Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_meanplot.wasp
Title produced by softwareMean Plot
Date of computationMon, 03 Mar 2014 14:53:52 -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/2014/Mar/03/t1393876459n9ygu7lst5du31a.htm/, Retrieved Tue, 14 May 2024 13:03:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234154, Retrieved Tue, 14 May 2024 13:03:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Mean Plot] [] [2014-03-03 19:53:52] [7924821bfd3c647737470140bc76edc8] [Current]
- R PD    [Mean Plot] [] [2014-05-19 18:40:49] [92db97885c79b0659d4d94792fd29e93]
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Dataseries X:
71,97
72,32
74,07
77,95
81,75
80,81
74,1
71,37
75,21
76,9
74,44
74,76
76,23
76,97
78,4
78,6
80,08
81,12
80,31
84,59
81,34
80,95
80,48
75,26
76,32
78,92
80,47
83,14
85,42
81,53
87,31
86,01
85,1
79,91
78,6
78,6
79,37
82,89
84,43
85,32
87,71
84,68
80,62
84,79
85,49
81,68
77,69
78,31
79,18
80,91
83,91
86,3
89,76
85,11
83,81
85,36
85,89
82,59
80,87
80,27
81,36
84,81
90,3
95,43
97,59
97,8
99,48
97,52
104,39
97,74
91,37
92,42
96,9
101,58
105,46
110,06
107,9
102,87
96,28
98,59
103,22
98,6
91,79
93,83
95,17
95,19
99,44
109,18
109,15
109,72
108,41
102,96
107,64
97,28
97,25
91,84
94,12
97,86
98,83
102,29
104,49
102,11
102,14
101,28
101,21
94,2
88,47
88,08
88,02
92,95
97,05
101,44
100,34
99,98
94,17
94,54
95,12
98,04
93,72
93,83
93,03
95,81
99,1
100,12
100,67
103,87
102,39
107,21
105,71
99,79
96,12
96,17
97,23
98,08
99,84
99,72
99,92
102,7
102,06
102,36
102,43
100,6
98,4
98,61
103,03
104,7
107,45
109,67
110,54
112,05
113,19
114,2
112,56
107,36
103,93
103,83
104,74
107,5
109,53
109,42
108,6
110,72
105,1
105,19
102,55
101,25
101,56
101,62
101,7
102,94
104,37
106,93
107,82
110,83
106,86
109,46
108,8
108,69
107,77
108,64
108,5
113,84
114,59
116,27
113,63
112,29
110,31
108,47
110,67
109,1
107,02
108,12
106,69
109,87
110,82
114,14
113,31
115,16
111,06
111,13
115,96
117,57
114,69
119,42
118,4
123,32
123,39
127,04
129,35
127,12
122,1
120,22
121,53
119,01
114,27
114,46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234154&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234154&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234154&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'Gwilym Jenkins' @ jenkins.wessa.net



Parameters (Session):
par1 = 18 ;
Parameters (R input):
par1 = 18 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np+1))
darr <- array(NA,dim=c(par1,np+1))
ari <- array(0,dim=par1)
dx <- diff(x)
j <- 0
for (i in 1:n)
{
j = j + 1
ari[j] = ari[j] + 1
arr[j,ari[j]] <- x[i]
darr[j,ari[j]] <- dx[i]
if (j == par1) j = 0
}
ari
arr
darr
arr.mean <- array(NA,dim=par1)
arr.median <- array(NA,dim=par1)
arr.midrange <- array(NA,dim=par1)
for (j in 1:par1)
{
arr.mean[j] <- mean(arr[j,],na.rm=TRUE)
arr.median[j] <- median(arr[j,],na.rm=TRUE)
arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2
}
overall.mean <- mean(x)
overall.median <- median(x)
overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2
bitmap(file='plot1.png')
plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.mean,0)
dev.off()
bitmap(file='plot2.png')
plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.median,0)
dev.off()
bitmap(file='plot3.png')
plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index')
mtext(paste('#blocks = ',np))
abline(overall.midrange,0)
dev.off()
bitmap(file='plot4.png')
z <- data.frame(t(arr))
names(z) <- c(1:par1)
(boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries'))
dev.off()
bitmap(file='plot4b.png')
z <- data.frame(t(darr))
names(z) <- c(1:par1)
(boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Differenced Periodic Subseries'))
dev.off()
bitmap(file='plot5.png')
z <- data.frame(arr)
names(z) <- c(1:np)
(boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks'))
dev.off()
bitmap(file='plot6.png')
z <- data.frame(cbind(arr.mean,arr.median,arr.midrange))
names(z) <- list('mean','median','midrange')
(boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots'))
dev.off()