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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 computationTue, 18 Nov 2014 11:32:14 +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/18/t1416310348s1cyx45an72mem3.htm/, Retrieved Sun, 19 May 2024 14:47:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=255986, Retrieved Sun, 19 May 2024 14:47:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

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)] [] [2014-11-18 11:32:14] [9c96953c9c62f1f8354e2cd3b0a37851] [Current]
-    D              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-11-18 11:47:32] [b7113647a6f457fe52279e60046b8f28]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
67	1	36
86	2	36
86	2	56
103	3	48
74	1	32
63	1	44
82	2	39
93	2	34
77	1	41
111	3	50
71	1	39
103	3	62
89	2	52
75	1	37
88	2	50
84	2	41
85	2	55
70	1	41
104	3	56
88	2	39
77	1	52
77	1	46
72	1	44
70	1	48
83	2	41
110	3	50
91	2	50
80	2	44
91	2	52
86	2	54
85	2	44
107	3	52
93	2	37
87	2	52
84	2	50
73	1	36
84	2	50
86	2	52
99	3	55
75	1	31
87	2	36
79	1	49
82	2	42
95	3	37
84	2	41
85	2	30
95	3	52
63	1	30
78	1	41
85	2	44
86	2	66
75	1	48
98	3	43
71	1	57
63	1	46
71	1	54
84	2	48
81	2	48
93	2	52
79	1	62
63	1	58
93	2	58
92	2	62
93	2	48
83	2	46
80	2	34
111	3	66
92	2	52
79	1	55
69	1	55
83	2	57
80	2	56
91	2	55
97	3	56
85	2	54
85	2	55
99	3	46
67	1	52
87	2	32
68	1	44
81	2	46
80	2	59
93	2	46
93	2	46
102	3	54
104	3	66
90	2	56
85	2	59
92	2	57
82	2	52
85	2	48
89	2	44
77	1	41
79	1	50
76	1	48
101	3	48
81	2	59
92	2	34
89	2	46
81	2	54
77	1	55
95	3	54
85	2	59
81	2	44
76	1	54
93	2	52
104	3	66
89	2	44
76	1	57
77	1	39
71	1	60
79	1	45
89	2	41
81	2	50
99	3	39
81	2	43
84	2	48
85	2	37
111	3	58
78	1	46
111	3	43
78	1	44
87	2	34
92	2	30
93	2	50
70	1	39
84	2	37
75	1	55
105	3	48
96	3	41
85	2	39
87	2	36
75	1	43
103	3	50
86	2	55
77	1	43
74	1	60
74	1	48
76	1	30
83	2	43
101	3	39
83	2	52
92	2	39
74	1	39
87	2	56
71	1	59
79	1	46
83	2	57
80	2	50
90	2	54
80	2	50
96	3	60
109	3	59
98	3	41
85	2	48
83	2	59
86	2	60
72	1	56
83	2	56
75	1	51

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'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255986&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255986&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'Sir Maurice George Kendall' @ kendall.wessa.net






ANOVA Model
MVRBIQ0 ~ scores
means73.5112.65828.883

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MVRBIQ0  ~  scores \tabularnewline
means & 73.51 & 12.658 & 28.883 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255986&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]MVRBIQ0  ~  scores[/C][/ROW]
[ROW][C]means[/C][C]73.51[/C][C]12.658[/C][C]28.883[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255986&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
MVRBIQ0 ~ scores
means73.5112.65828.883






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
scores215049.6827524.841372.1460
Residuals1573174.56220.22 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
scores & 2 & 15049.682 & 7524.841 & 372.146 & 0 \tabularnewline
Residuals & 157 & 3174.562 & 20.22 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255986&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]scores[/C][C]2[/C][C]15049.682[/C][C]7524.841[/C][C]372.146[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]157[/C][C]3174.562[/C][C]20.22[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255986&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255986&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)
scores215049.6827524.841372.1460
Residuals1573174.56220.22






Tukey Honest Significant Difference Comparisons
difflwruprp adj
2-112.65810.74214.5750
3-128.88326.36231.4030
3-216.22413.89918.5490

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
2-1 & 12.658 & 10.742 & 14.575 & 0 \tabularnewline
3-1 & 28.883 & 26.362 & 31.403 & 0 \tabularnewline
3-2 & 16.224 & 13.899 & 18.549 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255986&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]12.658[/C][C]10.742[/C][C]14.575[/C][C]0[/C][/ROW]
[ROW][C]3-1[/C][C]28.883[/C][C]26.362[/C][C]31.403[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]16.224[/C][C]13.899[/C][C]18.549[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255986&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255986&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
2-112.65810.74214.5750
3-128.88326.36231.4030
3-216.22413.89918.5490






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group21.6240.2
157 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 2 & 1.624 & 0.2 \tabularnewline
  & 157 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255986&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]1.624[/C][C]0.2[/C][/ROW]
[ROW][C] [/C][C]157[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255986&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255986&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)
Group21.6240.2
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')