Free Statistics

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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 computationThu, 23 Oct 2008 06:24:03 -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/2008/Oct/23/t1224764711fqxt1dpnpzyc2e4.htm/, Retrieved Sun, 19 May 2024 14:38:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18487, Retrieved Sun, 19 May 2024 14:38:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact242
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Univariate Explorative Data Analysis] [Q2 kledij] [2008-10-23 12:24:03] [b23db733701c4d62df5e228d507c1c6a] [Current]
F R       [Univariate Explorative Data Analysis] [Q2 Investigating ...] [2008-10-24 17:21:50] [29647dffafb5b58c12a48dbf6cba2b57]
F         [Univariate Explorative Data Analysis] [Univariate explor...] [2008-10-27 09:05:47] [b5373f20234c18c6452d5f98d8abf0fe]
- RMP     [Central Tendency] [Q2 verbetering] [2008-10-28 18:57:50] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- R         [Central Tendency] [Q2 verbetering (2)] [2008-10-28 19:00:48] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-    D    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-12-19 20:31:13] [29647dffafb5b58c12a48dbf6cba2b57]
-           [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-12-20 16:04:20] [70cb582895831af4be81fec73c607e93]
- RMPD      [Notched Boxplots] [Evelyn] [2008-12-20 16:07:43] [29647dffafb5b58c12a48dbf6cba2b57]
Feedback Forum
2008-10-28 19:39:54 [Ken Van den Heuvel] [reply
Q2: assumptie 3&4.
Bij assumptie 3 deed ik in feite grotendeels wat ik bij assumptie 4 moest doen, namelijk nagaan of de mean ongeveer 0 is.

Assumptie 3:
http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/28/t1225220484jswurbt3ibggf56.htm

Op de plot van de winsorized mean zien we een bescheiden negatief verloop over de gehele termijn gezien. De locatie zal dus niet vast zijn.

Assumptie 4:
http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/28/t1225220321std1trcmlbp0m19.htm

Als we de mean aftrekken van de tijdsreeks houden we error component over. De mean van deze component zou 0 moeten zijn. Uit de gegeven herberekening blijkt ongeveer te kloppen (winsorized mean ligt binnen het betrouwbaarheidsinterval). De variatie lijkt dus vast.
2008-11-04 08:33:56 [Bas van Keken] [reply
Het negatieve verloop neem ik niet waar bij de winsorized mean.
2008-11-04 08:36:50 [Bas van Keken] [reply
De uitleg van de resultaten is uitstekend. Vooral het relativeringsvermogen en juiste bewoording is gebruikt.

Post a new message
Dataseries X:
109.20
88.60
94.30
98.30
86.40
80.60
104.10
108.20
93.40
71.90
94.10
94.90
96.40
91.10
84.40
86.40
88.00
75.10
109.70
103.00
82.10
68.00
96.40
94.30
90.00
88.00
76.10
82.50
81.40
66.50
97.20
94.10
80.70
70.50
87.80
89.50
99.60
84.20
75.10
92.00
80.80
73.10
99.80
90.00
83.10
72.40
78.80
87.30
91.00
80.10
73.60
86.40
74.50
71.20
92.40
81.50
85.30
69.90
84.20
90.70
100.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18487&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18487&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations61
minimum66.5
Q180.6
median87.3
mean86.8934426229508
Q394.1
maximum109.7

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 66.5 \tabularnewline
Q1 & 80.6 \tabularnewline
median & 87.3 \tabularnewline
mean & 86.8934426229508 \tabularnewline
Q3 & 94.1 \tabularnewline
maximum & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18487&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]66.5[/C][/ROW]
[ROW][C]Q1[/C][C]80.6[/C][/ROW]
[ROW][C]median[/C][C]87.3[/C][/ROW]
[ROW][C]mean[/C][C]86.8934426229508[/C][/ROW]
[ROW][C]Q3[/C][C]94.1[/C][/ROW]
[ROW][C]maximum[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18487&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
# observations61
minimum66.5
Q180.6
median87.3
mean86.8934426229508
Q394.1
maximum109.7



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')