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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationTue, 11 Nov 2008 08:21:20 -0700
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/Nov/11/t1226416895k97usapqsg34jtv.htm/, Retrieved Sun, 19 May 2024 10:41:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23588, Retrieved Sun, 19 May 2024 10:41:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [] [2008-11-11 15:01:49] [29747f79f5beb5b2516e1271770ecb47]
F RMPD  [Partial Correlation] [] [2008-11-11 15:17:50] [29747f79f5beb5b2516e1271770ecb47]
F RMPD      [Trivariate Scatterplots] [] [2008-11-11 15:21:20] [c0a347e3519123f7eef62b705326dad9] [Current]
F RMPD        [Hierarchical Clustering] [] [2008-11-11 15:27:51] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Box-Cox Linearity Plot] [] [2008-11-11 15:33:03] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Testing Mean with known Variance - Critical Value] [] [2008-11-11 16:11:09] [29747f79f5beb5b2516e1271770ecb47]
F RM            [Testing Mean with known Variance - p-value] [] [2008-11-11 16:21:44] [29747f79f5beb5b2516e1271770ecb47]
F RMP           [Testing Mean with known Variance - Type II Error] [] [2008-11-11 16:29:04] [29747f79f5beb5b2516e1271770ecb47]
- RMP           [Testing Mean with known Variance - Sample Size] [] [2008-11-11 16:34:38] [29747f79f5beb5b2516e1271770ecb47]
F                 [Testing Mean with known Variance - Sample Size] [] [2008-11-11 16:40:41] [29747f79f5beb5b2516e1271770ecb47]
F RM              [Testing Population Mean with known Variance - Confidence Interval] [] [2008-11-11 17:00:42] [29747f79f5beb5b2516e1271770ecb47]
F RM              [Testing Sample Mean with known Variance - Confidence Interval] [] [2008-11-11 17:05:19] [29747f79f5beb5b2516e1271770ecb47]
Feedback Forum
2008-11-24 17:53:39 [Jan Cavents] [reply] 
de kubussen geven drie dimensionaal weer wat de verbanden zijn tussen de reeksen. omdat die op een scherm niet duidelijk is, moeten we oppassen met de conclusies die we er uit trekken

verder hebben we ook nog een grafiek met scatterplots en histogrammen, hier worden de verbanden onderling ook nog eens weergegeven.

tot slot geeft ook de scatterplot de verbanden weer.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97.6
96.9
105.6
102.8
101.7
104.2
92.7
91.9
106.5
112.3
102.8
96.5
101.0
98.9
105.1
103.0
99.0
104.3
94.6
90.4
108.9
111.4
100.8
102.5
98.2
98.7
113.3
104.6
99.3
111.8
97.3
97.7
115.6
111.9
107.0
107.1
100.6
99.2
108.4
103.0
99.8
115.0
90.8
95.9
114.4
108.2
112.6
109.1
105.0
105.0
118.5
103.7
112.5
116.6
96.6
101.9
116.5
119.3
115.4
108.5
111.5
108.8
121.8
109.6
112.2
119.6
104.1
105.3
115.0
124.1
116.8
107.5
115.6
116.2
116.3
119.0
111.9
118.6
106.7
Dataseries Y:
Download CSV
Histogram 
9.1
9.0
8.6
7.9
7.7
7.8
9.1
9.4
9.3
8.7
8.4
8.6
9.0
9.1
8.7
8.2
7.9
7.9
9.1
9.4
9.5
9.1
9.0
9.3
9.9
9.8
9.4
8.3
8.0
8.5
10.4
11.1
10.9
9.9
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9.0
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9.0
9.0
9.0
9.8
10.0
9.9
9.3
9.0
9.0
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.8
7.9
7.9
8.0
7.9
7.5
7.2
6.9
6.6
6.7
7.3
Dataseries Z:
Download CSV
Histogram 
6.4
6.3
6.3
6.4
6.3
6.0
6.2
6.3
6.6
7.5
7.8
7.9
7.8
7.6
7.5
7.6
7.5
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8.0
7.5
6.8
6.5
6.6
7.6
8.0
8.0
7.7
7.5
7.6
7.7
7.9
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.1
7.9
7.3
6.9
6.6
6.7
6.9
7.0
7.1
7.2
7.1
6.9
7.0
6.8
6.4
6.7
6.7
6.4
6.3
6.2
6.5
6.8
6.8
6.5
6.3
5.9
5.9
6.4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23588&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23588&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23588&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Totale Productie ; par6 = Werkloosheidsgraad Vrouwen ; par7 = Werkloosheidsgraad Mannen ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Totale Productie ; par6 = Werkloosheidsgraad Vrouwen ; par7 = Werkloosheidsgraad Mannen ;
R code (references can be found in the software module):
x <- array(x,dim=c(length(x),1))
colnames(x) <- par5
y <- array(y,dim=c(length(y),1))
colnames(y) <- par6
z <- array(z,dim=c(length(z),1))
colnames(z) <- par7
d <- data.frame(cbind(z,y,x))
colnames(d) <- list(par7,par6,par5)
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1>500) par1 <- 500
if (par2>500) par2 <- 500
if (par1<10) par1 <- 10
if (par2<10) par2 <- 10
library(GenKern)
library(lattice)
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='black', ...)
}
bitmap(file='cloud1.png')
cloud(z~x*y, screen = list(x=-45, y=45, z=35),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='cloud2.png')
cloud(z~x*y, screen = list(x=35, y=45, z=25),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='cloud3.png')
cloud(z~x*y, screen = list(x=35, y=-25, z=90),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='pairs.png')
pairs(d,diag.panel=panel.hist)
dev.off()
x <- as.vector(x)
y <- as.vector(y)
z <- as.vector(z)
bitmap(file='bidensity1.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=cor(x,y), xbandwidth=dpik(x), ybandwidth=dpik(y))
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,y)',xlab=par5,ylab=par6)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
bitmap(file='bidensity2.png')
op <- KernSur(y,z, xgridsize=par1, ygridsize=par2, correlation=cor(y,z), xbandwidth=dpik(y), ybandwidth=dpik(z))
op
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (y,z)',xlab=par6,ylab=par7)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(y,z)
(r<-lm(z ~ y))
abline(r)
box()
dev.off()
bitmap(file='bidensity3.png')
op <- KernSur(x,z, xgridsize=par1, ygridsize=par2, correlation=cor(x,z), xbandwidth=dpik(x), ybandwidth=dpik(z))
op
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,z)',xlab=par5,ylab=par7)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(x,z)
(r<-lm(z ~ x))
abline(r)
box()
dev.off()