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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, 09 Dec 2014 13:04:08 +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/Dec/09/t14181304397gnv3z2l6mn1b5o.htm/, Retrieved Thu, 16 May 2024 12:22:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264559, Retrieved Thu, 16 May 2024 12:22:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RMPD    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA Intrinsieke...] [2014-12-09 13:04:08] [8eaf8ca403eea369f03debd8dc66ae53] [Current]
- R         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA Extrinsieke...] [2014-12-09 13:11:27] [ce9f16fa58bb2303d66047ab4343b505]
- R         [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA Totale Moti...] [2014-12-09 13:12:55] [ce9f16fa58bb2303d66047ab4343b505]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
56	61	117	0
57	68	125	0
51	61	112	0
56	64	120	0
30	65	95	0
61	69	130	0
47	63	110	0
56	75	131	0
50	63	113	0
67	73	140	0
41	75	116	0
45	63	108	0
48	63	111	0
44	62	106	0
37	64	101	0
56	60	116	0
66	56	122	0
38	59	97	0
34	68	102	0
49	66	115	0
55	73	128	0
49	72	121	0
59	71	130	0
40	59	99	0
58	64	122	0
60	66	126	0
63	78	141	0
56	68	124	0
54	73	127	0
52	62	114	0
34	65	99	0
69	68	137	0
32	65	97	0
48	60	108	0
67	71	138	0
58	65	123	0
57	68	125	0
42	64	106	0
64	74	138	0
58	69	127	0
66	76	142	0
26	68	94	0
61	72	133	0
52	67	119	0
51	63	114	0
55	59	114	0
50	73	123	0
60	66	126	0
56	62	118	0
63	69	132	0
61	66	127	0
62	72	134	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
NA	NA	NA	0
26	50	76	1
51	68	119	1
57	62	119	1
37	54	91	1
67	71	138	1
43	54	97	1
52	65	117	1
52	73	125	1
43	52	95	1
84	84	168	1
67	42	109	1
49	66	115	1
70	65	135	1
52	78	130	1
58	73	131	1
68	75	143	1
43	66	109	1
56	70	126	1
74	81	155	1
65	71	136	1
63	69	132	1
58	71	129	1
57	72	129	1
63	68	131	1
53	70	123	1
64	67	131	1
53	76	129	1
29	70	99	1
54	60	114	1
51	77	128	1
58	72	130	1
43	69	112	1
51	71	122	1
53	62	115	1
54	70	124	1
61	58	119	1
47	76	123	1
39	52	91	1
48	59	107	1
50	68	118	1
35	76	111	1
68	67	135	1
49	59	108	1
67	76	143	1
43	60	103	1
62	63	125	1
57	70	127	1
54	66	120	1
61	64	125	1
56	70	126	1
41	75	116	1
43	61	104	1
53	60	113	1
66	73	139	1
58	61	119	1
46	66	112	1
51	59	110	1
51	64	115	1
45	66	111	1
37	78	115	1
59	53	112	1
42	67	109	1
66	66	132	1
53	71	124	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=264559&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=264559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264559&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
IM ~ B/S
means52.4421.089

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
IM  ~  B/S \tabularnewline
means & 52.442 & 1.089 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264559&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]IM  ~  B/S[/C][/ROW]
[ROW][C]means[/C][C]52.442[/C][C]1.089[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264559&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
IM ~ B/S
means52.4421.089






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
B/S134.0234.020.3020.584
Residuals11412862.764112.831 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
B/S & 1 & 34.02 & 34.02 & 0.302 & 0.584 \tabularnewline
Residuals & 114 & 12862.764 & 112.831 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264559&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]B/S[/C][C]1[/C][C]34.02[/C][C]34.02[/C][C]0.302[/C][C]0.584[/C][/ROW]
[ROW][C]Residuals[/C][C]114[/C][C]12862.764[/C][C]112.831[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264559&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264559&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)
B/S134.0234.020.3020.584
Residuals11412862.764112.831






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-01.089-2.845.0180.584

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 1.089 & -2.84 & 5.018 & 0.584 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264559&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]1-0[/C][C]1.089[/C][C]-2.84[/C][C]5.018[/C][C]0.584[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264559&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264559&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
1-01.089-2.845.0180.584






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.0290.865
114 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.029 & 0.865 \tabularnewline
  & 114 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264559&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]1[/C][C]0.029[/C][C]0.865[/C][/ROW]
[ROW][C] [/C][C]114[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264559&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264559&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)
Group10.0290.865
114


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 4 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'TRUE'
par2 <- '4'
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')