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Description of Statistical Computation

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, 17 Nov 2011 09:38:49 -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/2011/Nov/17/t1321540788t62scerrw4ec65w.htm/, Retrieved Tue, 16 Apr 2024 12:18:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=144752, Retrieved Tue, 16 Apr 2024 12:18:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69

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  [Blocked Bootstrap Plot - Central Tendency] [Colombia Coffee] [2008-01-07 10:26:26] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Explorative Data Analysis] [EDA] [2011-11-17 14:38:49] [e5e604418bec6ffe5109fb01f8a59ccb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
61
81
87
87
136
147
168
185
137
125
64
45
35
-4
88
85
95
128
186
182
151
106
60
44
30
54
72
88
153
168
181
180
149
84
85
42
54
30
96
110
141
159
164
155
135
93
28
56
56
22
76
83
121
151
208
179
139
99
103
57
44
70
58
91
126
146
199
194
145
131
74
-3
7
10
34
94
105
151
162
175
128
115
62
11
-7
64
80
77
127
158
173
206
147
103
73
52
52
68
77
94
147
160
166
167
155
104
44
53
56
36
76
99
142
150
190
176
175
112
73
52
48
61
68
97
146
160
155
175
163
117
82
55
32
48
53
82
139
150
184
185
138
147
77
32
48
72
76
94
133
164
174
187
149
102
86
35
31
28
75
102
133
178
190
190
147
83
83
46
40
50
61
102
117
158
170
190
155
117
68
40
56
28
66
103
122
166
176
164
160
139
75
44
22
32
42
86
140
163
222
166
183
140
98
69
75
63
81
126
139
171
170
173
144
105
75
41
68
53
61
87
155
159
180
175
138
105
73
26
12
35
64
115
138
138
182
191
155
113
98
29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'AstonUniversity' @ aston.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 & 4 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144752&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144752&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144752&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 time4 seconds
R Server'AstonUniversity' @ aston.wessa.net






Descriptive Statistics
# observations240
minimum-7
Q161.75
median102
mean106.370833333333
Q3153.5
maximum222

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 240 \tabularnewline
minimum & -7 \tabularnewline
Q1 & 61.75 \tabularnewline
median & 102 \tabularnewline
mean & 106.370833333333 \tabularnewline
Q3 & 153.5 \tabularnewline
maximum & 222 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=144752&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]240[/C][/ROW]
[ROW][C]minimum[/C][C]-7[/C][/ROW]
[ROW][C]Q1[/C][C]61.75[/C][/ROW]
[ROW][C]median[/C][C]102[/C][/ROW]
[ROW][C]mean[/C][C]106.370833333333[/C][/ROW]
[ROW][C]Q3[/C][C]153.5[/C][/ROW]
[ROW][C]maximum[/C][C]222[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=144752&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=144752&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:

Descriptive Statistics
# observations240
minimum-7
Q161.75
median102
mean106.370833333333
Q3153.5
maximum222


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)
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')