99.11953031
86.78158147
118.4195003
118.7441447
106.5296192
134.7772694
104.6778714
105.2954304
139.4139849
103.6060491
99.78182974
103.4610301
120.0594945
96.71377168
107.1308929
105.3608372
111.6942359
132.0519998
126.8037879
154.4824253
141.5570984
109.9506882
127.904198
133.0888617
120.0796299
117.5557142
143.0362309
159.982927
128.5991124
149.7373327
126.8169313
140.9639674
137.6691981
117.9402337
122.3095247
127.7804207
136.1677176
116.2405856
123.1576893
116.3400234
108.6119282
125.8982264
112.8003105
107.5182447
135.0955413
115.5096488
115.8640759
104.5883906
163.7213386
113.4482275
98.0428844
116.7868521
126.5330444
113.0336597
124.3392163
109.8298759
124.4434777
111.5039454
102.0350019
116.8726598
112.2073122
101.1513902
124.4255108
Dataseries Y:
100
99.94940551
102.0743739
102.0237794
102.6309132
102.8838857
103.0103719
104.3258285
105.211232
104.7305844
104.174045
103.6933974
104.3258285
105.211232
105.3124209
105.5400961
106.7037693
106.6025803
105.008854
104.3258285
104.174045
103.4151278
102.3273463
101.8214015
103.5669112
103.8957754
104.5788009
105.0341513
105.6665823
105.6918796
105.7171768
105.843663
105.7930686
105.3883127
105.9701493
106.5013913
107.1338224
109.3599798
109.3599798
108.4239818
107.9433342
108.0951176
108.3986845
110.5489502
111.8138123
112.5474323
111.6620288
111.3837592
113.1039717
115.1783456
121.0726031
123.0710853
123.3999494
122.9193018
122.3880597
123.5517329
124.9683784
124.8671895
123.2734632
121.9580066
122.4892487
125.6767012
126.7644827
126.4356185
125.3478371
126.0055654
127.4475082
130.5843663
133.0887933
133.3417657
132.8358209
133.7971161
136.6304073
138.8818619
140.6526689
143.9160132
149.0260562
149.3296231
152.6182646
161.5987857
162.6612699
166.1269922
165.9752087
165.4692639
166.9365039
167.4930433
169.2891475
170.2757399
171.5911966
171.3635214
171.641791
170.0986592
168.302555
168.9602833
170.0227675
167.5942322
172.6030863
175.082216
177.7637238
182.4943081
185.4793827
189.1474829
186.5924614
184.4927903
178.62383
170.5793069
166.7088287
163.3442955




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 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 & 20 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55696&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]20 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=55696&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55696&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 time20 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c44.213854718663
b0.783439682861554

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 44.213854718663 \tabularnewline
b & 0.783439682861554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55696&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]44.213854718663[/C][/ROW]
[ROW][C]b[/C][C]0.783439682861554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55696&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55696&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]
c44.213854718663
b0.783439682861554







Descriptive Statistics about e[t]
# observations108
minimum-39.8936799033788
Q1-17.0359043991053
median-6.1340407652553
mean1.41171153984816e-16
Q316.5888036741468
maximum60.3406660520229

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 108 \tabularnewline
minimum & -39.8936799033788 \tabularnewline
Q1 & -17.0359043991053 \tabularnewline
median & -6.1340407652553 \tabularnewline
mean & 1.41171153984816e-16 \tabularnewline
Q3 & 16.5888036741468 \tabularnewline
maximum & 60.3406660520229 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55696&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]108[/C][/ROW]
[ROW][C]minimum[/C][C]-39.8936799033788[/C][/ROW]
[ROW][C]Q1[/C][C]-17.0359043991053[/C][/ROW]
[ROW][C]median[/C][C]-6.1340407652553[/C][/ROW]
[ROW][C]mean[/C][C]1.41171153984816e-16[/C][/ROW]
[ROW][C]Q3[/C][C]16.5888036741468[/C][/ROW]
[ROW][C]maximum[/C][C]60.3406660520229[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55696&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55696&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]
# observations108
minimum-39.8936799033788
Q1-17.0359043991053
median-6.1340407652553
mean1.41171153984816e-16
Q316.5888036741468
maximum60.3406660520229



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')