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Author*The author of this computation has been verified*
R Software ModuleIan.Hollidayrwasp_One Factor ANOVA.wasp
Title produced by softwareChi Square Measure of Association- Free Statistics Software (Calculator)
Date of computationThu, 03 Dec 2009 14:34:43 +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/2009/Dec/03/t1259847419msvzrtitgj8b0re.htm/, Retrieved Thu, 28 Mar 2024 10:41:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62747, Retrieved Thu, 28 Mar 2024 10:41:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
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]
-   PD        [Chi Square Measure of Association- Free Statistics Software (Calculator)] [] [2009-12-03 13:34:43] [a9807aa03159d97ebfb8b094401eef38] [Current]
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Dataseries X:
88	6
94	8
90	8
73	7
68	5
80	7
86	8
86	9
91	9
79	3
96	9
92	7
72	9
96	8
70	6
86	7
87	8
88	9
79	7
90	6
95	8
85	7
90	8
115	9
84	9
79	7
94	4
97	7
86	7
111	9
87	7
98	9
87	10
68	5
88	6
82	9
111	9
75	8
94	6
95	6
80	5
95	8
68	8
94	5
88	6
84	9
101	6
101	10
95	8
95	7
95	8
90	3
107	8
92	10
86	7
70	5
95	10
96	5
91	8
87	9
92	6
97	9
102	8
91	5
68	8
88	3
97	7
90	8
101	10
94	9
101	10
109	9
100	8
103	8
94	8
97	9
85	4
75	6
77	7
87	4
78	9
108	7
97	8
106	8
107	7
95	7
107	9
115	8
101	8
85	9
90	9
115	10
95	7
97	8
112	5
97	9
77	8
90	7
94	8
103	8
77	7
98	6
90	7
111	7
77	6
88	6
75	7
92	9
78	6
106	10
80	4
87	8
92	7
86	5
85	9
90	8
101	9
94	8
86	8
86	9
90	8
75	9
86	7
91	6
97	8
91	6
70	5
98	3
96	6
95	8
100	7
95	8
97	6
97	9
92	9
115	10
88	7
87	5
100	8
98	9
102	8
96	4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62747&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62747&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62747&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







ANOVA Model
RespVar ~ AgeGroup
means101.444-12.694-13.044-17.626-12.722-12.074-8.102-8.611

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
RespVar  ~  AgeGroup \tabularnewline
means & 101.444 & -12.694 & -13.044 & -17.626 & -12.722 & -12.074 & -8.102 & -8.611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62747&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]RespVar  ~  AgeGroup[/C][/ROW]
[ROW][C]means[/C][C]101.444[/C][C]-12.694[/C][C]-13.044[/C][C]-17.626[/C][C]-12.722[/C][C]-12.074[/C][C]-8.102[/C][C]-8.611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62747&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62747&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
RespVar ~ AgeGroup
means101.444-12.694-13.044-17.626-12.722-12.074-8.102-8.611







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
AgeGroup72058.522294.0752.8550.008
Residuals13413804.435103.018

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
AgeGroup & 7 & 2058.522 & 294.075 & 2.855 & 0.008 \tabularnewline
Residuals & 134 & 13804.435 & 103.018 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62747&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]AgeGroup[/C][C]7[/C][C]2058.522[/C][C]294.075[/C][C]2.855[/C][C]0.008[/C][/ROW]
[ROW][C]Residuals[/C][C]134[/C][C]13804.435[/C][C]103.018[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62747&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62747&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)
AgeGroup72058.522294.0752.8550.008
Residuals13413804.435103.018







Tukey Honest Significant Difference Comparisons
difflwruprp adj
3-10-12.694-31.4776.0880.432
4-10-13.044-30.4784.3890.299
5-10-17.626-31.674-3.5780.004
6-10-12.722-25.4820.0380.051
7-10-12.074-24.104-0.0440.048
8-10-8.102-19.6893.4840.387
9-10-8.611-20.493.2680.339
4-3-0.35-21.31720.6171
5-3-4.932-23.18113.3170.991
6-3-0.028-17.30517.2491
7-30.62-16.12517.3661
8-34.592-11.83721.0220.989
9-34.083-12.55420.720.995
5-4-4.582-21.4412.2760.991
6-40.322-15.47816.1231
7-40.97-14.24716.1871
8-44.942-9.92719.8110.97
9-44.433-10.66419.5310.985
6-54.904-7.05816.8660.911
7-55.552-5.62816.7320.79
8-59.524-1.17720.2250.12
9-59.015-2.00220.0320.196
7-60.648-8.86310.1591
8-64.62-4.32313.5630.755
9-64.111-5.20713.430.874
8-73.972-3.89511.8390.776
9-73.463-4.82811.7540.903
9-8-0.509-8.1427.1251

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
3-10 & -12.694 & -31.477 & 6.088 & 0.432 \tabularnewline
4-10 & -13.044 & -30.478 & 4.389 & 0.299 \tabularnewline
5-10 & -17.626 & -31.674 & -3.578 & 0.004 \tabularnewline
6-10 & -12.722 & -25.482 & 0.038 & 0.051 \tabularnewline
7-10 & -12.074 & -24.104 & -0.044 & 0.048 \tabularnewline
8-10 & -8.102 & -19.689 & 3.484 & 0.387 \tabularnewline
9-10 & -8.611 & -20.49 & 3.268 & 0.339 \tabularnewline
4-3 & -0.35 & -21.317 & 20.617 & 1 \tabularnewline
5-3 & -4.932 & -23.181 & 13.317 & 0.991 \tabularnewline
6-3 & -0.028 & -17.305 & 17.249 & 1 \tabularnewline
7-3 & 0.62 & -16.125 & 17.366 & 1 \tabularnewline
8-3 & 4.592 & -11.837 & 21.022 & 0.989 \tabularnewline
9-3 & 4.083 & -12.554 & 20.72 & 0.995 \tabularnewline
5-4 & -4.582 & -21.44 & 12.276 & 0.991 \tabularnewline
6-4 & 0.322 & -15.478 & 16.123 & 1 \tabularnewline
7-4 & 0.97 & -14.247 & 16.187 & 1 \tabularnewline
8-4 & 4.942 & -9.927 & 19.811 & 0.97 \tabularnewline
9-4 & 4.433 & -10.664 & 19.531 & 0.985 \tabularnewline
6-5 & 4.904 & -7.058 & 16.866 & 0.911 \tabularnewline
7-5 & 5.552 & -5.628 & 16.732 & 0.79 \tabularnewline
8-5 & 9.524 & -1.177 & 20.225 & 0.12 \tabularnewline
9-5 & 9.015 & -2.002 & 20.032 & 0.196 \tabularnewline
7-6 & 0.648 & -8.863 & 10.159 & 1 \tabularnewline
8-6 & 4.62 & -4.323 & 13.563 & 0.755 \tabularnewline
9-6 & 4.111 & -5.207 & 13.43 & 0.874 \tabularnewline
8-7 & 3.972 & -3.895 & 11.839 & 0.776 \tabularnewline
9-7 & 3.463 & -4.828 & 11.754 & 0.903 \tabularnewline
9-8 & -0.509 & -8.142 & 7.125 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62747&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]3-10[/C][C]-12.694[/C][C]-31.477[/C][C]6.088[/C][C]0.432[/C][/ROW]
[ROW][C]4-10[/C][C]-13.044[/C][C]-30.478[/C][C]4.389[/C][C]0.299[/C][/ROW]
[ROW][C]5-10[/C][C]-17.626[/C][C]-31.674[/C][C]-3.578[/C][C]0.004[/C][/ROW]
[ROW][C]6-10[/C][C]-12.722[/C][C]-25.482[/C][C]0.038[/C][C]0.051[/C][/ROW]
[ROW][C]7-10[/C][C]-12.074[/C][C]-24.104[/C][C]-0.044[/C][C]0.048[/C][/ROW]
[ROW][C]8-10[/C][C]-8.102[/C][C]-19.689[/C][C]3.484[/C][C]0.387[/C][/ROW]
[ROW][C]9-10[/C][C]-8.611[/C][C]-20.49[/C][C]3.268[/C][C]0.339[/C][/ROW]
[ROW][C]4-3[/C][C]-0.35[/C][C]-21.317[/C][C]20.617[/C][C]1[/C][/ROW]
[ROW][C]5-3[/C][C]-4.932[/C][C]-23.181[/C][C]13.317[/C][C]0.991[/C][/ROW]
[ROW][C]6-3[/C][C]-0.028[/C][C]-17.305[/C][C]17.249[/C][C]1[/C][/ROW]
[ROW][C]7-3[/C][C]0.62[/C][C]-16.125[/C][C]17.366[/C][C]1[/C][/ROW]
[ROW][C]8-3[/C][C]4.592[/C][C]-11.837[/C][C]21.022[/C][C]0.989[/C][/ROW]
[ROW][C]9-3[/C][C]4.083[/C][C]-12.554[/C][C]20.72[/C][C]0.995[/C][/ROW]
[ROW][C]5-4[/C][C]-4.582[/C][C]-21.44[/C][C]12.276[/C][C]0.991[/C][/ROW]
[ROW][C]6-4[/C][C]0.322[/C][C]-15.478[/C][C]16.123[/C][C]1[/C][/ROW]
[ROW][C]7-4[/C][C]0.97[/C][C]-14.247[/C][C]16.187[/C][C]1[/C][/ROW]
[ROW][C]8-4[/C][C]4.942[/C][C]-9.927[/C][C]19.811[/C][C]0.97[/C][/ROW]
[ROW][C]9-4[/C][C]4.433[/C][C]-10.664[/C][C]19.531[/C][C]0.985[/C][/ROW]
[ROW][C]6-5[/C][C]4.904[/C][C]-7.058[/C][C]16.866[/C][C]0.911[/C][/ROW]
[ROW][C]7-5[/C][C]5.552[/C][C]-5.628[/C][C]16.732[/C][C]0.79[/C][/ROW]
[ROW][C]8-5[/C][C]9.524[/C][C]-1.177[/C][C]20.225[/C][C]0.12[/C][/ROW]
[ROW][C]9-5[/C][C]9.015[/C][C]-2.002[/C][C]20.032[/C][C]0.196[/C][/ROW]
[ROW][C]7-6[/C][C]0.648[/C][C]-8.863[/C][C]10.159[/C][C]1[/C][/ROW]
[ROW][C]8-6[/C][C]4.62[/C][C]-4.323[/C][C]13.563[/C][C]0.755[/C][/ROW]
[ROW][C]9-6[/C][C]4.111[/C][C]-5.207[/C][C]13.43[/C][C]0.874[/C][/ROW]
[ROW][C]8-7[/C][C]3.972[/C][C]-3.895[/C][C]11.839[/C][C]0.776[/C][/ROW]
[ROW][C]9-7[/C][C]3.463[/C][C]-4.828[/C][C]11.754[/C][C]0.903[/C][/ROW]
[ROW][C]9-8[/C][C]-0.509[/C][C]-8.142[/C][C]7.125[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62747&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62747&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
3-10-12.694-31.4776.0880.432
4-10-13.044-30.4784.3890.299
5-10-17.626-31.674-3.5780.004
6-10-12.722-25.4820.0380.051
7-10-12.074-24.104-0.0440.048
8-10-8.102-19.6893.4840.387
9-10-8.611-20.493.2680.339
4-3-0.35-21.31720.6171
5-3-4.932-23.18113.3170.991
6-3-0.028-17.30517.2491
7-30.62-16.12517.3661
8-34.592-11.83721.0220.989
9-34.083-12.55420.720.995
5-4-4.582-21.4412.2760.991
6-40.322-15.47816.1231
7-40.97-14.24716.1871
8-44.942-9.92719.8110.97
9-44.433-10.66419.5310.985
6-54.904-7.05816.8660.911
7-55.552-5.62816.7320.79
8-59.524-1.17720.2250.12
9-59.015-2.00220.0320.196
7-60.648-8.86310.1591
8-64.62-4.32313.5630.755
9-64.111-5.20713.430.874
8-73.972-3.89511.8390.776
9-73.463-4.82811.7540.903
9-8-0.509-8.1427.1251







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group70.9820.447
134

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 7 & 0.982 & 0.447 \tabularnewline
  & 134 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62747&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]7[/C][C]0.982[/C][C]0.447[/C][/ROW]
[ROW][C] [/C][C]134[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62747&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62747&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)
Group70.9820.447
134



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){
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
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')