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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 computationMon, 11 Nov 2013 09:08:42 -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/11/t1384178938xxye2sek4ahw7dw.htm/, Retrieved Fri, 03 May 2024 14:01:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=223899, Retrieved Fri, 03 May 2024 14:01:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

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)] [MOMAGE AND IQ AT ...] [2013-11-10 18:24:00] [64170401b557979db6e7469620652d25]
- R  D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [H] [2013-11-11 13:58:50] [64170401b557979db6e7469620652d25]
- R  D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [IJKI] [2013-11-11 14:08:42] [0bd2f83192fbb218ef9d5de6049875e0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88	1
94	2
90	2
73	2
68	1
80	2
86	2
86	3
91	3
79	1
96	3
92	2
72	3
96	2
70	1
86	2
87	2
88	3
79	2
90	1
95	2
85	2
90	2
115	3
84	3
79	2
94	1
97	2
86	2
111	3
87	2
98	3
87	3
68	1
88	1
82	3
111	3
75	2
94	1
95	1
80	1
95	2
68	2
94	1
88	1
84	3
101	1
98	2
78	3
109	2
102	2
81	1
97	3
75	3
97	2
101	1
101	3
95	2
95	2
95	2
90	1
107	2
92	3
86	2
70	1
95	3
96	1
91	2
87	2
92	1
97	3
102	2
91	1
68	2
88	1
97	2
90	2
101	3
94	3
101	3
109	3
100	2
103	2
94	2
97	3
85	1
75	1
77	2
87	1
78	3
108	2
97	2
106	2
107	2
95	2
107	3
115	2
101	2
85	3
90	3
115	3
95	2
97	2
112	1
97	3
77	2
90	2
94	2
103	2
77	2
98	2
90	1
111	7
77	1
88	1
75	2
92	3
78	1
106	3
80	1
87	2
92	2
86	1
85	3
90	2
101	3
94	2
86	2
86	3
90	2
75	3
86	2
91	1
97	2
91	1
70	1
98	1
96	1
95	2
100	2
95	2
97	1
97	3
92	3
115	3
88	2
87	1
100	2
98	2
102	2
96	4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223899&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223899&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223899&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






ANOVA Model
WISCRY7 ~ MWARM30
means87.0265.0897.0498.97423.974

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7  ~  MWARM30
 \tabularnewline
means & 87.026 & 5.089 & 7.049 & 8.974 & 23.974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223899&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7  ~  MWARM30
[/C][/ROW]
[ROW][C]means[/C][C]87.026[/C][C]5.089[/C][C]7.049[/C][C]8.974[/C][C]23.974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223899&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223899&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
WISCRY7 ~ MWARM30
means87.0265.0897.0498.97423.974






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MWARM30 41472.781368.1953.4530.01
Residuals14615566.835106.622 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MWARM30
 & 4 & 1472.781 & 368.195 & 3.453 & 0.01 \tabularnewline
Residuals & 146 & 15566.835 & 106.622 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223899&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]1472.781[/C][C]368.195[/C][C]3.453[/C][C]0.01[/C][/ROW]
[ROW][C]Residuals[/C][C]146[/C][C]15566.835[/C][C]106.622[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223899&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223899&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)
MWARM30 41472.781368.1953.4530.01
Residuals14615566.835106.622






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-15.089-0.6110.7880.104
3-17.0490.63113.4680.024
4-18.974-19.91137.8590.912
7-123.974-4.91152.8590.153
3-21.961-3.6927.6140.873
4-23.886-24.83932.610.996
7-218.886-9.83947.610.368
4-31.925-26.95130.8011
7-316.925-11.95145.8010.488
7-415-25.33655.3360.842

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 5.089 & -0.61 & 10.788 & 0.104 \tabularnewline
3-1 & 7.049 & 0.631 & 13.468 & 0.024 \tabularnewline
4-1 & 8.974 & -19.911 & 37.859 & 0.912 \tabularnewline
7-1 & 23.974 & -4.911 & 52.859 & 0.153 \tabularnewline
3-2 & 1.961 & -3.692 & 7.614 & 0.873 \tabularnewline
4-2 & 3.886 & -24.839 & 32.61 & 0.996 \tabularnewline
7-2 & 18.886 & -9.839 & 47.61 & 0.368 \tabularnewline
4-3 & 1.925 & -26.951 & 30.801 & 1 \tabularnewline
7-3 & 16.925 & -11.951 & 45.801 & 0.488 \tabularnewline
7-4 & 15 & -25.336 & 55.336 & 0.842 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223899&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]5.089[/C][C]-0.61[/C][C]10.788[/C][C]0.104[/C][/ROW]
[ROW][C]3-1[/C][C]7.049[/C][C]0.631[/C][C]13.468[/C][C]0.024[/C][/ROW]
[ROW][C]4-1[/C][C]8.974[/C][C]-19.911[/C][C]37.859[/C][C]0.912[/C][/ROW]
[ROW][C]7-1[/C][C]23.974[/C][C]-4.911[/C][C]52.859[/C][C]0.153[/C][/ROW]
[ROW][C]3-2[/C][C]1.961[/C][C]-3.692[/C][C]7.614[/C][C]0.873[/C][/ROW]
[ROW][C]4-2[/C][C]3.886[/C][C]-24.839[/C][C]32.61[/C][C]0.996[/C][/ROW]
[ROW][C]7-2[/C][C]18.886[/C][C]-9.839[/C][C]47.61[/C][C]0.368[/C][/ROW]
[ROW][C]4-3[/C][C]1.925[/C][C]-26.951[/C][C]30.801[/C][C]1[/C][/ROW]
[ROW][C]7-3[/C][C]16.925[/C][C]-11.951[/C][C]45.801[/C][C]0.488[/C][/ROW]
[ROW][C]7-4[/C][C]15[/C][C]-25.336[/C][C]55.336[/C][C]0.842[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223899&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223899&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
2-15.089-0.6110.7880.104
3-17.0490.63113.4680.024
4-18.974-19.91137.8590.912
7-123.974-4.91152.8590.153
3-21.961-3.6927.6140.873
4-23.886-24.83932.610.996
7-218.886-9.83947.610.368
4-31.925-26.95130.8011
7-316.925-11.95145.8010.488
7-415-25.33655.3360.842






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group41.2630.287
146 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 4 & 1.263 & 0.287 \tabularnewline
  & 146 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=223899&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]1.263[/C][C]0.287[/C][/ROW]
[ROW][C] [/C][C]146[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=223899&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=223899&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)
Group41.2630.287
146


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):
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')