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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_meanplot.wasp
Title produced by softwareMean Plot
Date of computationWed, 29 Oct 2008 13:00:24 -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/29/t122530695865hoxtwjla4zti5.htm/, Retrieved Sun, 19 May 2024 14:44:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19938, Retrieved Sun, 19 May 2024 14:44:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Mean Plot] [workshop 3] [2007-10-26 12:14:28] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F R PD    [Mean Plot] [vraag 2] [2008-10-29 19:00:24] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
F R P       [Mean Plot] [vraag 4] [2008-10-29 22:25:49] [c45c87b96bbf32ffc2144fc37d767b2e]
F R PD        [Mean Plot] [taak 5] [2008-10-30 06:53:19] [c45c87b96bbf32ffc2144fc37d767b2e]
-   P           [Mean Plot] [herberekening] [2008-11-05 18:47:04] [c45c87b96bbf32ffc2144fc37d767b2e]
-   P           [Mean Plot] [] [2008-11-11 18:34:45] [2a30350413961f11db13c46be07a5f73]
-   P           [Mean Plot] [] [2008-11-11 18:34:45] [2a30350413961f11db13c46be07a5f73]
-   P           [Mean Plot] [] [2008-11-11 18:34:45] [2a30350413961f11db13c46be07a5f73]
- RMPD          [Bivariate Kernel Density Estimation] [] [2008-11-11 20:43:43] [2a30350413961f11db13c46be07a5f73]
- RMPD          [Partial Correlation] [] [2008-11-11 20:56:10] [2a30350413961f11db13c46be07a5f73]
- RMPD          [Bivariate Kernel Density Estimation] [] [2008-11-11 20:58:08] [2a30350413961f11db13c46be07a5f73]
- RMPD          [Trivariate Scatterplots] [] [2008-11-11 21:02:37] [2a30350413961f11db13c46be07a5f73]
- RMPD          [Hierarchical Clustering] [] [2008-11-11 21:15:39] [2a30350413961f11db13c46be07a5f73]
F   P         [Mean Plot] [Q2] [2008-10-30 21:02:59] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   P       [Mean Plot] [herberekening] [2008-11-05 17:54:04] [c45c87b96bbf32ffc2144fc37d767b2e]
Feedback Forum
2008-11-05 18:02:13 [Michaël De Kuyer] [reply] 
Deze vraag heb ik fout beantwoord. Ik moest me baseren op de gegevens gegenereerd uit de mean plot en moest de blockwitdh instellen 12 : http://www.freestatistics.org/blog/date/2008/Nov/05/t1225907740u81va5u7pjjlkvn.htm. Als ik me baseer op de mean plot kan ik onder andere vaststellen dat de waarde in de zesde maand beduidend lager ligt dan van de zevende maand. Aan de hand van de notched boxplot kan ik vaststellen dat het gaat over een significant verschil, aangezien het betrouwbaarheidsinterval van maand 6 dat van maand 7 niet overlapt. We kunnen dus spreken van seizonaliteit in de tijdreeks.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

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'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=19938&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=19938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19938&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 24 ;
Parameters (R input):
par1 = 24 ;
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()