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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 computationWed, 07 Dec 2011 09:08:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/07/t1323268228qf16dszvkkcd7bw.htm/, Retrieved Thu, 02 May 2024 19:03:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152444, Retrieved Thu, 02 May 2024 19:03:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

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)] [Treatment Groups ...] [2011-12-07 14:08:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.2166	6 
0.2954	6 
0.3253	6 
0.4188	6 
0.4442	6 
0.4301	6 
0.3232	6 
0.2949	6 
0.3086	6 
0.3064	6 
0.3246	6 
0.2939	6 
0.2086	6 
0.1942	6 
0.2763	6 
0.2548	6 
0.3079	12
0.3433	12 
0.2973	12 
0.3564	12 
0.4907	12 
0.2426	12 
0.2379	12 
0.2825	12 
0.3229	12 
0.3171	12 
0.3022	12 
0.3136	12 
0.3222	12 
0.3093	12 
0.3178	12 
0.256	12 
0.3667	18 
0.3748	18 
0.3912	18 
0.3764	18 
0.4179	18 
0.3602	18 
0.3588	18 
0.3183	18 
0.3288	18 
0.3348	18 
0.3022	18 
0.3044	18 
0.2917	18 
0.3236	18 
0.3041	18 
0.3207	18 
0.3875	24 
0.3763	24 
0.4772	24 
0.4086	24 
0.3488	24 
0.3001	24 
0.3259	24 
0.3383	24 
0.3464	24 
0.335	24 
0.3461	24 
0.347	24 
0.339	24 
0.3051	24 
0.3197	24 
0.3226	24 
0.367	30 
0.387	30 
0.3703	30 
0.358	30 
0.3616	30 
0.3356	30 
0.3498	30 
0.3368	30 
0.3317	30 
0.3393	30 
0.2997	30 
0.2874	30 
0.2936	30 
0.2861	30 
0.2746	30 
0.276	30 
0.4088	36 
0.4216	36 
0.3829	36 
0.3326	36 
0.2806	36 
0.3449	36 
0.3492	36 
0.3609	36 
0.3849	36 
0.3527	36 
0.325	36 
0.3252	36 
0.3026	36 
0.2894	36 
0.3184	36 
0.3126	36

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'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152444&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152444&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'AstonUniversity' @ aston.wessa.net






ANOVA Model
Response ~ Treatment
means0.3140.0280.0380.0150.03-0.006

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Response  ~  Treatment \tabularnewline
means & 0.314 & 0.028 & 0.038 & 0.015 & 0.03 & -0.006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152444&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Response  ~  Treatment[/C][/ROW]
[ROW][C]means[/C][C]0.314[/C][C]0.028[/C][C]0.038[/C][C]0.015[/C][C]0.03[/C][C]-0.006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152444&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
Response ~ Treatment
means0.3140.0280.0380.0150.03-0.006






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Treatment50.0250.0051.9880.088
Residuals900.2270.003 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Treatment & 5 & 0.025 & 0.005 & 1.988 & 0.088 \tabularnewline
Residuals & 90 & 0.227 & 0.003 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152444&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]Treatment[/C][C]5[/C][C]0.025[/C][C]0.005[/C][C]1.988[/C][C]0.088[/C][/ROW]
[ROW][C]Residuals[/C][C]90[/C][C]0.227[/C][C]0.003[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152444&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)
Treatment50.0250.0051.9880.088
Residuals900.2270.003






Tukey Honest Significant Difference Comparisons
difflwruprp adj
18-120.028-0.0230.080.599
24-120.038-0.0140.0890.283
30-120.015-0.0370.0660.962
36-120.03-0.0220.0810.558
6-12-0.006-0.0580.0450.999
24-180.009-0.0420.0610.995
30-18-0.014-0.0650.0380.971
36-180.001-0.0510.0531
6-18-0.035-0.0870.0170.368
30-24-0.023-0.0750.0290.784
36-24-0.008-0.060.0430.997
6-24-0.044-0.0960.0070.137
36-300.015-0.0370.0670.96
6-30-0.021-0.0730.030.839
6-36-0.036-0.0880.0160.333

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
18-12 & 0.028 & -0.023 & 0.08 & 0.599 \tabularnewline
24-12 & 0.038 & -0.014 & 0.089 & 0.283 \tabularnewline
30-12 & 0.015 & -0.037 & 0.066 & 0.962 \tabularnewline
36-12 & 0.03 & -0.022 & 0.081 & 0.558 \tabularnewline
6-12 & -0.006 & -0.058 & 0.045 & 0.999 \tabularnewline
24-18 & 0.009 & -0.042 & 0.061 & 0.995 \tabularnewline
30-18 & -0.014 & -0.065 & 0.038 & 0.971 \tabularnewline
36-18 & 0.001 & -0.051 & 0.053 & 1 \tabularnewline
6-18 & -0.035 & -0.087 & 0.017 & 0.368 \tabularnewline
30-24 & -0.023 & -0.075 & 0.029 & 0.784 \tabularnewline
36-24 & -0.008 & -0.06 & 0.043 & 0.997 \tabularnewline
6-24 & -0.044 & -0.096 & 0.007 & 0.137 \tabularnewline
36-30 & 0.015 & -0.037 & 0.067 & 0.96 \tabularnewline
6-30 & -0.021 & -0.073 & 0.03 & 0.839 \tabularnewline
6-36 & -0.036 & -0.088 & 0.016 & 0.333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152444&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]18-12[/C][C]0.028[/C][C]-0.023[/C][C]0.08[/C][C]0.599[/C][/ROW]
[ROW][C]24-12[/C][C]0.038[/C][C]-0.014[/C][C]0.089[/C][C]0.283[/C][/ROW]
[ROW][C]30-12[/C][C]0.015[/C][C]-0.037[/C][C]0.066[/C][C]0.962[/C][/ROW]
[ROW][C]36-12[/C][C]0.03[/C][C]-0.022[/C][C]0.081[/C][C]0.558[/C][/ROW]
[ROW][C]6-12[/C][C]-0.006[/C][C]-0.058[/C][C]0.045[/C][C]0.999[/C][/ROW]
[ROW][C]24-18[/C][C]0.009[/C][C]-0.042[/C][C]0.061[/C][C]0.995[/C][/ROW]
[ROW][C]30-18[/C][C]-0.014[/C][C]-0.065[/C][C]0.038[/C][C]0.971[/C][/ROW]
[ROW][C]36-18[/C][C]0.001[/C][C]-0.051[/C][C]0.053[/C][C]1[/C][/ROW]
[ROW][C]6-18[/C][C]-0.035[/C][C]-0.087[/C][C]0.017[/C][C]0.368[/C][/ROW]
[ROW][C]30-24[/C][C]-0.023[/C][C]-0.075[/C][C]0.029[/C][C]0.784[/C][/ROW]
[ROW][C]36-24[/C][C]-0.008[/C][C]-0.06[/C][C]0.043[/C][C]0.997[/C][/ROW]
[ROW][C]6-24[/C][C]-0.044[/C][C]-0.096[/C][C]0.007[/C][C]0.137[/C][/ROW]
[ROW][C]36-30[/C][C]0.015[/C][C]-0.037[/C][C]0.067[/C][C]0.96[/C][/ROW]
[ROW][C]6-30[/C][C]-0.021[/C][C]-0.073[/C][C]0.03[/C][C]0.839[/C][/ROW]
[ROW][C]6-36[/C][C]-0.036[/C][C]-0.088[/C][C]0.016[/C][C]0.333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152444&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152444&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
18-120.028-0.0230.080.599
24-120.038-0.0140.0890.283
30-120.015-0.0370.0660.962
36-120.03-0.0220.0810.558
6-12-0.006-0.0580.0450.999
24-180.009-0.0420.0610.995
30-18-0.014-0.0650.0380.971
36-180.001-0.0510.0531
6-18-0.035-0.0870.0170.368
30-24-0.023-0.0750.0290.784
36-24-0.008-0.060.0430.997
6-24-0.044-0.0960.0070.137
36-300.015-0.0370.0670.96
6-30-0.021-0.0730.030.839
6-36-0.036-0.0880.0160.333






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group51.10.366
90 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 5 & 1.1 & 0.366 \tabularnewline
  & 90 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152444&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]5[/C][C]1.1[/C][C]0.366[/C][/ROW]
[ROW][C] [/C][C]90[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152444&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152444&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)
Group51.10.366
90


Figures (Output of Computation)

Input Parameters & R Code

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):
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()
}
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<-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')