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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 computationFri, 01 Jun 2012 05:41:08 -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/Jun/01/t1338543688n5gc5hxmqwh3y19.htm/, Retrieved Thu, 02 May 2024 06:19:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168371, Retrieved Thu, 02 May 2024 06:19:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [male1] [2012-06-01 09:41:08] [e736236f6db1679287c406e2c94ebdc5] [Current]
-    D    [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [female 1] [2012-06-01 09:47:02] [2b8093ecf59eda89cc76f527bcb38785]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
77	182	77	180
68	177	70	175
76	170	76	165
76	167	77	165
69	186	73	180
71	178	71	175
65	171	64	170
70	175	75	174
92	187	101	185
76	197	75	200
119	180	124	178
65	175	66	173
66	173	70	170
101	183	100	180
75	178	73	175
79	173	76	173
64	176	65	175
69	174	69	171
88	178	86	175
65	187	67	188
80	178	80	178
78	183	80	180
85	179	82	175
73	180	NA	NA
82	182	85	183
74	169	73	170
102	185	107	185
64	177	NA	NA
65	176	64	172
73	183	74	180
75	172	70	169
57	173	58	170
68	165	69	165
71	177	71	170
71	180	76	175
97	189	98	185
80	178	76	175
66	173	66	175
69	182	70	180
69	183	70	183
55	168	56	170
59	182	61	183
62	178	66	175
70	173	68	170
84	184	86	183
69	180	71	180
88	189	87	185
103	185	101	182
63	178	63	175
84	183	90	183
79	179	79	171
67	179	67	179
83	184	83	181
96	184	94	183
75	169	76	165
65	178	66	178
78	178	77	175
69	167	73	165
67	179	NA	NA
87	185	89	185
83	177	84	175
90	188	91	185
85	191	83	188
66	175	68	175
88	184	86	183
54	169	58	165
69	172	68	174
56	163	58	161
96	191	95	188
76	169	75	165
61	170	61	170
82	176	NA	NA
62	168	64	168
71	178	68	178
66	170	67	165
81	178	82	175
68	174	68	173
80	176	78	175
82	181	NA	NA
70	173	70	173
76	183	75	180
88	185	93	188
89	173	86	173
74	175	71	175
83	180	80	180
81	175	NA	NA
90	181	91	178
79	177	81	178

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168371&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168371&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168371&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'Gwilym Jenkins' @ jenkins.wessa.net






ANOVA Model
V1 ~ V2
means566872.558.569.7567.66765727168.571.272.75737474.5838671.7580.16787.75956978.59092.590.576

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
V1  ~  V2 \tabularnewline
means & 56 & 68 & 72.5 & 58.5 & 69.75 & 67.667 & 65 & 72 & 71 & 68.5 & 71.2 & 72.75 & 73 & 74 & 74.5 & 83 & 86 & 71.75 & 80.167 & 87.75 & 95 & 69 & 78.5 & 90 & 92.5 & 90.5 & 76 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168371&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]V1  ~  V2[/C][/ROW]
[ROW][C]means[/C][C]56[/C][C]68[/C][C]72.5[/C][C]58.5[/C][C]69.75[/C][C]67.667[/C][C]65[/C][C]72[/C][C]71[/C][C]68.5[/C][C]71.2[/C][C]72.75[/C][C]73[/C][C]74[/C][C]74.5[/C][C]83[/C][C]86[/C][C]71.75[/C][C]80.167[/C][C]87.75[/C][C]95[/C][C]69[/C][C]78.5[/C][C]90[/C][C]92.5[/C][C]90.5[/C][C]76[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168371&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168371&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
V1 ~ V2
means566872.558.569.7567.66765727168.571.272.75737474.5838671.7580.16787.75956978.59092.590.576






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
V227512921.718997.1183.9610
Residuals616299.3103.267 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
V2 & 27 & 512921.7 & 18997.1 & 183.961 & 0 \tabularnewline
Residuals & 61 & 6299.3 & 103.267 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168371&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]V2[/C][C]27[/C][C]512921.7[/C][C]18997.1[/C][C]183.961[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]61[/C][C]6299.3[/C][C]103.267[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168371&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168371&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)
V227512921.718997.1183.9610
Residuals616299.3103.267






Must Include Intercept to use Tukey Test 

\begin{tabular}{lllllllll}
\hline
Must Include Intercept to use Tukey Test  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168371&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168371&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168371&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:

Must Include Intercept to use Tukey Test






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group260.5920.929
61 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 26 & 0.592 & 0.929 \tabularnewline
  & 61 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168371&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]26[/C][C]0.592[/C][C]0.929[/C][/ROW]
[ROW][C] [/C][C]61[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168371&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168371&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)
Group260.5920.929
61


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = FALSE ;
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){
'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')