Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationMon, 20 Oct 2008 12:23:11 -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/t1224527103ziaq9v0oon26rtj.htm/, Retrieved Fri, 17 May 2024 11:39:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17852, Retrieved Fri, 17 May 2024 11:39:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Pearson Correlation] [Q4 Clothing produ...] [2007-10-20 14:33:09] [b731da8b544846036771bbf9bf2f34ce]
- RM D  [Percentiles] [Percentiles] [2008-10-18 17:01:55] [b943bd7078334192ff8343563ee31113]
F RMPD      [Pearson Correlation] [Pearson Tijdreeks...] [2008-10-20 18:23:11] [620b6ad5c4696049e39cb73ce029682c] [Current]
Feedback Forum
2008-10-27 11:47:29 [Michael Van Spaandonck] [reply
Een waarde van 0,47 duidt inderdaad op een gemiddeld positief lineair verband tussen uitvoer naar en invoer vanuit Amerika.

Post a new message
Dataseries X:
1045.9
1401.9
1027.6
1703.8
1481.3
1422.7
1304.7
1246.1
1417.8
1459.1
1156.4
1304.5
1336.9
1372.3
975.5
1180.8
1361.3
1428.1
1355.9
1781.2
1697
1852
1844.1
1967.2
1747.1
1863.9
1559.3
1675
2237.5
1965.2
1871.5
1752.2
1360.7
1444.3
1621.6
1368
1553.9
1695.3
1397.1
1848.4
1809.2
1551.1
1546.6
1467.9
1662.4
1972.3
1673.5
1762
2019.8
1754.3
1400.4
1453.6
1740.9
1694.6
1541.2
1482.3
1632.1
1837.3
1797
2066.2
1983.8
1601.7
1660.3
1954
1991.9
1881.4
2345.5
1773.1
1719.2
2240.9
1816.4
2171.3
1823.3
2022.5
1991
1920
2168.4
2013.5
1790.8
1855.7
2074
2535.8
1837.2
1805.1
1785.7
2250
1959.7
1890.8
2405.7
2090.3
1666.5
1803.5
1793.8
1488.8
1545
1369.9
1451.6
Dataseries Y:
1593
1477.9
1733.7
1569.7
1843.7
1950.3
1657.5
1772.1
1568.3
1809.8
1646.7
1808.5
1763.9
1625.5
1538.8
1342.4
1645.1
1619.9
1338.1
1505.5
1529.1
1511.9
1656.7
1694.4
1662.3
1588.7
1483.3
1585.6
1658.9
1584.4
1470.6
1618.7
1407.6
1473.9
1515.3
1485.4
1496.1
1493.5
1298.4
1375.3
1507.9
1455.3
1363.3
1392.8
1348.8
1880.3
1669.2
1543.6
1701.2
1516.5
1466.8
1484.1
1577.2
1684.5
1414.7
1674.5
1598.7
1739.1
1674.6
1671.8
1802
1526.8
1580.9
1634.8
1610.3
1712
1678.8
1708.1
1680.6
2056
1624
2021.4
1861.1
1750.8
1767.5
1710.3
2151.5
2047.9
1915.4
1984.7
1896.5
2170.8
2139.9
2330.5
2121.8
2226.8
1857.9
2155.9
2341.7
2290.2
2006.5
2111.9
1731.3
1762.2
1863.2
1943.5
1975.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17852&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]1 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=17852&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17852&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean1705.442268041241706.35154639175
Biased Variance93674.700584546757561.1616728664
Biased Standard Deviation306.063229716584239.919073174407
Covariance35151.9942568729
Correlation0.473776522098695
Determination0.224464192891935
T-Test5.24365863362446
p-value (2 sided)9.50913180419732e-07
p-value (1 sided)4.75456590209866e-07
Degrees of Freedom95
Number of Observations97

\begin{tabular}{lllllllll}
\hline
Pearson Product Moment Correlation - Ungrouped Data \tabularnewline
Statistic & Variable X & Variable Y \tabularnewline
Mean & 1705.44226804124 & 1706.35154639175 \tabularnewline
Biased Variance & 93674.7005845467 & 57561.1616728664 \tabularnewline
Biased Standard Deviation & 306.063229716584 & 239.919073174407 \tabularnewline
Covariance & 35151.9942568729 \tabularnewline
Correlation & 0.473776522098695 \tabularnewline
Determination & 0.224464192891935 \tabularnewline
T-Test & 5.24365863362446 \tabularnewline
p-value (2 sided) & 9.50913180419732e-07 \tabularnewline
p-value (1 sided) & 4.75456590209866e-07 \tabularnewline
Degrees of Freedom & 95 \tabularnewline
Number of Observations & 97 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17852&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]1705.44226804124[/C][C]1706.35154639175[/C][/ROW]
[ROW][C]Biased Variance[/C][C]93674.7005845467[/C][C]57561.1616728664[/C][/ROW]
[ROW][C]Biased Standard Deviation[/C][C]306.063229716584[/C][C]239.919073174407[/C][/ROW]
[ROW][C]Covariance[/C][C]35151.9942568729[/C][/ROW]
[ROW][C]Correlation[/C][C]0.473776522098695[/C][/ROW]
[ROW][C]Determination[/C][C]0.224464192891935[/C][/ROW]
[ROW][C]T-Test[/C][C]5.24365863362446[/C][/ROW]
[ROW][C]p-value (2 sided)[/C][C]9.50913180419732e-07[/C][/ROW]
[ROW][C]p-value (1 sided)[/C][C]4.75456590209866e-07[/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=17852&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17852&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Pearson Product Moment Correlation - Ungrouped Data
StatisticVariable XVariable Y
Mean1705.442268041241706.35154639175
Biased Variance93674.700584546757561.1616728664
Biased Standard Deviation306.063229716584239.919073174407
Covariance35151.9942568729
Correlation0.473776522098695
Determination0.224464192891935
T-Test5.24365863362446
p-value (2 sided)9.50913180419732e-07
p-value (1 sided)4.75456590209866e-07
Degrees of Freedom95
Number of Observations97



Parameters (Session):
par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = Uitvoer naar Amerika ; par5 = Rentevoet ;
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')