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 computationTue, 16 Dec 2014 23:15:19 +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/16/t1418772058d9vn2kcybroa845.htm/, Retrieved Thu, 16 May 2024 14:26:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269972, Retrieved Thu, 16 May 2024 14:26:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact49

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2010-11-01 13:13:29] [b98453cac15ba1066b407e146608df68]
- RMP   [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 07:51:16] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-12-16 23:15:19] [6870495cd5e22452491bd29e9b20b7c8] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3	15.25
3	11.7
4	18.55
4	9.5
7	14.75
9	10.9
10	10.4
11	12.4
12	12.6
12	11.9
13	14.3
13	11.7
14	12.6
14	15.6
14	14.35
15	6.4
15	10.0
15	11.8
15	12.6
15	13.6
16	6.4
16	11.5
16	8.3
16	12.7
16	13.0
16	13.6
16	14.8
16	14.35
16	19.1
16	9.85
16	15.6
16	17.1
16	13.6
17	14.5
17	9.9
17	13.6
17	17.6
18	7.4
18	6.3
18	13.8
18	9.7
18	13.3
18	11.1
18	13.35
18	18.4
18	17.75
19	8.2
19	12.0
19	11.7
19	10.9
19	15.9
19	9.2
19	13.0
19	11.4
19	10.6
19	16.15
19	14.75
19	12.45
19	12.65
19	16.1
19	16.85
19	17.1
19	19.3
19	19.05
19	13.35
19	11.95
20	14.8
20	10.6
20	11.9
20	13.2
20	16.2
20	17.75
20	17.65
20	13.35
20	7.6
20	12.75
20	19.1
20	12.85
20	14.05
21	12.9
21	11.1
21	9.3
21	10.8
21	10.3
21	7.6
21	18.1
21	8.6
22	12.2
22	12.8
22	13.3
22	11.4
22	9.3
22	12.7
22	18.4
22	16.1
22	7.7
23	6.7
23	13.8
23	9.9
23	10.8
23	5.9
23	11.4
23	11.3
23	12.5
23	4.35
23	19.1
23	16.1
23	14.7
23	17.35
23	17.65
23	16.35
23	15.6
23	16.1
23	19.25
23	15.25
23	18.15
23	18.4
23	17.75
23	14.6

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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269972&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269972&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269972&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 Ronald Aylmer Fisher' @ fisher.wessa.net






ANOVA Model
EX ~ NUM
means10.412.412.251314.18310.8813.06913.912.34413.6313.98511.08712.65614.04313.47514.02514.7510.9

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline EX ~ NUM \tabularnewline means & 10.4 & 12.4 & 12.25 & 13 & 14.183 & 10.88 & 13.069 & 13.9 & 12.344 & 13.63 & 13.985 & 11.087 & 12.656 & 14.043 & 13.475 & 14.025 & 14.75 & 10.9 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=269972&T=1

[TABLE]
[ROW]
ANOVA Model[/C][/ROW] [ROW]EX ~ NUM[/C][/ROW] [ROW][C]means[/C][C]10.4[/C][C]12.4[/C][C]12.25[/C][C]13[/C][C]14.183[/C][C]10.88[/C][C]13.069[/C][C]13.9[/C][C]12.344[/C][C]13.63[/C][C]13.985[/C][C]11.087[/C][C]12.656[/C][C]14.043[/C][C]13.475[/C][C]14.025[/C][C]14.75[/C][C]10.9[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=269972&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269972&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
EX ~ NUM
means10.412.412.251314.18310.8813.06913.912.34413.6313.98511.08712.65614.04313.47514.02514.7510.9






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
NUM1820772.0271154.00191.9320
Residuals1011267.82812.553 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
NUM & 18 & 20772.027 & 1154.001 & 91.932 & 0 \tabularnewline
Residuals & 101 & 1267.828 & 12.553 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269972&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]NUM[/C][C]18[/C][C]20772.027[/C][C]1154.001[/C][C]91.932[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]101[/C][C]1267.828[/C][C]12.553[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269972&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269972&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)
NUM1820772.0271154.00191.9320
Residuals1011267.82812.553






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269972&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269972&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269972&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:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group170.8350.65
101 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 17 & 0.835 & 0.65 \tabularnewline
  & 101 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269972&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]17[/C][C]0.835[/C][C]0.65[/C][/ROW]
[ROW][C] [/C][C]101[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269972&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269972&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)
Group170.8350.65
101


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = FALSE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '2'
par1 <- '1'
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')