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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software ModuleRscript (source code is shown below)
Title produced by softwareR console
Date of computationMon, 06 Jul 2009 00:49:57 -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/2009/Jul/06/t1246862999odwh34bz66dnt0p.htm/, Retrieved Fri, 17 May 2024 10:16:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42339, Retrieved Fri, 17 May 2024 10:16:30 +0000
QR Codes:

Original text written by user:This is the first time that UseR is blogging a computation.
IsPrivate?No (this computation is public)
User-defined keywordstutorial test
Estimated Impact508

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [R console] [my first computation] [2009-07-06 06:49:57] [256f657a32c6b2b7628dddcfa9a822d0] [Current]
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Dataset

Tables (Output of Computation)

> {
+     x <- rnorm(150)
+     y <- rnorm(150)
+     print(cor.test(x, y))
+     plot(x, y)
+ }

	Pearson's product-moment correlation

data:  x and y 
t = -1.5048, df = 148, p-value = 0.1345
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.27755888  0.03825629 
sample estimates:
       cor 
-0.1227579

Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (body of R function):
{
    x <- rnorm(150)
    y <- rnorm(150)
    print(cor.test(x, y))
    
    plot(x, y)
    
}