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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, 04 Nov 2009 08:15:48 -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/04/t1257347837o889dbkx6iwy8ma.htm/, Retrieved Mon, 29 Apr 2024 14:40:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53629, Retrieved Mon, 29 Apr 2024 14:40:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 5 Part 3: Bivariate EDA met e[t] en e[t]'
Estimated Impact144

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] [shw-ws5p3] [2009-11-04 15:15:48] [5b5bced41faf164488f2c271c918b21f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-7,384479833
-348,812296
656,3387963
168,4268193
163,9341261
-219,1238071
131,7351533
68,87952107
-499,4813227
88,460018
-3,676899151
-250,2346886
174,1014888
-231,4249098
544,4571966
124,3024887
245,2234366
98,23681742
372,6587033
36,0872455
-337,1878898
-72,72145156
-121,8431801
-137,6524521
19,966092
-447,5428034
769,4438158
243,4453361
-164,2602175
454,3943467
-69,44942508
405,8522526
-358,8682021
-83,29905889
50,36917358
-94,12503992
-307,9726466
-171,4972374
581,7501227
244,4978459
74,07234434
218,1732414
41,97296758
230,9245802
-379,8087485
-230,0475763
-14,66583292
-134,2125562
-277,3250263
-389,3945325
682,2209027
-261,6970045
148,0023313
158,047103
-258,1716876
153,2005099
-667,3263955
-162,5924918
-58,96570282
-588,4092144
Dataseries Y:
Download CSV
Histogram 
-65394,81482
-73603,50368
-78450,88979
-90778,88555
-108938,6215
-115307,0815
-47777,9916
-52962,36932
-42626,41087
-35826,22462
-37255,50152
-35506,88014
-23495,07045
-31691,22561
-40467,17858
-45410,6674
-65784,05152
-61264,6355
3833,982718
2529,025341
11020,79232
10104,45451
716,0311004
5905,134813
17951,92739
10453,82142
6526,405403
-14837,31986
-29564,60018
-25387,19272
19927,57084
39008,04039
44293,06931
55500,83098
46906,81719
46191,80647
46541,09958
41423,38188
35868,26637
14705,82773
1496,334583
1543,996595
46668,94731
56384,43289
57551,80404
57298,34864
48115,71879
47808,56048
49603,91991
43001,48136
29209,15725
16457,09084
6759,137791
540,7772771
46990,1623
51925,58688
43201,67348
33171,62779
19015,68671
6178,38612

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=53629&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=53629&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53629&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]
c9.36763907842975e-07
b-28.7729874123560

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 9.36763907842975e-07 \tabularnewline
b & -28.7729874123560 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53629&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]9.36763907842975e-07[/C][/ROW]
[ROW][C]b[/C][C]-28.7729874123560[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53629&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53629&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]
c9.36763907842975e-07
b-28.7729874123560






Descriptive Statistics about e[t]
# observations60
minimum-121611.928044373
Q1-35058.4672370426
median7916.76681064873
mean3.36009738551487e-12
Q338150.302766699
maximum63028.8229283614

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -121611.928044373 \tabularnewline
Q1 & -35058.4672370426 \tabularnewline
median & 7916.76681064873 \tabularnewline
mean & 3.36009738551487e-12 \tabularnewline
Q3 & 38150.302766699 \tabularnewline
maximum & 63028.8229283614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53629&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]-121611.928044373[/C][/ROW]
[ROW][C]Q1[/C][C]-35058.4672370426[/C][/ROW]
[ROW][C]median[/C][C]7916.76681064873[/C][/ROW]
[ROW][C]mean[/C][C]3.36009738551487e-12[/C][/ROW]
[ROW][C]Q3[/C][C]38150.302766699[/C][/ROW]
[ROW][C]maximum[/C][C]63028.8229283614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53629&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53629&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-121611.928044373
Q1-35058.4672370426
median7916.76681064873
mean3.36009738551487e-12
Q338150.302766699
maximum63028.8229283614


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')