Free Statistics

of Irreproducible Research!

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, 12 Dec 2017 09:30:41 +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/2017/Dec/12/t15130674642iowtg9v8m7ohu4.htm/, Retrieved Thu, 31 Oct 2024 23:45:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309034, Retrieved Thu, 31 Oct 2024 23:45:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
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)] [1 WAY ANOVA ] [2017-12-12 08:30:41] [fda4350e119ddbaf0177fa3308cc9af4] [Current]
Feedback Forum

Post a new message
Dataseries X:
127	'AA'
129	'AA'
131	'AA'
132	'AA'
132	'AA'
136	'AA'
137	'AA'
137	'AA'
141	'AA'
142	'AA'
144	'AA'
149	'AA'
158	'AA'
159	'AA'
190	'AA'
192	'AA'
208	'AA'
216	'AA'
242	'AA'
249	'AA'
290	'AA'
306	'AA'
610	'AA'
782	'AA'
120	'AA'
126	'AA'
133	'AA'
135	'AA'
142	'AA'
145	'AA'
191	'AA'
192	'AA'
228	'AA'
244	'AA'
343	'AA'
134	'AA'
138	'AA'
140	'AA'
142	'B6'
155	'B6'
179	'B6'
179	'B6'
293	'B6'
430	'B6'
659	'B6'
924	'B6'
133,00	'B6'
135,00	'B6'
135,00	'B6'
137,00	'B6'
139,00	'B6'
140,00	'B6'
142,00	'B6'
142,00	'B6'
143,00	'B6'
145,00	'B6'
147,00	'B6'
148,00	'B6'
150,00	'B6'
153,00	'B6'
154,00	'B6'
157,00	'B6'
158,00	'B6'
175,00	'B6'
178,00	'B6'
178,00	'B6'
190,00	'B6'
191,00	'B6'
192,00	'B6'
192,00	'B6'
193,00	'B6'
195,00	'B6'
195,00	'B6'
207,00	'B6'
218,00	'B6'
219,00	'B6'
224,00	'B6'
227,00	'B6'
228,00	'B6'
234,00	'B6'
234,00	'B6'
242,00	'B6'
244,00	'B6'
259,00	'B6'
273,00	'B6'
286,00	'B6'
291,00	'B6'
343,00	'B6'
568,00	'B6'
134,00	'DL'
134,00	'DL'
138,00	'DL'
140,00	'DL'
142,00	'DL'
144,00	'DL'
155,00	'DL'
167,00	'DL'
177,00	'DL'
179,00	'DL'
179,00	'DL'
182,00	'DL'
210,00	'DL'
224,00	'DL'
248,00	'DL'
273,00	'DL'
293,00	'DL'
410,00	'DL'
430,00	'DL'
452,00	'DL'
454,00	'DL'
520,00	'DL'
586,00	'DL'
617,00	'DL'
659,00	'DL'
759,00	'DL'
924,00	'DL'
941,00	'DL'
11,26	'DL'




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309034&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]4 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309034&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309034&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Delay ~ Carrier
means201.31626.037139.452

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Delay  ~  Carrier \tabularnewline
means & 201.316 & 26.037 & 139.452 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309034&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Delay  ~  Carrier[/C][/ROW]
[ROW][C]means[/C][C]201.316[/C][C]26.037[/C][C]139.452[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309034&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309034&T=1

As an alternative you can also use a QR Code:  

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

ANOVA Model
Delay ~ Carrier
means201.31626.037139.452







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Carrier2353969.613176984.8065.9750.003
Residuals1153406333.75929620.294

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Carrier & 2 & 353969.613 & 176984.806 & 5.975 & 0.003 \tabularnewline
Residuals & 115 & 3406333.759 & 29620.294 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309034&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]Carrier[/C][C]2[/C][C]353969.613[/C][C]176984.806[/C][C]5.975[/C][C]0.003[/C][/ROW]
[ROW][C]Residuals[/C][C]115[/C][C]3406333.759[/C][C]29620.294[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309034&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309034&T=2

As an alternative you can also use a QR Code:  

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

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Carrier2353969.613176984.8065.9750.003
Residuals1153406333.75929620.294







Tukey Honest Significant Difference Comparisons
difflwruprp adj
B6-AA26.037-61.537113.6110.76
DL-AA139.45238.688240.2150.004
DL-B6113.41518.372208.4570.015

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
B6-AA & 26.037 & -61.537 & 113.611 & 0.76 \tabularnewline
DL-AA & 139.452 & 38.688 & 240.215 & 0.004 \tabularnewline
DL-B6 & 113.415 & 18.372 & 208.457 & 0.015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309034&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]B6-AA[/C][C]26.037[/C][C]-61.537[/C][C]113.611[/C][C]0.76[/C][/ROW]
[ROW][C]DL-AA[/C][C]139.452[/C][C]38.688[/C][C]240.215[/C][C]0.004[/C][/ROW]
[ROW][C]DL-B6[/C][C]113.415[/C][C]18.372[/C][C]208.457[/C][C]0.015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309034&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309034&T=3

As an alternative you can also use a QR Code:  

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

Tukey Honest Significant Difference Comparisons
difflwruprp adj
B6-AA26.037-61.537113.6110.76
DL-AA139.45238.688240.2150.004
DL-B6113.41518.372208.4570.015







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group27.0130.001
115

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 7.013 & 0.001 \tabularnewline
  & 115 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309034&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]2[/C][C]7.013[/C][C]0.001[/C][/ROW]
[ROW][C] [/C][C]115[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309034&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309034&T=4

As an alternative you can also use a QR Code:  

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

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group27.0130.001
115



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