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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, 01 Nov 2012 10:58:54 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/01/t13517819554wns9mkavaydsnv.htm/, Retrieved Fri, 19 Apr 2024 19:06:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185534, Retrieved Fri, 19 Apr 2024 19:06:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98

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)] [WISCRY7V] [2012-11-01 12:45:55] [74be16979710d4c4e7c6647856088456]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [MVRBIQ0] [2012-11-01 14:58:54] [e6b76bc2c41e16dbd9e5cc558f04c104] [Current]
-    D                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mother's IQ and C...] [2012-11-04 18:44:01] [74be16979710d4c4e7c6647856088456]
-    D                  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Mother's IQ and C...] [2012-11-04 18:53:37] [74be16979710d4c4e7c6647856088456]
-    D                    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Maternal Warmth A...] [2012-11-04 19:20:20] [74be16979710d4c4e7c6647856088456]
-    D                      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Maternal Warmth A...] [2012-11-04 20:04:38] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
67	1
86	2
86	2
103	3
74	1
63	1
82	2
93	3
77	1
111	3
71	1
103	3
89	2
75	1
88	2
84	2
85	2
70	1
104	3
88	2
77	1
77	1
72	1
70	1
83	2
110	3
91	2
80	2
91	2
86	2
85	2
107	3
93	2
87	2
84	2
73	1
84	2
86	2
99	3
75	1
87	2
79	1
82	2
95	2
84	2
85	2
95	2
63	1
78	1
85	2
86	2
75	1
98	3
71	1
63	1
71	1
84	2
81	2
93	2
79	1
63	1
93	2
92	2
93	2
83	2
80	2
111	3
92	2
79	1
69	1
83	2
80	2
91	2
97	3
85	2
85	2
99	3
67	1
87	2
68	1
81	2
80	2
93	2
93	2
102	3
104	3
90	2
85	2
92	2
82	2
85	2
89	2
77	1
79	1
76	1
101	3
81	2
92	2
89	2
81	2
77	1
95	2
85	2
81	2
76	1
93	2
104	3
89	2
76	1
77	1
71	1
79	1
89	2
81	2
99	3
81	2
84	2
85	2
111	3
78	1
111	3
78	1
87	2
92	2
93	2
70	1
84	2
75	1
105	3
96	3
85	2
87	2
75	1
103	3
86	2
77	1
74	1
74	1
76	1
83	2
101	3
83	2
92	2
74	1
87	2
71	1
79	1
83	2
80	2
90	2
80	2
96	3
109	3
98	3
85	2
83	2
86	2
72	1
83	2
75	1

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185534&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185534&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185534&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'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
IQ ~ Mothers-Age
means73.5112.8929.374

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
IQ  ~  Mothers-Age \tabularnewline
means & 73.51 & 12.89 & 29.374 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185534&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]IQ  ~  Mothers-Age[/C][/ROW]
[ROW][C]means[/C][C]73.51[/C][C]12.89[/C][C]29.374[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185534&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185534&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
IQ ~ Mothers-Age
means73.5112.8929.374






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Mothers-Age214948.9457474.473358.2860
Residuals1573275.29920.862 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Mothers-Age & 2 & 14948.945 & 7474.473 & 358.286 & 0 \tabularnewline
Residuals & 157 & 3275.299 & 20.862 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185534&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]Mothers-Age[/C][C]2[/C][C]14948.945[/C][C]7474.473[/C][C]358.286[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]157[/C][C]3275.299[/C][C]20.862[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185534&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185534&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)
Mothers-Age214948.9457474.473358.2860
Residuals1573275.29920.862






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-112.8910.95114.8280
3-129.37426.75231.9970
3-216.48514.06318.9070

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 12.89 & 10.951 & 14.828 & 0 \tabularnewline
3-1 & 29.374 & 26.752 & 31.997 & 0 \tabularnewline
3-2 & 16.485 & 14.063 & 18.907 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185534&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]12.89[/C][C]10.951[/C][C]14.828[/C][C]0[/C][/ROW]
[ROW][C]3-1[/C][C]29.374[/C][C]26.752[/C][C]31.997[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]16.485[/C][C]14.063[/C][C]18.907[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185534&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185534&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
2-112.8910.95114.8280
3-129.37426.75231.9970
3-216.48514.06318.9070






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group20.6590.519
157 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 0.659 & 0.519 \tabularnewline
  & 157 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185534&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]0.659[/C][C]0.519[/C][/ROW]
[ROW][C] [/C][C]157[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185534&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185534&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)
Group20.6590.519
157


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')