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, 25 Nov 2009 16:09:30 -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/26/t1259190640n846mz683unsijp.htm/, Retrieved Mon, 29 Apr 2024 06:49:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59682, Retrieved Mon, 29 Apr 2024 06:49:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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_WS4_Q2(1)] [2009-10-23 08:40:25] [8b1aef4e7013bd33fbc2a5833375c5f5]
-  M D    [Bivariate Explorative Data Analysis] [Revieuw ws] [2009-11-25 23:09:30] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
23500.89
23870.25
24087.04
24617.61
24649
24774.76
24711.84
24806.25
24964
25122.25
25281
25376.49
25600
25856.64
26211.61
26406.25
26471.29
26503.84
26536.41
26569
26896
27126.09
27159.04
27192.01
27225
27489.64
27589.21
27955.84
28123.29
28324.89
28425.96
28527.21
28594.81
28730.25
28764.16
28798.09
28832.04
29036.16
29206.81
29549.61
29549.61
29584
29584
29721.76
29929
30171.69
30206.44
30206.44
30241.21
30485.16
30625
30940.81
30976
30660.01
30835.36
30940.81
31222.89
31011.21
31011.21
31046.44
31081.69
31612.84
31862.25
32184.36
32220.25
32256.16
32292.09
32292.09
32328.04
32364.01
32472.04
32544.16
32544.16
32869.69
33087.61
33306.25
33379.29
33525.61
33708.96
33745.69
33782.44
33819.21
33892.81
34003.36
34040.25
34558.81
34819.56
35193.76
35268.84
35306.41
35344
35456.89
35494.56
35532.25
35532.25
35569.96
35569.96
35872.36
36100
36825.61
37056.25
37249
37442.25
37597.21
37713.64
37986.01
37986.01
37986.01
37986.01
38220.25
38416
38494.44
38494.44
38494.44
38494.44
38809
39085.29
39204
39283.24
39402.25
39441.96
39800.25
40000
40521.69
40884.84
41168.41
41412.25
41412.25
41616
41656.81
41738.49
41820.25
41943.04
42066.01
42312.49
42642.25
42807.61
42890.41
43180.84
43264
43472.25
43513.96
43681
43722.81
43974.09
44016.04
44058.01
44100
44436.64
44689.96
44816.89
44944
45028.84
45113.76
45326.41
45539.56
45667.69
45796
45924.49
46139.04
46225
46612.81
46828.96
47045.61
47175.84
47306.25
47480.41
47567.61
47785.96
47917.21
48092.49
48576.16
48796.81
48841
49195.24
49284
49372.84
49506.25
49684.41
49773.61
49907.56
50176
50670.01
50850.25
51030.81
51211.69
51302.25
51529
51665.29
51892.84
52029.61
52166.56
52212.25
52349.44
52441
52486.81
52578.49
52716.16
52854.01
52900
52992.04
53268.64
53361
53684.89
53777.61
54289
55272.01
55696
56121.61
56216.41
56406.25
56739.24
57073.21
57168.81
57600
57696.04
57840.25
57936.49
58129.21
58273.96
58660.84
59000.41
59146.24
59487.21
Dataseries Y:
Download CSV
Histogram 
15.0544
15.8404
10.8241
8.2944
10.3684
13.1044
14.5924
12.5316
6.4009
4.9284
8.1225
7.7284
5.1984
5.1076
7.3441
7.6729
7.6729
6.9696
6.5536
4.2849
5.3824
4.6656
4.9729
5.76
8.0656
7.6729
8.5849
8.4681
7.2361
5.6644
6.6564
10.1761
7.9524
7.3984
6.4009
7.29
5.8564
6.25
5.3361
5.8081
6.5536
7.6176
7.3441
5.9536
6.0516
4.4944
3.9601
3.4596
3.5344
3.3124
3.0276
2.9241
1.9044
1.6129
1.4161
1.6384
1.4161
1.4884
2.1609
2.1316
3.8416
3.5344
4.1209
4.1616
3.61
3.24
3.6864
3.6864
3.8809
6.0516
5.5696
6.4009
5.3361
3.9204
2.1316
1.5876
2.4964
3.0276
3.5721
3.4225
2.6244
1.69
2.0164
1.3225
0.1764
0.5476
1.0404
2.2801
3.4596
2.5281
1.0609
0.1936
0.6724
0.7396
0.3364
0.3481
0.9025
0.9604
1.5129
1.3689
0.7056
0.5476
0.4225
0.8281
1.4161
1.69
2.3409
3.7636
3.2041
3.8025
5.1076
4.1616
4.6656
7.5625
7.7841
8.2944
11.2896
8.8209
9.61
6.2001
4.84
5.0625
4.3681
7.7841
9.8596
8.5849
7.0225
7.1289
5.1076
5.5225
4.5369
4.7524
8.41
6.9169
7.1289
3.2761
1.7689
0.7744
1.6384
1.5876
1.5876
1.6641
1.21
1.8769
1.4641
3.0276
3.0976
2.1904
1.0816
2.6244
2.2201
3.2041
3.24
2.4964
3.4596
3.0276
2.5281
1.5876
1.2769
3.6864
6.8121
5.1076
5.8081
5.1076
4.1209
8.1796
6.5025
5.1529
5.1076
6.6049
9.4249
7.6176
6.3001
8.2369
9.8596
9.6721
9.9856
6.1009
6.6049
8.3521
6.9169
5.6644
2.8561
3.8416
4.7961
3.4969
2.56
2.6569
1.4884
1.4641
2.2201
2.6896
2.7556
3.1329
3.3124
3.1684
1.6384
1.6641
1.8769
1.2544
2.2801
5.0176
8.6436
9.5481
11.9716
13.2496
19.2721
17.2225
27.1441
33.64
34.9281
29.0521
29.8116
22.2784
9.8596
6.9169
5.3824
3.7249
0.3844
0.36
0.1369
1.21
2.8224
0.6084

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59682&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59682&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59682&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c2.56839198511102
b7.37057719653324e-05

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 2.56839198511102 \tabularnewline
b & 7.37057719653324e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59682&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]2.56839198511102[/C][/ROW]
[ROW][C]b[/C][C]7.37057719653324e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59682&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59682&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]
c2.56839198511102
b7.37057719653324e-05






Descriptive Statistics about e[t]
# observations224
minimum-6.75513448144588
Q1-3.41095724726088
median-1.07046649512968
mean2.6238854219334e-16
Q32.00196837458759
maximum28.2022418149694

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 224 \tabularnewline
minimum & -6.75513448144588 \tabularnewline
Q1 & -3.41095724726088 \tabularnewline
median & -1.07046649512968 \tabularnewline
mean & 2.6238854219334e-16 \tabularnewline
Q3 & 2.00196837458759 \tabularnewline
maximum & 28.2022418149694 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59682&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]224[/C][/ROW]
[ROW][C]minimum[/C][C]-6.75513448144588[/C][/ROW]
[ROW][C]Q1[/C][C]-3.41095724726088[/C][/ROW]
[ROW][C]median[/C][C]-1.07046649512968[/C][/ROW]
[ROW][C]mean[/C][C]2.6238854219334e-16[/C][/ROW]
[ROW][C]Q3[/C][C]2.00196837458759[/C][/ROW]
[ROW][C]maximum[/C][C]28.2022418149694[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59682&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59682&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]
# observations224
minimum-6.75513448144588
Q1-3.41095724726088
median-1.07046649512968
mean2.6238854219334e-16
Q32.00196837458759
maximum28.2022418149694


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')