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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationMon, 20 Oct 2008 13:15:50 -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/20/t1224530207xgtjac5mcq9d89i.htm/, Retrieved Sun, 19 May 2024 14:46:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17936, Retrieved Sun, 19 May 2024 14:46:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact111

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Back to Back Histogram] [Omzet industrie v...] [2008-10-20 18:44:01] [e340b5273efb4d885d02142e6a0fc74b]
F RMPD  [Pearson Correlation] [Correlation omzet...] [2008-10-20 19:08:40] [e340b5273efb4d885d02142e6a0fc74b]
F    D      [Pearson Correlation] [correlation inves...] [2008-10-20 19:15:50] [0ee5a336ab8a2fb221821eda2df0f830] [Current]
F    D        [Pearson Correlation] [correlation omzet...] [2008-10-20 19:20:53] [e340b5273efb4d885d02142e6a0fc74b]
F    D          [Pearson Correlation] [correlaation omze...] [2008-10-20 19:26:14] [e340b5273efb4d885d02142e6a0fc74b]
Feedback Forum
2008-10-27 01:32:39 [Kristof Augustyns] [reply] 
Nu gaat het om de correlatie INVESTERINGEN industrie en niet-industrie.
Hier is de correlatie ook vrij hoog: 0.775169366145227 of een 78% samenhang.
Dit kan je ook zo wat zien met het blote oog op de grafiek.
Als er voor 100% iets gebeurd bij de investeringen van de industrie, zal er voor 78% ook iets gebeuren bij de niet-industrie.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
80,7
86,9
105
95,1
100,2
182,4
90
78,2
97,4
84,2
90
100,9
84,5
92,3
90,3
91
96,4
167,6
88,5
67,5
83
77,7
80,6
96,1
71,2
75,3
90,9
106,4
96,3
181,2
65,4
72,2
80,4
77,7
76,5
100,1
73,5
77,3
98,6
112,4
77,3
139,3
75,4
64,2
86,8
79,1
71,7
100
82,1
74,8
92,3
83,3
83,7
148
71,4
71,2
84,6
80,9
80,6
105,5
79,2
78,4
92,6
88,3
98,2
157,4
73,9
80,9
93
84,9
96,2
106,5
81,7
82,9
96
92,6
116,5
155
95,1
86,2
105
89,7
97,1
120,8
92,2
98,8
104,1
106,5
113,4
192,4
103,6
97,6
99,9
106,2
104,9
114,2
94,5
Dataseries Y:
Download CSV
Histogram 
86,7
87,9
89,8
103
102,7
156,3
95
84,6
106,5
98,7
103,5
110,7
96,2
89,2
97,1
104,8
132,5
154,8
83,6
82,4
103,9
87
93,2
110,5
96,4
76,3
94
103,4
137
150,1
112,6
81,4
113,6
99,6
98,2
118,6
86,8
79,3
98,4
93,6
101
161,2
92,5
99,8
104,1
90,2
99,2
116,5
98,4
90,6
130,5
107,4
106
196,5
107,8
90,5
123,8
114,7
115,3
197
88,4
93,8
111,3
105,9
123,6
171
97
99,2
126,6
103,4
121,3
129,6
110,8
98,9
122,8
120,9
133,1
203,1
110,2
119,5
135,1
113,9
137,4
157,1
126,4
112,2
128,8
136,8
156,5
215,2
146,7
130,8
133,1
154,4
160,4
175,1
145,3

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17936&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17936&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17936&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'George Udny Yule' @ 72.249.76.132






Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean95.778350515464116.479381443299
Biased Variance603.481696248273820.608028483367
Biased Standard Deviation24.565864451475628.6462567970646
Covariance551.184548969072
Correlation0.775169366145227
Determination0.600887546209993
T-Test11.9594377987208
p-value (2 sided)0
p-value (1 sided)0
Degrees of Freedom95
Number of Observations97

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 95.778350515464 & 116.479381443299 \tabularnewline
Biased Variance & 603.481696248273 & 820.608028483367 \tabularnewline
Biased Standard Deviation & 24.5658644514756 & 28.6462567970646 \tabularnewline
Covariance & 551.184548969072 \tabularnewline
Correlation & 0.775169366145227 \tabularnewline
Determination & 0.600887546209993 \tabularnewline
T-Test & 11.9594377987208 \tabularnewline
p-value (2 sided) & 0 \tabularnewline
p-value (1 sided) & 0 \tabularnewline
Degrees of Freedom & 95 \tabularnewline
Number of Observations & 97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17936&T=1

[TABLE]
[ROW][C]Pearson Product Moment Correlation - Ungrouped Data[/C][/ROW]
[ROW][C]Statistic[/C][C]Variable X[/C][C]Variable Y[/C][/ROW]
[ROW][C]Mean[/C][C]95.778350515464[/C][C]116.479381443299[/C][/ROW]
[ROW][C]Biased Variance[/C][C]603.481696248273[/C][C]820.608028483367[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]24.5658644514756[/C][C]28.6462567970646[/C][/ROW]
[ROW][C]Covariance[/C][C]551.184548969072[/C][/ROW]
[ROW][C]Correlation[/C][C]0.775169366145227[/C][/ROW]
[ROW][C]Determination[/C][C]0.600887546209993[/C][/ROW]
[ROW][C]T-Test[/C][C]11.9594377987208[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]0[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]0[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]95[/C][/ROW]
[ROW][C]Number of Observations[/C][C]97[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17936&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17936&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:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean95.778350515464116.479381443299
Biased Variance603.481696248273820.608028483367
Biased Standard Deviation24.565864451475628.6462567970646
Covariance551.184548969072
Correlation0.775169366145227
Determination0.600887546209993
T-Test11.9594377987208
p-value (2 sided)0
p-value (1 sided)0
Degrees of Freedom95
Number of Observations97


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
bitmap(file='test1.png')
histx <- hist(x, plot=FALSE)
histy <- hist(y, plot=FALSE)
maxcounts <- max(c(histx$counts, histx$counts))
xrange <- c(min(x),max(x))
yrange <- c(min(y),max(y))
nf <- layout(matrix(c(2,0,1,3),2,2,byrow=TRUE), c(3,1), c(1,3), TRUE)
par(mar=c(4,4,1,1))
plot(x, y, xlim=xrange, ylim=yrange, xlab=xlab, ylab=ylab)
par(mar=c(0,4,1,1))
barplot(histx$counts, axes=FALSE, ylim=c(0, maxcounts), space=0)
par(mar=c(4,0,1,1))
barplot(histy$counts, axes=FALSE, xlim=c(0, maxcounts), space=0, horiz=TRUE)
dev.off()
lx = length(x)
makebiased = (lx-1)/lx
varx = var(x)*makebiased
vary = var(y)*makebiased
corxy <- cor.test(x,y,method='pearson')
cxy <- as.matrix(corxy$estimate)[1,1]
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson Product Moment Correlation - Ungrouped Data',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Statistic',1,TRUE)
a<-table.element(a,'Variable X',1,TRUE)
a<-table.element(a,'Variable Y',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm','Mean',''),header=TRUE)
a<-table.element(a,mean(x))
a<-table.element(a,mean(y))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased.htm','Biased Variance',''),header=TRUE)
a<-table.element(a,varx)
a<-table.element(a,vary)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('biased1.htm','Biased Standard Deviation',''),header=TRUE)
a<-table.element(a,sqrt(varx))
a<-table.element(a,sqrt(vary))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('covariance.htm','Covariance',''),header=TRUE)
a<-table.element(a,cov(x,y),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('pearson_correlation.htm','Correlation',''),header=TRUE)
a<-table.element(a,cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('coeff_of_determination.htm','Determination',''),header=TRUE)
a<-table.element(a,cxy*cxy,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('ttest_statistic.htm','T-Test',''),header=TRUE)
a<-table.element(a,as.matrix(corxy$statistic)[1,1],2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (2 sided)',header=TRUE)
a<-table.element(a,(p2 <- as.matrix(corxy$p.value)[1,1]),2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (1 sided)',header=TRUE)
a<-table.element(a,p2/2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degrees of Freedom',header=TRUE)
a<-table.element(a,lx-2,2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of Observations',header=TRUE)
a<-table.element(a,lx,2)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')