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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hypothesisprop2.wasp
Title produced by softwareTesting Population Proportion - P-Value
Date of computationTue, 25 Mar 2014 18:47:37 -0400
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/Mar/25/t139578773893b7dswamme1ge4.htm/, Retrieved Tue, 14 May 2024 20:30:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234360, Retrieved Tue, 14 May 2024 20:30:44 +0000
QR Codes:

Original text written by user:This test shows that the use of five peremptory challenges to four African-American jurors would be statistically significant if the jury venire were 43 percent African American.
IsPrivate?No (this computation is public)
User-defined keywordsBatson, Wheeler, peremptory challenges, peremptory strikes, peremptories, racial discrimination, jury selection
Estimated Impact184

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Testing Population Proportion - P-Value] [Statistical Signi...] [2014-03-25 22:47:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Tables (Output of Computation)





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=234360&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=234360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234360&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Testing Population Proportion (normal approximation)
Sample size5
Sample proportion0.8
Null hypothesis0.43
Type I error (alpha)0.05
p-value (1-sided)0.0473461645011979

\begin{tabular}{lllllllll}
\hline
Testing Population Proportion (normal approximation) \tabularnewline
Sample size & 5 \tabularnewline
Sample proportion & 0.8 \tabularnewline
Null hypothesis & 0.43 \tabularnewline
Type I error (alpha) & 0.05 \tabularnewline
p-value (1-sided) & 0.0473461645011979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234360&T=1

[TABLE]
[ROW][C]Testing Population Proportion (normal approximation)[/C][/ROW]
[ROW][C]Sample size[/C][C]5[/C][/ROW]
[ROW][C]Sample proportion[/C][C]0.8[/C][/ROW]
[ROW][C]Null hypothesis[/C][C]0.43[/C][/ROW]
[ROW][C]Type I error (alpha)[/C][C]0.05[/C][/ROW]
[ROW][C]p-value (1-sided)[/C][C]0.0473461645011979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234360&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:

Testing Population Proportion (normal approximation)
Sample size5
Sample proportion0.8
Null hypothesis0.43
Type I error (alpha)0.05
p-value (1-sided)0.0473461645011979


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = .75 ; par3 = 0.31 ; par4 = 0.05 ;
Parameters (R input):
par1 = 5 ; par2 = .8 ; par3 = 0.43 ; par4 = 0.05 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
u <- (par2 - par3) / sqrt(par3 * (1-par3) / par1)
pu <- pnorm(-abs(u))
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Testing Population Proportion (normal approximation)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample size',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Sample proportion',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Null hypothesis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error (alpha)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value (1-sided)',header=TRUE)
a<-table.element(a,pu)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')