FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationFri, 12 Dec 2014 08:24:13 +0000
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/Dec/12/t1418372680sgwestwkso9z8hq.htm/, Retrieved Thu, 16 May 2024 09:24:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266440, Retrieved Thu, 16 May 2024 09:24:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA 1] [2014-12-12 08:24:13] [a0dc8dfb1ad11084a66a61bab0a3c2c7] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	26
1	57
0	37
1	67
1	43
1	52
0	52
1	43
1	84
1	67
1	49
1	70
1	52
0	58
0	68
0	62
1	43
0	56
1	56
0	74
1	65
1	63
0	58
1	57
1	63
1	53
1	57
0	51
1	64
0	53
0	29
0	54
1	51
1	58
1	43
1	51
1	53
0	54
1	56
1	61
0	47
1	39
1	48
1	50
1	35
1	30
0	68
1	49
1	61
0	67
1	47
1	56
1	50
1	43
1	67
1	62
1	57
0	41
1	54
0	45
1	48
1	61
0	56
0	41
1	43
0	53
1	44
0	66
1	58
1	46
0	37
0	51
0	51
0	56
1	66
1	45
0	37
1	59
0	42
1	38
0	66
0	34
1	53
0	49
0	55
0	49
1	59
0	40
1	58
1	60
0	63
0	56
0	54
1	52
1	34
1	69
0	32
1	48
0	67
1	58
1	57
1	42
1	64
1	58
0	66
1	26
1	61
1	52
0	51
0	55
0	50
0	60
0	56
0	63
1	61
1	52
1	16
1	46
1	56
0	52
1	55
1	50
0	59
1	60
0	52
0	44
1	67
1	52
1	55
1	37
1	54
1	72
1	51
1	48
0	60
1	50
1	63
1	33
1	67
1	46
1	54
0	59
1	61
1	33
1	47
1	69
1	52
0	55
0	55
0	41
1	73
0	51
0	52
0	50
1	51
0	60
1	56
1	56
0	29
1	66
1	66
1	73
0	55
0	64
0	40
0	46
1	58
0	43
1	61
0	51
1	50
0	52
1	54
0	66
0	61
1	80
0	51
1	56
1	56
1	56
1	53
1	47
0	25
1	47
0	46
0	50
0	39
1	51
0	58
1	35
0	58
0	60
0	62
0	63
1	53
1	46
1	67
1	59
0	64
0	38
1	50
0	48
0	48
0	47
0	66
1	47
1	63
0	58
0	44
1	51
0	43
1	55
1	38
1	56
0	45
1	50
1	54
1	57
0	60
0	55
0	56
1	49
1	37
0	43
1	59
1	46
0	51
0	58
0	64
1	53
1	48
0	51
0	47
0	59
1	62
1	62
0	51
0	64
0	52
1	67
1	50
1	54
1	58
0	56
1	63
1	31
1	65
0	71
0	50
1	57
0	47
1	54
1	47
1	57
0	43
1	41
0	63
1	63
1	56
0	51
1	50
0	22
1	41
0	59
1	56
0	66
0	53
1	42
1	52
0	54
1	44
1	62
0	53
1	50
0	36
0	76
1	66
1	62
0	59
1	47
0	55
0	58
1	60
0	44
0	57
1	45
1	58
1	51
0	57
1	30
1	46
1	51
1	56
0	58
1	44
0	14
0	53
1	42
0	49
1	44
0	62
0	30
1	46
0	56
1	50
1	54
0	48
0	55
0	35
1	55
0	41
1	59
1	54
1	66
1	55
0	45
1	51
0	47
1	42
0	53
0	53
0	41
0	55
0	55
0	46
1	63
1	43
1	65
0	59
0	39
0	44
0	60
0	57
1	67
1	52
1	52
1	69
0	46
1	46
0	53
1	40
1	70
0	54
1	77
0	45
0	60
0	47
0	50
0	66
0	60
1	41
0	53
0	34
1	51
1	69
1	60
1	45
0	58
1	39
1	51
0	52
0	49
0	63
0	44
1	51
0	52
0	60
0	53
0	53
0	52
0	31
1	51
1	65
1	51
0	49
0	61
1	58
0	62
1	54
1	52
1	72
1	50
1	65
0	53
0	56
0	63
0	62
0	66
1	50
0	45
0	58
1	52
0	53
0	68
1	59
0	58
1	52
1	45
0	58
1	70
0	69
1	71
0	46
1	58
1	39
1	46
0	64
1	67
1	44
0	54
1	41
1	68
1	63
1	57
0	61
1	39
0	69
0	64
1	38
0	59
1	51
1	59
0	51
0	65
1	47
1	50
1	57
1	21
0	47
1	51
1	37
1	67
1	43
0	58
0	51
1	40
0	41
1	58
1	64
0	64
1	58
0	50
1	59
0	55
0	59
1	58
1	41
1	56
1	63
0	77
0	60
1	58
0	64
1	47
0	46
1	62
1	60
1	50
1	46
1	44
1	58
1	56
1	43
0	54
1	54
0	56
0	65
1	66
1	62
1	58
1	67
1	25
1	56
1	53
0	56
1	59
1	46
1	49
0	56
1	76
1	33
1	49
1	53
0	58
1	72
1	51
0	42
0	69
1	51
1	54
1	52
1	59
0	51
1	67
0	64
1	58
1	53

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266440&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266440&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266440&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
I ~ G
means53.0280.524

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
I  ~  G \tabularnewline
means & 53.028 & 0.524 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266440&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]I  ~  G[/C][/ROW]
[ROW][C]means[/C][C]53.028[/C][C]0.524[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266440&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266440&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:

ANOVA Model
I ~ G
means53.0280.524






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
G133.5133.510.3270.568
Residuals49550795.335102.617 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
G & 1 & 33.51 & 33.51 & 0.327 & 0.568 \tabularnewline
Residuals & 495 & 50795.335 & 102.617 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266440&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]G[/C][C]1[/C][C]33.51[/C][C]33.51[/C][C]0.327[/C][C]0.568[/C][/ROW]
[ROW][C]Residuals[/C][C]495[/C][C]50795.335[/C][C]102.617[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266440&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266440&T=2

As an alternative you can also use a QR Code:  
QR Code


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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
G133.5133.510.3270.568
Residuals49550795.335102.617






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.524-1.2772.3250.568

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 0.524 & -1.277 & 2.325 & 0.568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266440&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]1-0[/C][C]0.524[/C][C]-1.277[/C][C]2.325[/C][C]0.568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266440&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266440&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-00.524-1.2772.3250.568






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.2140.644
495 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.214 & 0.644 \tabularnewline
  & 495 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266440&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]1[/C][C]0.214[/C][C]0.644[/C][/ROW]
[ROW][C] [/C][C]495[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266440&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266440&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.2140.644
495


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = TRUE ;
R code (references can be found in the software module):
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-leveneTest(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')