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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 computationThu, 13 Nov 2014 12:50:42 +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/2014/Nov/13/t14158830781vwro1x6l71legc.htm/, Retrieved Sun, 19 May 2024 12:42:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=254260, Retrieved Sun, 19 May 2024 12:42:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

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]
- RM D          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers Age and 3...] [2014-11-13 11:45:48] [579bc715ab196de960e48351189dde49]
-    D            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers age and Y7] [2014-11-13 11:50:39] [579bc715ab196de960e48351189dde49]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mothers IQ and 30M] [2014-11-13 12:17:04] [579bc715ab196de960e48351189dde49]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [mat warmth child 30] [2014-11-13 12:45:58] [579bc715ab196de960e48351189dde49]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mat Warmth child 7] [2014-11-13 12:50:42] [d9da722954c8dd705d8623da18e0bbdf] [Current]
-   P                       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [EX 3(1) NO INT] [2014-11-14 11:04:18] [579bc715ab196de960e48351189dde49]
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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	9
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	3
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	1
90	2
111	2
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	3
102	2
96	1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254260&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254260&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
WISCRY7V ~ MaternalWarmth
means87.454.8116.94-9.45

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MaternalWarmth \tabularnewline
means & 87.45 & 4.811 & 6.94 & -9.45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254260&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MaternalWarmth[/C][/ROW]
[ROW][C]means[/C][C]87.45[/C][C]4.811[/C][C]6.94[/C][C]-9.45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254260&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
WISCRY7V ~ MaternalWarmth
means87.454.8116.94-9.45






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MaternalWarmth31220.655406.8853.7810.012
Residuals14715818.96107.612 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MaternalWarmth & 3 & 1220.655 & 406.885 & 3.781 & 0.012 \tabularnewline
Residuals & 147 & 15818.96 & 107.612 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254260&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]MaternalWarmth[/C][C]3[/C][C]1220.655[/C][C]406.885[/C][C]3.781[/C][C]0.012[/C][/ROW]
[ROW][C]Residuals[/C][C]147[/C][C]15818.96[/C][C]107.612[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254260&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254260&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)
MaternalWarmth31220.655406.8853.7810.012
Residuals14715818.96107.612






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-14.811-0.54610.1680.095
3-16.940.94912.9310.016
9-1-9.45-36.74217.8420.805
3-22.129-3.1867.4450.726
9-2-14.261-41.41312.8910.523
9-3-16.39-43.67510.8940.404

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 4.811 & -0.546 & 10.168 & 0.095 \tabularnewline
3-1 & 6.94 & 0.949 & 12.931 & 0.016 \tabularnewline
9-1 & -9.45 & -36.742 & 17.842 & 0.805 \tabularnewline
3-2 & 2.129 & -3.186 & 7.445 & 0.726 \tabularnewline
9-2 & -14.261 & -41.413 & 12.891 & 0.523 \tabularnewline
9-3 & -16.39 & -43.675 & 10.894 & 0.404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254260&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]4.811[/C][C]-0.546[/C][C]10.168[/C][C]0.095[/C][/ROW]
[ROW][C]3-1[/C][C]6.94[/C][C]0.949[/C][C]12.931[/C][C]0.016[/C][/ROW]
[ROW][C]9-1[/C][C]-9.45[/C][C]-36.742[/C][C]17.842[/C][C]0.805[/C][/ROW]
[ROW][C]3-2[/C][C]2.129[/C][C]-3.186[/C][C]7.445[/C][C]0.726[/C][/ROW]
[ROW][C]9-2[/C][C]-14.261[/C][C]-41.413[/C][C]12.891[/C][C]0.523[/C][/ROW]
[ROW][C]9-3[/C][C]-16.39[/C][C]-43.675[/C][C]10.894[/C][C]0.404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254260&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254260&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
2-14.811-0.54610.1680.095
3-16.940.94912.9310.016
9-1-9.45-36.74217.8420.805
3-22.129-3.1867.4450.726
9-2-14.261-41.41312.8910.523
9-3-16.39-43.67510.8940.404






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group30.8240.482
147 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 0.824 & 0.482 \tabularnewline
  & 147 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=254260&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]3[/C][C]0.824[/C][C]0.482[/C][/ROW]
[ROW][C] [/C][C]147[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=254260&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=254260&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)
Group30.8240.482
147


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')