Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationTue, 25 Nov 2008 00:22:11 -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/2008/Nov/25/t12275977668yvmcvdb3j33dg5.htm/, Retrieved Thu, 09 May 2024 13:58:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=25569, Retrieved Thu, 09 May 2024 13:58:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Taak 6 - Q2 (1)] [2008-11-16 11:01:18] [46c5a5fbda57fdfa1d4ef48658f82a0c]
F    D    [Univariate Explorative Data Analysis] [Task 6 - Q1] [2008-11-25 07:22:11] [e7b118d7688fea522247297d6fc6c452] [Current]
Feedback Forum
2008-11-30 15:11:26 [Chi-Kwong Man] [reply
Voor deze vraag moet men deze assumpties testen:

1e voorwaarde: Het gemiddelde moet constant zijn, en gelijk zijn aan 0.
2e voorwaarde: Er mag geen autocorrelatie zijn.
3e voorwaarde: De variantie moet constant zijn.
4e voorwaarde: De residu’s moeten normaal verdeeld zijn.

Post a new message
Dataseries X:
-183.9235445
-177.0726091
-228.6351091
-237.4476091
-127.7601091
-193.0101091
-220.6351091
-164.5101091
-268.3226091
-333.6976091
-34.26010911
-154.8851091
-97.74528053
101.1056549
2.543154874
-43.26934513
-163.5818451
-162.8318451
46.54315487
26.66815487
-107.1443451
42.48065487
76.91815487
196.2931549
201.4329835
12.28391886
-0.278581137
42.90891886
87.59641886
84.34641886
57.72141886
173.8464189
-185.9660811
47.65891886
89.09641886
-68.52858114
272.6112475
146.4621829
162.8996829
10.08718285
279.7746829
212.5246829
248.8996829
-41.97531715
-5.787817149
52.83718285
274.2746829
414.6496829
310.7895114
362.6404468
26.07794684
403.2654468
327.9529468
193.7029468
317.0779468
202.2029468
321.3904468
178.0154468
16.45294684
-68.17205316
-157.0322246
-76.18128917
-81.74378917
-134.5562892
77.13121083
199.8812108
105.2562108
198.3812108
262.5687108
196.1937108
11.63121083
-145.9937892
-166.8539606
-202.0030252
43.43447482
-113.3780252
-113.6905252
-155.9405252
-210.5655252
-124.4405252
-64.25302518
-298.6280252
-154.1905252
23.18447482
-249.6756966
118.1752388
-180.3872612
-79.19976119
-81.51226119
-246.7622612
-105.3872612
-319.2622612
-72.07476119
-90.44976119
-80.01226119
119.3627388
-53.49743261
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-14.58399721
-82.20899721
17.91600279
-162.8964972
-132.2714972
-16.83399721
81.54100279
275.6808314
-32.46823322
17.96926678
27.15676678
-123.1557332
108.5942668
67.96926678
34.09426678
-13.71823322
-113.0932332
54.34426678
149.7192668
153.8590954
-28.28996923
238.1475308
50.33503077
8.022530771
-61.22746923
-140.8524692
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9.460030771
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41.52253077
115.8975308
27.03735936
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3.325794759
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27.06655875
60.50405875
35.69155875
16.37905875
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115.5040587
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87.81655875
205.4415587
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35.24482274
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17.86982274
2.557322737
129.3073227
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164.8073227
21.99482274
138.6198227
87.05732274
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5.245620328
68.43312033
-0.879379672
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102.5581203
23.18312033
-180.3793797
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30.13544892
23.98638432
90.42388432
31.61138432
81.29888432
25.04888432
-13.57611568
33.54888432
140.7363843
132.3613843
94.79888432
4.173884316




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25569&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25569&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Descriptive Statistics
# observations192
minimum-333.6976091
Q1-105.826532175
median4.709752322
mean-8.0729257479187e-10
Q385.02414483
maximum414.6496829

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 192 \tabularnewline
minimum & -333.6976091 \tabularnewline
Q1 & -105.826532175 \tabularnewline
median & 4.709752322 \tabularnewline
mean & -8.0729257479187e-10 \tabularnewline
Q3 & 85.02414483 \tabularnewline
maximum & 414.6496829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25569&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]192[/C][/ROW]
[ROW][C]minimum[/C][C]-333.6976091[/C][/ROW]
[ROW][C]Q1[/C][C]-105.826532175[/C][/ROW]
[ROW][C]median[/C][C]4.709752322[/C][/ROW]
[ROW][C]mean[/C][C]-8.0729257479187e-10[/C][/ROW]
[ROW][C]Q3[/C][C]85.02414483[/C][/ROW]
[ROW][C]maximum[/C][C]414.6496829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25569&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics
# observations192
minimum-333.6976091
Q1-105.826532175
median4.709752322
mean-8.0729257479187e-10
Q385.02414483
maximum414.6496829



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)
library(lattice)
bitmap(file='pic1.png')
plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(x)
grid()
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~x,col='black',main='Density Plot')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot1.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main='Lag plot (k=1), lowess, and regression line')
lines(lowess(z))
abline(lm(z))
dev.off()
if (par2 > 1) {
bitmap(file='lagplotpar2.png')
dum <- cbind(lag(x,k=par2),x)
dum
dum1 <- dum[(par2+1):length(x),]
dum1
z <- as.data.frame(dum1)
z
mylagtitle <- 'Lag plot (k='
mylagtitle <- paste(mylagtitle,par2,sep='')
mylagtitle <- paste(mylagtitle,'), and lowess',sep='')
plot(z,main=mylagtitle)
lines(lowess(z))
dev.off()
}
bitmap(file='pic5.png')
acf(x,lag.max=par2,main='Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(x,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(x,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')