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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, 26 Nov 2018 23:57:26 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Nov/26/t1543273054jzjwi2xpw97cqdc.htm/, Retrieved Fri, 03 May 2024 00:10:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315704, Retrieved Fri, 03 May 2024 00:10:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
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)] [] [2018-11-26 22:57:26] [faeb7b06c531293c72cd094586d8c91e] [Current]
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Dataseries X:
1687 0
1508 0
1507 0
1385 0
1632 0
1511 0
1559 0
1630 0
1579 0
1653 0
2152 0
2148 0
1752 0
1765 0
1717 0
1558 0
1575 0
1520 0
1805 0
1800 0
1719 0
2008 0
2242 0
2478 0
2030 0
1655 0
1693 0
1623 0
1805 0
1746 0
1795 0
1926 0
1619 0
1992 0
2233 0
2192 0
2080 0
1768 0
1835 0
1569 0
1976 0
1853 0
1965 0
1689 0
1778 0
1976 0
2397 0
2654 0
2097 0
1963 0
1677 0
1941 0
2003 0
1813 0
2012 0
1912 0
2084 0
2080 0
2118 0
2150 0
1608 0
1503 0
1548 0
1382 0
1731 0
1798 0
1779 0
1887 0
2004 0
2077 0
2092 0
2051 0
1577 0
1356 0
1652 0
1382 0
1519 0
1421 0
1442 0
1543 0
1656 0
1561 0
1905 0
2199 0
1473 0
1655 0
1407 0
1395 0
1530 0
1309 0
1526 0
1327 0
1627 0
1748 0
1958 0
2274 0
1648 0
1401 0
1411 0
1403 0
1394 0
1520 0
1528 0
1643 0
1515 0
1685 0
2000 0
2215 0
1956 0
1462 0
1563 0
1459 0
1446 0
1622 0
1657 0
1638 0
1643 0
1683 0
2050 0
2262 0
1813 0
1445 0
1762 0
1461 0
1556 0
1431 0
1427 0
1554 0
1645 0
1653 0
2016 0
2207 0
1665 0
1361 0
1506 0
1360 0
1453 0
1522 0
1460 0
1552 0
1548 0
1827 0
1737 0
1941 0
1474 0
1458 0
1542 0
1404 0
1522 0
1385 0
1641 0
1510 0
1681 0
1938 0
1868 0
1726 0
1456 0
1445 0
1456 0
1365 0
1487 0
1558 0
1488 0
1684 0
1594 0
1850 0
1998 0
2079 0
1494 0
1057 1
1218 1
1168 1
1236 1
1076 1
1174 1
1139 1
1427 1
1487 1
1483 1
1513 1
1357 1
1165 1
1282 1
1110 1
1297 1
1185 1
1222 1
1284 1
1444 1
1575 1
1737 1
1763 1




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time4 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315704&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]4 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315704&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315704&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R ServerBig Analytics Cloud Computing Center







ANOVA Model
Accidents ~ Belt
means1717.751-396.056

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Accidents  ~  Belt \tabularnewline
means & 1717.751 & -396.056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315704&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Accidents  ~  Belt[/C][/ROW]
[ROW][C]means[/C][C]1717.751[/C][C]-396.056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315704&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315704&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
Accidents ~ Belt
means1717.751-396.056







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Belt13175602.4383175602.43846.9750
Residuals19012844428.43267602.255

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
Belt & 1 & 3175602.438 & 3175602.438 & 46.975 & 0 \tabularnewline
Residuals & 190 & 12844428.432 & 67602.255 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315704&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]Belt[/C][C]1[/C][C]3175602.438[/C][C]3175602.438[/C][C]46.975[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]190[/C][C]12844428.432[/C][C]67602.255[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315704&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315704&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
Belt13175602.4383175602.43846.9750
Residuals19012844428.43267602.255







Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-396.056-510.041-282.0710

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & -396.056 & -510.041 & -282.071 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315704&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]-396.056[/C][C]-510.041[/C][C]-282.071[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315704&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315704&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-0-396.056-510.041-282.0710







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group12.1720.142
190

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 2.172 & 0.142 \tabularnewline
  & 190 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315704&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]2.172[/C][C]0.142[/C][/ROW]
[ROW][C] [/C][C]190[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315704&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315704&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group12.1720.142
190



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){
'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')