Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software ModuleIan.Hollidayrwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 25 Nov 2010 11:41:02 +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/2010/Nov/25/t1290685341el8gw7idcbkmaxk.htm/, Retrieved Sat, 03 Dec 2022 16:33:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=100809, Retrieved Sat, 03 Dec 2022 16:33:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA wit...] [2009-11-29 13:09:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Chi Square Measure of Association- Free Statistics Software (Calculator)] [One Way ANOVA for...] [2009-12-01 13:05:10] [3fdd735c61ad38cbc9b3393dc997cdb7]
- R P     [Chi Square Measure of Association- Free Statistics Software (Calculator)] [CARE date with Tu...] [2009-12-01 18:33:48] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [CARE Data with Tu...] [2010-11-23 12:09:38] [3fdd735c61ad38cbc9b3393dc997cdb7]
-   PD          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [compendium 8.1] [2010-11-25 11:41:02] [15eab2c43e9c2ac9cd9b0628e098f0c4] [Current]
Feedback Forum

Post a new message
Dataseries X:
1	86	6	36	88
3	86	8	56	94
3	103	8	48	90
3	74	7	32	73
1	63	5	44	68
2	82	7	39	80
3	93	8	34	86
3	77	9	41	86
2	111	9	50	91
1	71	3	39	79
1	103	9	62	96
3	89	7	52	92
3	75	9	37	72
3	88	8	50	96
1	84	6	41	70
3	85	7	55	86
3	70	8	41	87
3	104	9	56	88
2	88	7	39	79
2	77	6	52	90
1	77	8	46	95
1	72	7	44	85
3	83	8	41	90
1	110	9	50	115
1	91	9	50	84
3	80	7	44	79
1	91	4	52	94
2	86	7	54	97
3	85	7	44	86
2	107	9	52	111
2	93	7	37	87
3	87	9	52	98
1	84	10	50	87
3	73	5	36	68
3	84	6	50	88
1	86	9	52	82
2	99	9	55	111
1	75	8	31	75
1	87	6	36	94
2	79	6	49	95
1	82	5	42	80
1	95	8	37	95
3	84	8	41	68
2	85	5	30	94
2	95	6	52	88
1	63	9	30	84
1	85	4	44	101
1	86	8	66	98
2	75	9	48	78
3	98	7	43	109
3	71	7	57	102
3	63	6	46	81
3	71	9	54	97
2	84	9	48	75
2	81	8	48	97
3	79	6	62	101
3	63	10	58	101
2	93	8	58	95
2	92	7	62	95
3	83	8	46	95
2	80	3	34	90
3	111	8	66	107
3	92	10	52	92
2	79	7	55	86
2	69	5	55	70
3	83	10	57	95
3	80	5	56	96
2	91	8	55	91
1	97	9	56	87
2	85	6	54	92
2	85	9	55	97
2	99	8	46	102
2	67	5	52	91
3	87	8	32	68
2	68	3	44	88
3	81	7	46	97
1	80	8	59	90
3	93	10	46	101
3	93	9	46	94
1	102	10	54	101
1	104	9	66	109
2	90	8	56	100
1	85	8	59	103
3	92	8	57	94
1	82	9	52	97
3	85	4	48	85
2	89	6	44	75
3	77	7	41	77
1	79	4	50	87
1	76	9	48	78
2	101	7	48	108
3	81	8	59	97
3	89	8	46	106
1	81	7	54	107
2	77	7	55	95
2	95	9	54	107
3	85	8	59	115
3	81	8	44	101
1	76	9	54	85
3	93	9	52	90
3	104	10	66	115
3	89	7	44	95
2	76	8	57	97
3	77	5	39	112
3	71	9	60	97
3	79	8	45	77
3	89	7	41	90
1	81	8	50	94
3	99	8	39	103
1	81	7	43	77
3	84	6	48	98
3	85	7	37	90
3	111	7	58	111
2	78	6	46	77
3	111	6	43	88
2	78	7	44	75
3	87	9	34	92
2	92	6	30	78
2	93	10	50	106
2	70	4	39	80
3	84	8	37	87
3	75	7	55	92
3	85	5	39	86
3	87	9	36	85
2	75	8	43	90
1	103	9	50	101
3	86	8	55	94
3	77	8	43	86
3	74	9	60	86
2	74	8	48	90
1	76	9	30	75
3	83	7	43	86
3	101	6	39	91
3	83	8	52	97
2	92	6	39	91
3	74	5	39	70
2	87	3	56	98
3	71	6	59	96
3	79	8	46	95
2	83	7	57	100
3	80	8	50	95
3	90	6	54	97
3	80	9	50	97
3	96	9	60	92
1	109	10	59	115
3	98	7	41	88
2	85	5	48	87
3	83	8	59	100
3	86	9	60	98
1	72	8	56	102
3	75	4	51	96




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100809&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100809&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100809&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







ANOVA Model
MC30VRB ~ MOMAGE
means48.3430.157-0.167

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MOMAGE \tabularnewline
means & 48.343 & 0.157 & -0.167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100809&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MOMAGE[/C][/ROW]
[ROW][C]means[/C][C]48.343[/C][C]0.157[/C][C]-0.167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100809&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100809&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
MC30VRB ~ MOMAGE
means48.3430.157-0.167







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MOMAGE22.8851.4420.020.981
Residuals14810885.10273.548

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MOMAGE & 2 & 2.885 & 1.442 & 0.02 & 0.981 \tabularnewline
Residuals & 148 & 10885.102 & 73.548 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100809&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]MOMAGE[/C][C]2[/C][C]2.885[/C][C]1.442[/C][C]0.02[/C][C]0.981[/C][/ROW]
[ROW][C]Residuals[/C][C]148[/C][C]10885.102[/C][C]73.548[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100809&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100809&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)
MOMAGE22.8851.4420.020.981
Residuals14810885.10273.548







Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-10.157-4.494.8040.996
3-1-0.167-4.3323.9980.995
3-2-0.324-4.2473.5980.979

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 0.157 & -4.49 & 4.804 & 0.996 \tabularnewline
3-1 & -0.167 & -4.332 & 3.998 & 0.995 \tabularnewline
3-2 & -0.324 & -4.247 & 3.598 & 0.979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100809&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]2-1[/C][C]0.157[/C][C]-4.49[/C][C]4.804[/C][C]0.996[/C][/ROW]
[ROW][C]3-1[/C][C]-0.167[/C][C]-4.332[/C][C]3.998[/C][C]0.995[/C][/ROW]
[ROW][C]3-2[/C][C]-0.324[/C][C]-4.247[/C][C]3.598[/C][C]0.979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100809&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100809&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
2-10.157-4.494.8040.996
3-1-0.167-4.3323.9980.995
3-2-0.324-4.2473.5980.979







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.9980.371
148

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.998 & 0.371 \tabularnewline
  & 148 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=100809&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]0.998[/C][C]0.371[/C][/ROW]
[ROW][C] [/C][C]148[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=100809&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=100809&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)
Group20.9980.371
148



Parameters (Session):
par1 = 4 ; par2 = 1 ; par3 = TRUE ;
Parameters (R input):
par1 = 4 ; 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){
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
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<-levene.test(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')