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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 computationMon, 17 Nov 2014 20:54:29 +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/17/t1416257684serf7vwlssd7krw.htm/, Retrieved Sun, 19 May 2024 10:09:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=255781, Retrieved Sun, 19 May 2024 10:09:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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]
- RMPD            [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-11-17 20:54:29] [0ce137e93756d78d5d30d64827f474a7] [Current]
-   PD              [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-11-17 21:07:29] [bee63b5a134ce38846adbb81a61f1d5e]
-   PD                [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2014-11-17 21:27:08] [bee63b5a134ce38846adbb81a61f1d5e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92	36	3	1
88	36	1	2
94	56	3	2
90	48	3	3
73	32	3	1
68	44	1	1
80	39	2	2
86	34	3	2
86	41	3	1
91	50	2	3
79	39	1	1
96	62	1	3
92	52	3	2
72	37	3	1
96	50	3	2
70	41	1	2
86	55	3	2
87	41	3	1
88	56	3	3
79	39	2	2
90	52	2	1
95	46	1	1
85	44	1	1
92	48	3	1
90	41	3	2
115	50	1	3
84	50	1	2
79	44	3	2
94	52	1	2
97	54	2	2
86	44	3	2
111	52	2	3
87	37	2	2
98	52	3	2
87	50	1	2
68	36	3	1
88	50	3	2
82	52	1	2
111	55	2	3
75	31	1	1
94	36	1	2
95	49	2	1
80	42	1	2
95	37	1	2
68	41	3	2
94	30	2	2
88	52	2	2
84	30	1	1
92	41	1	1
101	44	1	2
98	66	1	2
78	48	2	1
109	43	3	3
102	57	3	1
81	46	3	1
97	54	3	1
75	48	2	2
97	48	2	2
92	52	2	2
101	62	3	1
101	58	3	1
95	58	2	2
95	62	2	2
92	48	2	2
95	46	3	2
90	34	2	2
107	66	3	3
92	52	3	2
86	55	2	1
70	55	2	1
95	57	3	2
96	56	3	2
91	55	2	2
87	56	1	2
92	54	2	2
97	55	2	2
102	46	2	3
91	52	2	1
68	32	3	2
88	44	2	1
97	46	3	2
90	59	1	2
101	46	3	2
94	46	3	2
101	54	1	3
109	66	1	3
100	56	2	2
103	59	1	2
94	57	3	2
97	52	1	2
85	48	3	2
75	44	2	2
77	41	3	1
87	50	1	1
78	48	1	1
108	48	2	3
97	59	3	2
105	34	1	2
106	46	3	2
107	54	1	2
95	55	2	1
107	54	2	2
115	59	3	2
101	44	3	2
85	54	1	1
90	52	3	2
115	66	3	3
95	44	3	2
97	57	2	1
112	39	3	1
97	60	3	1
77	45	3	1
90	41	3	2
94	50	1	2
103	39	3	3
77	43	1	2
98	48	3	2
90	37	3	2
111	58	3	3
77	46	2	1
88	43	3	3
75	44	2	1
92	34	3	2
78	30	2	2
106	50	2	2
80	39	2	1
87	37	3	2
92	55	3	1
92	48	1	3
111	41	1	3
86	39	3	2
85	36	3	2
90	43	2	1
101	50	1	3
94	55	3	2
86	43	3	1
86	60	3	1
90	48	2	1
75	30	1	1
86	43	3	2
91	39	3	3
97	52	3	2
91	39	2	2
70	39	3	1
98	56	2	2
96	59	3	1
95	46	3	1
100	57	2	2
95	50	3	2
97	54	3	2
97	50	3	2
92	60	3	3
115	59	1	3
88	41	3	3
87	48	2	2
100	59	3	2
98	60	3	2
102	56	1	1
92	56	1	2
96	51	3	0

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255781&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255781&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255781&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'George Udny Yule' @ yule.wessa.net






ANOVA Model
WISCRY7V ~ MVIQ
means96-9.604-4.235.875

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
WISCRY7V  ~  MVIQ \tabularnewline
means & 96 & -9.604 & -4.23 & 5.875 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255781&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]WISCRY7V  ~  MVIQ[/C][/ROW]
[ROW][C]means[/C][C]96[/C][C]-9.604[/C][C]-4.23[/C][C]5.875[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255781&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255781&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
WISCRY7V ~ MVIQ
means96-9.604-4.235.875






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
MVIQ33854.0941284.69814.5820
Residuals15613743.50688.099 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
MVIQ & 3 & 3854.094 & 1284.698 & 14.582 & 0 \tabularnewline
Residuals & 156 & 13743.506 & 88.099 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255781&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]MVIQ[/C][C]3[/C][C]3854.094[/C][C]1284.698[/C][C]14.582[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]156[/C][C]13743.506[/C][C]88.099[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255781&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255781&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)
MVIQ33854.0941284.69814.5820
Residuals15613743.50688.099






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-9.604-34.23215.0240.742
2-0-4.23-28.74520.2850.97
3-05.875-19.00330.7530.928
2-15.3740.9929.7570.009
3-115.4799.38521.5730
3-210.1054.48515.7250

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -9.604 & -34.232 & 15.024 & 0.742 \tabularnewline
2-0 & -4.23 & -28.745 & 20.285 & 0.97 \tabularnewline
3-0 & 5.875 & -19.003 & 30.753 & 0.928 \tabularnewline
2-1 & 5.374 & 0.992 & 9.757 & 0.009 \tabularnewline
3-1 & 15.479 & 9.385 & 21.573 & 0 \tabularnewline
3-2 & 10.105 & 4.485 & 15.725 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255781&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]-9.604[/C][C]-34.232[/C][C]15.024[/C][C]0.742[/C][/ROW]
[ROW][C]2-0[/C][C]-4.23[/C][C]-28.745[/C][C]20.285[/C][C]0.97[/C][/ROW]
[ROW][C]3-0[/C][C]5.875[/C][C]-19.003[/C][C]30.753[/C][C]0.928[/C][/ROW]
[ROW][C]2-1[/C][C]5.374[/C][C]0.992[/C][C]9.757[/C][C]0.009[/C][/ROW]
[ROW][C]3-1[/C][C]15.479[/C][C]9.385[/C][C]21.573[/C][C]0[/C][/ROW]
[ROW][C]3-2[/C][C]10.105[/C][C]4.485[/C][C]15.725[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255781&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255781&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
1-0-9.604-34.23215.0240.742
2-0-4.23-28.74520.2850.97
3-05.875-19.00330.7530.928
2-15.3740.9929.7570.009
3-115.4799.38521.5730
3-210.1054.48515.7250






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group31.9710.121
156 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 3 & 1.971 & 0.121 \tabularnewline
  & 156 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=255781&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]3[/C][C]1.971[/C][C]0.121[/C][/ROW]
[ROW][C] [/C][C]156[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=255781&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=255781&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)
Group31.9710.121
156


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 4 ; par3 = TRUE ;
Parameters (R input):
par1 = 1 ; par2 = 4 ; 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')