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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 computationSun, 09 Dec 2012 13:02:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/09/t1355076185ed6mn1n2b6qvddc.htm/, Retrieved Thu, 18 Apr 2024 18:35:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198018, Retrieved Thu, 18 Apr 2024 18:35:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
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]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Explorative Data Analysis] [Paper] [2012-12-09 18:02:36] [38c0fff34b8aa23b45468de8b641bfee] [Current]
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Dataseries X:
115.01
124.56
128.60
131.54
124.93
126.77
128.97
149.91
149.55
149.91
159.47
162.04
163.88
166.82
173.80
172.06
178.21
174.53
176.37
168.65
166.82
164.24
163.51
164.61
163.51
164.61
167.92
160.94
156.53
159.47
149.18
135.58
124.93
116.84
114.27
114.64
112.80
113.17
111.33
113.91
119.42
120.89
122.04
120.15
118.21
125.33
135.37
146.89
149.54
160.84
169.95
177.13
169.35
159.93
149.69
148.67
136.32
128.17
138.74
140.58
147.57
147.83
155.65
148.88
147.90
141.99
136.58
121.82
127.52
129.80
131.29
135.96
146.50
158.65
153.21
147.04
141.04
140.45
140.15
139.30
137.60
146.02
158.79
167.19
161.99
164.62
156.21
154.42
150.39
148.98
158.61
169.98
190.09
184.39
193.67
203.79
204.07
208.92
206.88
218.89
215.52
251.66
262.11
227.27
202.60
191.63
178.71
178.32
176.41
175.70
175.73
172.35
176.61
183.49
172.59
148.39
138.31
150.61
151.74
151.66
149.88
144.62
137.10
140.05
138.92
130.15
128.92
120.64
118.54
107.95
107.93
126.54
130.21
126.21
125.29
117.03
117.34
113.87
113.00
111.41
103.02
111.41
113.19
108.10
108.80
102.16
105.83
108.41
105.70
105.11
110.78
113.51
108.98
108.28
117.49
128.22
127.73
128.01
132.84
128.12
130.28
129.30
135.00
127.23
123.79
121.92
122.03
123.34
125.27
122.53
125.31
123.28
122.56
123.72
121.46
132.03
149.30
161.26
187.84
190.32
176.26
168.98
149.60
150.84
141.81
138.62
141.96
131.35
131.62
148.72
145.62
147.46
160.55
165.57
166.33
161.39
166.28
166.58
163.73
154.74
150.60
141.29
151.03
150.15
156.57
153.87
153.59
151.30
150.99
140.88
144.25
141.93
143.87
149.36
159.71
167.83
161.12
164.44
167.16
179.84
174.44
180.35
193.17
195.16
202.43
189.91
195.98
212.09
205.81
204.31
196.07
199.98
199.10
198.31
195.72
223.04
238.41
259.73
326.54
335.15
321.81
368.62
369.59
425.00
439.72
362.23
328.76
348.55
328.18
329.34
295.55
237.38
226.85
220.14
239.36
224.69
230.98
233.47
256.70
253.41
224.95
210.37
191.09
198.85
211.04
206.25
201.51
194.54
191.07
192.82
181.88
157.67
195.82
246.25
271.69
270.23
274.08
306.53
326.55
348.15
316.75
336.12
354.47
326.43
303.88
327.07
315.92
289.01
281.01
269.03
274.89
277.77
283.88
266.32
264.36
276.19
345.69
349.40
353.42
358.20
361.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198018&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198018&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198018&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 time6 seconds
R Server'George Udny Yule' @ yule.wessa.net







Descriptive Statistics
# observations301
minimum102.16
Q1131.62
median158.65
mean178.879302325581
Q3198.31
maximum439.72

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 301 \tabularnewline
minimum & 102.16 \tabularnewline
Q1 & 131.62 \tabularnewline
median & 158.65 \tabularnewline
mean & 178.879302325581 \tabularnewline
Q3 & 198.31 \tabularnewline
maximum & 439.72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198018&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]301[/C][/ROW]
[ROW][C]minimum[/C][C]102.16[/C][/ROW]
[ROW][C]Q1[/C][C]131.62[/C][/ROW]
[ROW][C]median[/C][C]158.65[/C][/ROW]
[ROW][C]mean[/C][C]178.879302325581[/C][/ROW]
[ROW][C]Q3[/C][C]198.31[/C][/ROW]
[ROW][C]maximum[/C][C]439.72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198018&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198018&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
# observations301
minimum102.16
Q1131.62
median158.65
mean178.879302325581
Q3198.31
maximum439.72



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')