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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationTue, 12 Nov 2013 07:55:06 -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/2013/Nov/12/t1384261073dl6az2hht6i6f9a.htm/, Retrieved Sat, 04 May 2024 11:13:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=224341, Retrieved Sat, 04 May 2024 11:13:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64

Tree of Dependent Computations

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]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IQ and Mothers Age] [2011-11-21 16:34:08] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-11 22:16:52] [35ebb7fa6f1e3e583125318bc91f18b4]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-12 00:30:30] [35ebb7fa6f1e3e583125318bc91f18b4]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-12 12:16:42] [74be16979710d4c4e7c6647856088456]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2013-11-12 12:55:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36	1
36	1
56	2
48	2
32	2
44	1
39	2
34	2
41	3
50	3
39	3
62	3
52	2
37	3
50	2
41	1
55	2
41	2
56	3
39	2
52	1
46	2
44	2
48	2
41	2
50	3
50	3
44	2
52	1
54	2
44	2
52	3
37	2
52	3
50	3
36	5
50	6
52	3
55	3
31	2
36	1
49	1
42	1
37	2
41	2
30	1
52	1
30	3
41	2
44	1
66	2
48	3
43	2
57	2
46	1
54	3
48	3
48	2
52	1
62	1
58	3
58	2
62	2
48	2
46	2
34	1
66	2
52	3
55	2
55	1
57	3
56	1
55	2
56	3
54	1
55	3
46	2
52	1
32	2
44	1
46	2
59	2
46	3
46	3
54	3
66	3
56	2
59	2
57	2
52	3
48	1
44	1
41	2
50	1
48	3
48	2
59	2
46	2
54	2
55	2
54	3
59	2
44	2
54	3
52	3
66	3
44	2
57	2
39	1
60	3
45	2
41	2
50	3
39	3
43	2
48	1
37	2
58	2
46	1
43	1
44	2
34	3
30	1
50	3
39	1
37	2
55	2
48	3
39	1
36	3
43	2
50	3
55	2
43	2
60	3
48	2
30	3
43	2
39	1
52	2
39	2
39	1
56	1
59	1
46	2
57	2
50	2
54	1
50	3
60	3
59	3
41	2
48	1
59	2
60	3
56	2
56	2
51	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224341&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224341&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224341&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
MC30VRB ~ MWARM30
means45.8162.3514.793-9.8164.184

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  MWARM30 \tabularnewline
means & 45.816 & 2.351 & 4.793 & -9.816 & 4.184 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224341&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MC30VRB  ~  MWARM30[/C][/ROW]
[ROW][C]means[/C][C]45.816[/C][C]2.351[/C][C]4.793[/C][C]-9.816[/C][C]4.184[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224341&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224341&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
MC30VRB ~ MWARM30
means45.8162.3514.793-9.8164.184






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM304634.706158.6772.3050.061
Residuals15310530.66768.828 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30 & 4 & 634.706 & 158.677 & 2.305 & 0.061 \tabularnewline
Residuals & 153 & 10530.667 & 68.828 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224341&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]MWARM30[/C][C]4[/C][C]634.706[/C][C]158.677[/C][C]2.305[/C][C]0.061[/C][/ROW]
[ROW][C]Residuals[/C][C]153[/C][C]10530.667[/C][C]68.828[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224341&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224341&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)
MWARM304634.706158.6772.3050.061
Residuals15310530.66768.828






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-12.351-2.2416.9430.62
3-14.793-0.2289.8130.069
5-1-9.816-33.01813.3860.77
6-14.184-19.01827.3860.987
3-22.442-1.8816.7650.526
5-2-12.167-35.22810.8940.592
6-21.833-21.22824.8940.999
5-3-14.609-37.7598.5410.411
6-3-0.609-23.75922.5411
6-514-18.38946.3890.755

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 2.351 & -2.241 & 6.943 & 0.62 \tabularnewline
3-1 & 4.793 & -0.228 & 9.813 & 0.069 \tabularnewline
5-1 & -9.816 & -33.018 & 13.386 & 0.77 \tabularnewline
6-1 & 4.184 & -19.018 & 27.386 & 0.987 \tabularnewline
3-2 & 2.442 & -1.881 & 6.765 & 0.526 \tabularnewline
5-2 & -12.167 & -35.228 & 10.894 & 0.592 \tabularnewline
6-2 & 1.833 & -21.228 & 24.894 & 0.999 \tabularnewline
5-3 & -14.609 & -37.759 & 8.541 & 0.411 \tabularnewline
6-3 & -0.609 & -23.759 & 22.541 & 1 \tabularnewline
6-5 & 14 & -18.389 & 46.389 & 0.755 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224341&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]2.351[/C][C]-2.241[/C][C]6.943[/C][C]0.62[/C][/ROW]
[ROW][C]3-1[/C][C]4.793[/C][C]-0.228[/C][C]9.813[/C][C]0.069[/C][/ROW]
[ROW][C]5-1[/C][C]-9.816[/C][C]-33.018[/C][C]13.386[/C][C]0.77[/C][/ROW]
[ROW][C]6-1[/C][C]4.184[/C][C]-19.018[/C][C]27.386[/C][C]0.987[/C][/ROW]
[ROW][C]3-2[/C][C]2.442[/C][C]-1.881[/C][C]6.765[/C][C]0.526[/C][/ROW]
[ROW][C]5-2[/C][C]-12.167[/C][C]-35.228[/C][C]10.894[/C][C]0.592[/C][/ROW]
[ROW][C]6-2[/C][C]1.833[/C][C]-21.228[/C][C]24.894[/C][C]0.999[/C][/ROW]
[ROW][C]5-3[/C][C]-14.609[/C][C]-37.759[/C][C]8.541[/C][C]0.411[/C][/ROW]
[ROW][C]6-3[/C][C]-0.609[/C][C]-23.759[/C][C]22.541[/C][C]1[/C][/ROW]
[ROW][C]6-5[/C][C]14[/C][C]-18.389[/C][C]46.389[/C][C]0.755[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224341&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224341&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
2-12.351-2.2416.9430.62
3-14.793-0.2289.8130.069
5-1-9.816-33.01813.3860.77
6-14.184-19.01827.3860.987
3-22.442-1.8816.7650.526
5-2-12.167-35.22810.8940.592
6-21.833-21.22824.8940.999
5-3-14.609-37.7598.5410.411
6-3-0.609-23.75922.5411
6-514-18.38946.3890.755






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group41.1080.355
153 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 1.108 & 0.355 \tabularnewline
  & 153 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=224341&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]4[/C][C]1.108[/C][C]0.355[/C][/ROW]
[ROW][C] [/C][C]153[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=224341&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=224341&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)
Group41.1080.355
153


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')