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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 computationSun, 27 Nov 2011 13:54:50 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/27/t1322420157t1x5d3yinubv0ze.htm/, Retrieved Thu, 16 May 2024 15:33:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147600, Retrieved Thu, 16 May 2024 15:33:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74

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 PD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ANOVA 1] [2011-11-27 18:54:50] [718abb62a78e84b22e01bdba2059eb20] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	86	6	36	88
3	86	8	56	94
3	103	8	48	90
3	74	7	32	73
1	63	5	44	68
2	82	7	39	80
3	93	8	34	86
3	77	9	41	86
2	111	9	50	91
1	71	3	39	79
1	103	9	62	96
3	89	7	52	92
3	75	9	37	72
3	88	8	50	96
1	84	6	41	70
3	85	7	55	86
3	70	8	41	87
3	104	9	56	88
2	88	7	39	79
2	77	6	52	90
1	77	8	46	95
1	72	7	44	85
3	83	8	41	90
1	110	9	50	115
1	91	9	50	84
3	80	7	44	79
1	91	4	52	94
2	86	7	54	97
3	85	7	44	86
2	107	9	52	111
2	93	7	37	87
3	87	9	52	98
1	84	10	50	87
3	73	5	36	68
3	84	6	50	88
1	86	9	52	82
2	99	9	55	111
1	75	8	31	75
1	87	6	36	94
2	79	6	49	95
1	82	5	42	80
1	95	8	37	95
3	84	8	41	68
2	85	5	30	94
2	95	6	52	88
1	63	9	30	84
1	85	4	44	101
1	86	8	66	98
2	75	9	48	78
3	98	7	43	109
3	71	7	57	102
3	63	6	46	81
3	71	9	54	97
2	84	9	48	75
2	81	8	48	97
3	79	6	62	101
3	63	10	58	101
2	93	8	58	95
2	92	7	62	95
3	83	8	46	95
2	80	3	34	90
3	111	8	66	107
3	92	10	52	92
2	79	7	55	86
2	69	5	55	70
3	83	10	57	95
3	80	5	56	96
2	91	8	55	91
1	97	9	56	87
2	85	6	54	92
2	85	9	55	97
2	99	8	46	102
2	67	5	52	91
3	87	8	32	68
2	68	3	44	88
3	81	7	46	97
1	80	8	59	90
3	93	10	46	101
3	93	9	46	94
1	102	10	54	101
1	104	9	66	109
2	90	8	56	100
1	85	8	59	103
3	92	8	57	94
1	82	9	52	97
3	85	4	48	85
2	89	6	44	75
3	77	7	41	77
1	79	4	50	87
1	76	9	48	78
2	101	7	48	108
3	81	8	59	97
3	89	8	46	106
1	81	7	54	107
2	77	7	55	95
2	95	9	54	107
3	85	8	59	115
3	81	8	44	101
1	76	9	54	85
3	93	9	52	90
3	104	10	66	115
3	89	7	44	95
2	76	8	57	97
3	77	5	39	112
3	71	9	60	97
3	79	8	45	77
3	89	7	41	90
1	81	8	50	94
3	99	8	39	103
1	81	7	43	77
3	84	6	48	98
3	85	7	37	90
3	111	7	58	111
2	78	6	46	77
3	111	6	43	88
2	78	7	44	75
3	87	9	34	92
2	92	6	30	78
2	93	10	50	106
2	70	4	39	80
3	84	8	37	87
3	75	7	55	92
3	85	5	39	86
3	87	9	36	85
2	75	8	43	90
1	103	9	50	101
3	86	8	55	94
3	77	8	43	86
3	74	9	60	86
2	74	8	48	90
1	76	9	30	75
3	83	7	43	86
3	101	6	39	91
3	83	8	52	97
2	92	6	39	91
3	74	5	39	70
2	87	3	56	98
3	71	6	59	96
3	79	8	46	95
2	83	7	57	100
3	80	8	50	95
3	90	6	54	97
3	80	9	50	97
3	96	9	60	92
1	109	10	59	115
3	98	7	41	88
2	85	5	48	87
3	83	8	59	100
3	86	9	60	98
1	72	8	56	102
3	75	4	51	96

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147600&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147600&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147600&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'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
MC30VRB ~ WISCRY7V
means57.33351.143534948584854.5553958.538.2545373239.443.754240.6674046524045.54645.5714645.54751.16747.755055.653.41756.4

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
MC30VRB  ~  WISCRY7V \tabularnewline
means & 57.333 & 51.143 & 53 & 49 & 48 & 58 & 48 & 54.5 & 55 & 39 & 58.5 & 38.25 & 45 & 37 & 32 & 39.4 & 43.75 & 42 & 40.667 & 40 & 46 & 52 & 40 & 45.5 & 46 & 45.571 & 46 & 45.5 & 47 & 51.167 & 47.75 & 50 & 55.6 & 53.417 & 56.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147600&T=1

[TABLE]
[ROW]ANOVA Model[/C][/ROW]
[ROW]MC30VRB  ~  WISCRY7V[/C][/ROW]
[ROW][C]means[/C][C]57.333[/C][C]51.143[/C][C]53[/C][C]49[/C][C]48[/C][C]58[/C][C]48[/C][C]54.5[/C][C]55[/C][C]39[/C][C]58.5[/C][C]38.25[/C][C]45[/C][C]37[/C][C]32[/C][C]39.4[/C][C]43.75[/C][C]42[/C][C]40.667[/C][C]40[/C][C]46[/C][C]52[/C][C]40[/C][C]45.5[/C][C]46[/C][C]45.571[/C][C]46[/C][C]45.5[/C][C]47[/C][C]51.167[/C][C]47.75[/C][C]50[/C][C]55.6[/C][C]53.417[/C][C]56.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147600&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147600&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
MC30VRB ~ WISCRY7V
means57.33351.143534948584854.5553958.538.2545373239.443.754240.6674046524045.54645.5714645.54751.16747.755055.653.41756.4






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
WISCRY7V35356912.74510197.507187.4880
Residuals1166309.25554.39 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
WISCRY7V & 35 & 356912.745 & 10197.507 & 187.488 & 0 \tabularnewline
Residuals & 116 & 6309.255 & 54.39 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147600&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]WISCRY7V[/C][C]35[/C][C]356912.745[/C][C]10197.507[/C][C]187.488[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]116[/C][C]6309.255[/C][C]54.39[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147600&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147600&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)
WISCRY7V35356912.74510197.507187.4880
Residuals1166309.25554.39






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=147600&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147600&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147600&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)
Group340.9150.605
116 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 34 & 0.915 & 0.605 \tabularnewline
  & 116 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147600&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]34[/C][C]0.915[/C][C]0.605[/C][/ROW]
[ROW][C] [/C][C]116[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147600&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147600&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)
Group340.9150.605
116


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = 5 ; par3 = FALSE ;
Parameters (R input):
par1 = 4 ; par2 = 5 ; 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){
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')