FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 10:34:20 -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/t12567479865x50twq77m5tn46.htm/, Retrieved Mon, 06 May 2024 09:41:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51531, Retrieved Mon, 06 May 2024 09:41:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Explorative Data Analysis] [WS bivariate EDA ...] [2009-10-28 16:34:20] [557d56ec4b06cd0135c259898de8ce95] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98101950,13
187968318,5
188999043,8
210743289
230609073,9
130468610,9
190983186,8
162537001
262991089
175244644
153536881
218451087,3
116973495,2
218177896,1
139972561
142356218
112613295,5
253547719,2
123096251,3
262749137,1
102010000
147614906,3
135590955,4
85561526,32
80654369,49
104950319,4
155190863,4
177088669,1
117497470,1
139892713,1
119376190,6
113962030,1
86439787,29
108851881,9
150342218,5
119054770,4
87131416,39
135840396,2
122766400
96828411,45
55486359,51
69933078,76
71667060,61
67583576,24
108844643,7
72887198,76
72854150,57
63959435
39707815,79
57692632,99
51846967,98
37853044,1
36775240,36
52851578,19
43275872,83
59417285,63
40974770,56
49590376,35
68830403,8
92416177,78
Dataseries Y:
Download CSV
Histogram 
10284,5
12792
12823,61538
13845,66667
15335,63636
11188,5
13633,25
12298,46667
15353,63636
12696,15385
12213,93333
13683,72727
11214,14286
13950,23077
11179,13333
11801,875
11188,82353
16456,27273
11110,0625
16530,69231
10038,41176
11681,25
11148,88235
8631
9386,444444
9764,736842
12043,75
12948,06667
10987,125
11648,3125
10633,35294
10219,3
9037,6
10296,31579
11705,41176
10681,94444
9362,947368
11306,35294
10984,45
10062,61905
8118,583333
8867,48
8346,72
8529,307692
10697,18182
8591,84
8695,607143
8125,571429
7009,758621
7883,466667
7527,645161
6763,758621
6682,333333
7855,681818
6738,88
7895,434783
6361,884615
6935,956522
8344,454545
9107,944444

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51531&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]2 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=51531&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51531&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Model: Y[t] = c + b X[t] + e[t]
c5634.55390160495
b4.08224655208704e-05

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 5634.55390160495 \tabularnewline
b & 4.08224655208704e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51531&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]5634.55390160495[/C][/ROW]
[ROW][C]b[/C][C]4.08224655208704e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51531&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51531&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]
c5634.55390160495
b4.08224655208704e-05






Descriptive Statistics about e[t]
# observations60
minimum-1016.86220460359
Q1-215.952460086642
median46.1739186085373
mean1.63193532761359e-14
Q3251.431485536416
maximum957.117255654717

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1016.86220460359 \tabularnewline
Q1 & -215.952460086642 \tabularnewline
median & 46.1739186085373 \tabularnewline
mean & 1.63193532761359e-14 \tabularnewline
Q3 & 251.431485536416 \tabularnewline
maximum & 957.117255654717 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51531&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]-1016.86220460359[/C][/ROW]
[ROW][C]Q1[/C][C]-215.952460086642[/C][/ROW]
[ROW][C]median[/C][C]46.1739186085373[/C][/ROW]
[ROW][C]mean[/C][C]1.63193532761359e-14[/C][/ROW]
[ROW][C]Q3[/C][C]251.431485536416[/C][/ROW]
[ROW][C]maximum[/C][C]957.117255654717[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51531&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51531&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-1016.86220460359
Q1-215.952460086642
median46.1739186085373
mean1.63193532761359e-14
Q3251.431485536416
maximum957.117255654717


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')