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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 Oct 2013 15:11:31 -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/2013/Oct/27/t13829011817gv62dyphi7w1ir.htm/, Retrieved Mon, 29 Apr 2024 08:44:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=219995, Retrieved Mon, 29 Apr 2024 08:44:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-19 12:03:37] [74be16979710d4c4e7c6647856088456]
- RM D  [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Assignment 2 vraag 2] [2012-10-22 21:16:02] [e35bad265b4f882bb08312c911aaf8f2]
- R PD      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [ù] [2013-10-27 19:11:31] [3ee9af9023d551eb0318c89a6418f337] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1	255
2	280.2
3	299.9
4	339.2
5	374.2
6	393.5
7	389.2
8	381.7
9	375.2
10	369
11	357.4
12	352.1
1	346.5
2	342.9
3	340.3
4	328.3
5	322.9
6	314.3
7	308.9
8	294
9	285.6
10	281.2
11	280.3
12	278.8
1	274.5
2	270.4
3	263.4
4	259.9
5	258
6	262.7
7	284.7
8	311.3
9	322.1
10	327
11	331.3
12	333.3
1	321.4
2	327
3	320
4	314.7
5	316.7
6	314.4
7	321.3
8	318.2
9	307.2
10	301.3
11	287.5
12	277.7
1	274.4
2	258.8
3	253.3
4	251
5	248.4
6	249.5
7	246.1
8	244.5
9	243.6
10	244
11	240.8
12	249.8
1	248
2	259.4
3	260.5
4	260.8
5	261.3
6	259.5
7	256.6
8	257.9
9	256.5
10	254.2
11	253.3
12	253.8
1	255.5
2	257.1
3	257.3
4	253.2
5	252.8
6	252
7	250.7
8	252.2
9	250
10	251
11	253.4
12	251.2
1	255.6
2	261.1
3	258.9
4	259.9
5	261.2
6	264.7
7	267.1
8	266.4
9	267.7
10	268.6
11	267.5
12	268.5
1	268.5
2	270.5
3	270.9
4	270.1
5	269.3
6	269.8
7	270.1
8	264.9
9	263.7
10	264.8
11	263.7
12	255.9
1	276.2
2	360.1
3	380.5
4	373.7
5	369.8
6	366.6
7	359.3
8	345.8
9	326.2
10	324.5
11	328.1
12	327.5
1	324.4
2	316.5
3	310.9
4	301.5
5	291.7
6	290.4
7	287.4
8	277.7
9	281.6
10	288
11	276
12	272.9
1	283
2	283.3
3	276.8
4	284.5
5	282.7
6	281.2
7	287.4
8	283.1
9	284
10	285.5
11	289.2
12	292.5
1	296.4
2	305.2
3	303.9
4	311.5
5	316.3
6	316.7
7	322.5
8	317.1
9	309.8
10	303.8
11	290.3
12	293.7
1	291.7
2	296.5
3	289.1
4	288.5
5	293.8
6	297.7
7	305.4
8	302.7
9	302.5
10	303
11	294.5
12	294.1
1	294.5
2	297.1
3	289.4
4	292.4
5	287.9
6	286.6
7	280.5
8	272.4
9	269.2
10	270.6
11	267.3
12	262.5
1	266.8
2	268.8
3	263.1
4	261.2
5	266
6	262.5
7	265.2
8	261.3
9	253.7
10	249.2
11	239.1
12	236.4
1	235.2
2	245.2
3	246.2
4	247.7
5	251.4
6	253.3
7	254.8
8	250
9	249.3
10	241.5
11	243.3
12	248
1	253
2	252.9
3	251.5
4	251.6
5	253.5
6	259.8
7	334.1
8	448
9	445.8
10	445
11	448.2
12	438.2
1	439.8
2	423.4
3	410.8
4	408.4
5	406.7
6	405.9
7	402.7
8	405.1
9	399.6
10	386.5
11	381.4
12	375.2
1	357.7
2	359
3	355
4	352.7
5	344.4
6	343.8
7	338
8	339
9	333.3
10	334.4
11	328.3
12	330.7
1	330
2	331.6
3	351.2
4	389.4
5	410.9
6	442.8
7	462.8
8	466.9
9	461.7
10	439.2
11	430.3
12	416.1
1	402.5
2	397.3
3	403.3
4	395.9
5	387.8
6	378.6
7	377.1
8	370.4
9	362
10	350.3
11	348.2
12	344.6
1	343.5
2	342.8
3	347.6
4	346.6
5	349.5
6	342.1
7	342
8	342.8
9	339.3
10	348.2
11	333.7
12	334.7
1	354
2	367.7
3	363.3
4	358.4
5	353.1
6	343.1
7	344.6
8	344.4
9	333.9
10	331.7
11	324.3
12	321.2
1	322.4
2	321.7
3	320.5
4	312.8
5	309.7
6	315.6
7	309.7
8	304.6
9	302.5
10	301.5
11	298.8
12	291.3
1	293.6
2	294.6
3	285.9
4	297.6
5	301.1
6	293.8
7	297.7
8	292.9
9	292.1
10	287.2
11	288.2
12	283.8
1	299.9
2	292.4
3	293.3
4	300.8
5	293.7
6	293.1
7	294.4
8	292.1
9	291.9
10	282.5
11	277.9
12	287.5
1	289.2
2	285.6
3	293.2
4	290.8
5	283.1
6	275
7	287.8
8	287.8
9	287.4
10	284
11	277.8
12	277.6
1	304.9
2	294
3	300.9
4	324
5	332.9
6	341.6
7	333.4
8	348.2
9	344.7
10	344.7
11	329.3
12	323.5
1	323.2
2	317.4
3	330.1
4	329.2
5	334.9
6	315.8
7	315.4
8	319.6
9	317.3
10	313.8
11	315.8
12	311.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=219995&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]3 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=219995&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=219995&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






ANOVA Model
USA ~ month
means302.71309.207304.84302.813306.017306.367308.543309.523309.547313.23315.433311.98

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
USA  ~  month \tabularnewline
means & 302.71 & 309.207 & 304.84 & 302.813 & 306.017 & 306.367 & 308.543 & 309.523 & 309.547 & 313.23 & 315.433 & 311.98 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=219995&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]USA  ~  month[/C][/ROW]
[ROW][C]means[/C][C]302.71[/C][C]309.207[/C][C]304.84[/C][C]302.813[/C][C]306.017[/C][C]306.367[/C][C]308.543[/C][C]309.523[/C][C]309.547[/C][C]313.23[/C][C]315.433[/C][C]311.98[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=219995&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=219995&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
USA ~ month
means302.71309.207304.84302.813306.017306.367308.543309.523309.547313.23315.433311.98






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
month1234234132.332852844.3611158.0140
Residuals348857321.042463.566 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
month & 12 & 34234132.33 & 2852844.361 & 1158.014 & 0 \tabularnewline
Residuals & 348 & 857321.04 & 2463.566 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=219995&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]month[/C][C]12[/C][C]34234132.33[/C][C]2852844.361[/C][C]1158.014[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]348[/C][C]857321.04[/C][C]2463.566[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=219995&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=219995&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)
month1234234132.332852844.3611158.0140
Residuals348857321.042463.566






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=219995&T=3

[TABLE]
[ROW][C]Must Include Intercept to use Tukey Test [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=219995&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=219995&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)
Group110.1381
348 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 11 & 0.138 & 1 \tabularnewline
  & 348 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=219995&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]11[/C][C]0.138[/C][C]1[/C][/ROW]
[ROW][C] [/C][C]348[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=219995&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=219995&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)
Group110.1381
348


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = 1 ; par3 = FALSE ;
Parameters (R input):
par1 = 2 ; par2 = 1 ; par3 = FALSE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '2'
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')