Free Statistics

of Irreproducible Research!

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 computationFri, 30 Oct 2009 05:36:57 -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/30/t125690286632mnlsu4ww06ee7.htm/, Retrieved Mon, 29 Apr 2024 02:02:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52077, Retrieved Mon, 29 Apr 2024 02:02:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS 5 b&c berekenen] [2009-10-30 11:36:57] [51d49d3536f6a59f2486a67bf50b2759] [Current]
-  M D    [Bivariate Explorative Data Analysis] [BBWS5-2] [2009-11-02 10:24:01] [408e92805dcb18620260f240a7fb9d53]
-  M D    [Bivariate Explorative Data Analysis] [BBWS5-3] [2009-11-02 10:27:45] [408e92805dcb18620260f240a7fb9d53]
-    D      [Bivariate Explorative Data Analysis] [BBWS5-4] [2009-11-02 10:33:15] [408e92805dcb18620260f240a7fb9d53]
Feedback Forum

Post a new message
Dataseries X:
498
350
314
288
254
229
306
170
230
440
305
426
412
602
613
482
241
277
252
383
506
366
473
581
688
792
761
592
251
162
183
164
223
237
567
778
888
1118
1275
419
324
197
172
220
98
122
303
750
745
293
534
318
72
67
256
82
337
596
1152
1028
Dataseries Y:
10436
9314
9717
8997
9062
8885
9058
9095
9149
9857
9848
10269
10341
9690
10125
9349
9224
9224
9454
9347
9430
9933
10148
10677
10735
9760
10567
9333
9409
9502
9348
9319
9594
10160
10182
10810
11105
9874
10958
9311
9610
9398
9784
9425
9557
10166
10337
10770
11265
10183
10941
9628
9709
9637
9579
9741
9754
10508
10749
11079




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52077&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52077&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52077&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c9239.29991647172
b1.47729233024209

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 9239.29991647172 \tabularnewline
b & 1.47729233024209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52077&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]9239.29991647172[/C][/ROW]
[ROW][C]b[/C][C]1.47729233024209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52077&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52077&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]
c9239.29991647172
b1.47729233024209







Descriptive Statistics about e[t]
# observations60
minimum-1016.91274168238
Q1-402.707182446853
median-3.02491153892963
mean-2.78767749624838e-14
Q3382.480048012318
maximum925.117297497923

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1016.91274168238 \tabularnewline
Q1 & -402.707182446853 \tabularnewline
median & -3.02491153892963 \tabularnewline
mean & -2.78767749624838e-14 \tabularnewline
Q3 & 382.480048012318 \tabularnewline
maximum & 925.117297497923 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52077&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]-1016.91274168238[/C][/ROW]
[ROW][C]Q1[/C][C]-402.707182446853[/C][/ROW]
[ROW][C]median[/C][C]-3.02491153892963[/C][/ROW]
[ROW][C]mean[/C][C]-2.78767749624838e-14[/C][/ROW]
[ROW][C]Q3[/C][C]382.480048012318[/C][/ROW]
[ROW][C]maximum[/C][C]925.117297497923[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52077&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52077&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-1016.91274168238
Q1-402.707182446853
median-3.02491153892963
mean-2.78767749624838e-14
Q3382.480048012318
maximum925.117297497923



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')