Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_correlation.wasp
Title produced by softwarePearson Correlation
Date of computationSat, 06 Sep 2014 21:50:42 +0100
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/Sep/06/t1410036711f7g7wbwuwda9diz.htm/, Retrieved Sun, 12 May 2024 19:26:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235786, Retrieved Sun, 12 May 2024 19:26:57 +0000
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Original text written by user:a
IsPrivate?No (this computation is public)
User-defined keywordsa
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Pearson Correlation] [a] [2014-09-06 20:50:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
2.382.290
1.595.000
4.000.000
3.424.470
2.885.000
2.100.000
1.120.820
1.222.000
4.146.000
1.934.000
2.202.810
3.447.010
1.811.350
5.123.210
544.847
1.153.470
1.026.600
1.296.520
1.797.000
1.019.000
853.000
667.000
1.675.000
1.754.420
708.000
1.460.000
875.000
342.000
1.396.000
638.500
868.964
1.091.950
932.159
1.708.000
648.000
683.000
667.047
210.000
248.000
13.089.000
6.774.000
2.187.000
4.000.000
2.467.400
840.000
967.000
1.083.750
956.550
5.200.000
4.450.000
2.025.420
981.469
1.153.000
1.031.210
1.283.190
935.321
594.500
402.500
1.251.320
707.001
1.105.000
1.298.750
113.000
434.724
567.000
1.235.770
352.000
711.250
381.157
1.631.000
5.013.090
3.034.000
6.950.420
1.313.000
1.158.000
849.330
879.166
679.000
862.500
1.025.130
1.066.550
981.000
679.000
914.874
638.394
1.453.640
1.453.640
2.862.000
2.615.000
6.556.000
2.325.000
1.215.000
6.305.000
1.810.000
1.328.000
2.347.000
2.065.890
1.212.700
4.207.960
2.146.550
239.000
782.400
785.000
2.885.000
1.413.670
2.515.000
475.882
473.000
430.000
350.000
115.000
1.900.000
1.038.240
259.538
1.480.630
926.247
1.945.000
596.833
720.482
872.074
390.453
226.054
202.532
934.000
330.314
178.500
1.499.340
612.264
538.000
366.000
167.987
214.733
187.940
2.694.420
771.000
300.000
140.000
899.000
1.453.000
359.900
146.000
222.000
226.641
204.000
85.500
318.032
212.400
278.900
233.500
434.000
97.250
800.430
692.864
428.000
420.385
116.807
69.400
66.000
36.600
1.766.000
254.832
50.000
82.500
399.050
169.769
47.500
59.000
182.200
176.000
91.260
20.000
195.000
399.217
60.250
490.531
491.182
125.520
163.000
93.000
40.000
846.000
431.492
1.100.000
2.539.000
81.564
107.589
50.000
134.926
26.304
31.500
102.909
27.500
77.799
44.500
60.500
65.000
4.000
279.200
198.604
92.300
160.797
40.500
Dataseries Y:
3.349.512.000
2.293.231.000
11.459.000.000
3.350.727.000
2.967.930.000
2.414.300.000
555.869.000
915.349.000
1.392.842.000
912.508.000
2.696.895.000
1.872.529.000
811.130.000
1.668.100.000
292.693.000
616.318.000
1.022.672.000
655.968.000
531.872.000
199.795.000
325.562.000
174.407.000
678.367.000
525.930.000
275.386.000
666.931.000
245.958.000
144.415.000
429.686.000
827.633.000
190.304.000
336.389.000
143.000.000
263.312.000
27.601.000
92.673.000
66.179.000
51.454.000
48.889.000
53.095.000.000
12.119.000.000
3.369.407.000
9.078.000.000
2.811.901.000
1.421.529.000
2.405.711.000
1.404.567.000
742.838.000
2.719.546.000
1.401.307.000
737.423.000
420.795.000
458.963.000
307.002.000
1.088.642.000
324.610.000
214.452.000
207.004.000
305.288.000
83.814.000
449.764.000
67.885.000
42.566.440
143.729.000
97.511.941
248.815.000
84.080.000
251.355.000
49.200.000
657.238.000
397.754.000
3.219.184.000
3.081.775.000
344.567.000
241.821.000
312.636.000
552.456.000
115.427.000
183.224.468
663.656.000
225.438.000
147.144.000
635.487.000
350.201.000
62.463.000
182.023.000
182.023.000
5.127.242.000
1.963.300.000
6.273.516.000
3.566.500.000
1.352.591.000
5.317.858.000
1.165.781.000
780.290.000
1.762.400.000
1.465.720.000
680.041.000
3.123.897.000
543.058.000
80.139.887
106.442.000
296.557.000
374.145.000
219.372.000
374.800.000
116.171.000
80.944.000
56.078.000
46.177.000
18.208.000
1.361.597.000
1.069.178.000
101.186.000
407.657.000
327.579.000
233.388.000
111.597.000
120.473.000
161.930.000
59.913.000
62.155.250
25.136.000
200.700.000
25.526.452
27.777.678
252.832.000
147.470.000
84.020.000
155.002.000
28.041.000
77.755.000
87.131.376
105.568.000
128.819.000
41.129.205
14.456.000
1.021.898.000
474.828.000
21.856.000
16.598.200
26.921.000
24.153.310
172.660.729
3.583.600
57.389.000
10.254.799
64.208.000
47.915.000
13.980.000
29.471.835
246.314.000
118.105.000
75.543.000
107.946.000
3.026.000
30.594.342
34.700.000
5.482.439
330.947.000
51.700.000
7.833.000
9.548.849
52.956.000
5.829.596
1.015.236
9.765.000
37.514.000
51.748.825
38.055.000
1.600.000
22.011.000
33.726.952
6.437.036
54.839.000
48.692.339
5.827.041
11.525.000
34.469.000
2.833.345
27.322.000
224.211.000
1.437.977.000
714.151.000
2.761.149
47.133.850
955.646
13.641.221
6.652.015
1.043.000
1.375.649
4.706.424
38.806.307
3.117.144
893.367
200.000
715
5.851.600
3.154.230
10.200.000
4.477.670
500.000




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235786&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235786&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235786&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'Gwilym Jenkins' @ jenkins.wessa.net



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
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, sub=main)
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', na.rm = T)
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')
library(moments)
library(nortest)
jarque.x <- jarque.test(x)
jarque.y <- jarque.test(y)
if(lx>7) {
ad.x <- ad.test(x)
ad.y <- ad.test(y)
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Normality Tests',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('jarque.x'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('jarque.y'),'
',sep=''))
a<-table.row.end(a)
if(lx>7) {
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('ad.x'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('ad.y'),'
',sep=''))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
library(car)
bitmap(file='test2.png')
qq.plot(x,main='QQplot of variable x')
dev.off()
bitmap(file='test3.png')
qq.plot(y,main='QQplot of variable y')
dev.off()