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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_One Factor ANOVA.wasp

Title produced by software

One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)

Date of computation

Thu, 03 May 2012 06:02:05 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/03/t13360393354tqswmb4drnltdf.htm/, Retrieved Thu, 02 May 2024 03:28:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166167, Retrieved Thu, 02 May 2024 03:28:40 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

116

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [T-Tests] [Salk Heatbeat Study] [2012-02-14 16:56:38] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD  [Histogram, QQplot and Density] [Salk Heatbeat Stu...] [2012-02-14 18:01:42] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [T-Tests] [T-test] [2012-05-03 09:50:49] [bf1ddb3cd45fb5d723b760bc40755ff6]
- RM          [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [Tukeys] [2012-05-03 10:02:05] [59312cd388a22453680c04e4e4e3aaf4] [Current]

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Dataseries X:

Download CSV

Histogram

Boxplots

-85	-50
-60	-45
-45	-45
-30	-45
-25	-30
-10	-30
0	-25
0	-30
10	-10
10	-25
10	-25
20	0
20	-10
30	10
40	20
50	25
75	70
80	100
80	100
190	140
NA	-50
NA	-50
NA	-60
NA	-75
NA	-75
NA	-85
NA	-85
NA	-100
NA	-110
NA	-130
NA	-130
NA	-155
NA	-155
NA	-180
NA	-240
NA	-290

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=166167&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=166167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166167&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 Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

ANOVA Model
htbeat ~ nohtbeat
means	15	-8.333	-26.667	-60	-100	5	15	65	175	25	35	60

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
htbeat  ~  nohtbeat \tabularnewline
means & 15 & -8.333 & -26.667 & -60 & -100 & 5 & 15 & 65 & 175 & 25 & 35 & 60 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166167&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]htbeat  ~  nohtbeat[/C][/ROW]
[ROW][C]means[/C][C]15[/C][C]-8.333[/C][C]-26.667[/C][C]-60[/C][C]-100[/C][C]5[/C][C]15[/C][C]65[/C][C]175[/C][C]25[/C][C]35[/C][C]60[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166167&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
htbeat ~ nohtbeat
means	15	-8.333	-26.667	-60	-100	5	15	65	175	25	35	60

ANOVA Statistics
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
nohtbeat	11	67736.667	6157.879	55.769	0
Residuals	8	883.333	110.417

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
nohtbeat & 11 & 67736.667 & 6157.879 & 55.769 & 0 \tabularnewline
Residuals & 8 & 883.333 & 110.417 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166167&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]nohtbeat[/C][C]11[/C][C]67736.667[/C][C]6157.879[/C][C]55.769[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]8[/C][C]883.333[/C][C]110.417[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166167&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166167&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
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
nohtbeat	11	67736.667	6157.879	55.769	0
Residuals	8	883.333	110.417

Tukey Honest Significant Difference Comparisons
	diff	lwr	upr	p adj
-25--10	-8.333	-50.22	33.553	0.997
-30--10	-26.667	-68.553	15.22	0.329
-45--10	-60	-101.886	-18.114	0.006
-50--10	-100	-156.196	-43.804	0.001
0--10	5	-51.196	61.196	1
10--10	15	-41.196	71.196	0.978
100--10	65	19.116	110.884	0.007
140--10	175	118.804	231.196	0
20--10	25	-31.196	81.196	0.716
25--10	35	-21.196	91.196	0.351
70--10	60	3.804	116.196	0.035
-30--25	-18.333	-55.798	19.131	0.618
-45--25	-51.667	-89.131	-14.202	0.008
-50--25	-91.667	-144.649	-38.684	0.002
0--25	13.333	-39.649	66.316	0.985
10--25	23.333	-29.649	76.316	0.726
100--25	73.333	31.447	115.22	0.002
140--25	183.333	130.351	236.316	0
20--25	33.333	-19.649	86.316	0.341
25--25	43.333	-9.649	96.316	0.131
70--25	68.333	15.351	121.316	0.012
-45--30	-33.333	-70.798	4.131	0.089
-50--30	-73.333	-126.316	-20.351	0.008
0--30	31.667	-21.316	84.649	0.395
10--30	41.667	-11.316	94.649	0.154
100--30	91.667	49.78	133.553	0
140--30	201.667	148.684	254.649	0
20--30	51.667	-1.316	104.649	0.057
25--30	61.667	8.684	114.649	0.022
70--30	86.667	33.684	139.649	0.003
-50--45	-40	-92.982	12.982	0.182
0--45	65	12.018	117.982	0.016
10--45	75	22.018	127.982	0.007
100--45	125	83.114	166.886	0
140--45	235	182.018	287.982	0
20--45	85	32.018	137.982	0.003
25--45	95	42.018	147.982	0.001
70--45	120	67.018	172.982	0
0--50	105	40.11	169.89	0.003
10--50	115	50.11	179.89	0.001
100--50	165	108.804	221.196	0
140--50	275	210.11	339.89	0
20--50	125	60.11	189.89	0.001
25--50	135	70.11	199.89	0
70--50	160	95.11	224.89	0
10-0	10	-54.89	74.89	1
100-0	60	3.804	116.196	0.035
140-0	170	105.11	234.89	0
20-0	20	-44.89	84.89	0.947
25-0	30	-34.89	94.89	0.678
70-0	55	-9.89	119.89	0.112
100-10	50	-6.196	106.196	0.089
140-10	160	95.11	224.89	0
20-10	10	-54.89	74.89	1
25-10	20	-44.89	84.89	0.947
70-10	45	-19.89	109.89	0.249
140-100	110	53.804	166.196	0.001
20-100	-40	-96.196	16.196	0.227
25-100	-30	-86.196	26.196	0.521
70-100	-5	-61.196	51.196	1
20-140	-150	-214.89	-85.11	0
25-140	-140	-204.89	-75.11	0
70-140	-115	-179.89	-50.11	0.001
25-20	10	-54.89	74.89	1
70-20	35	-29.89	99.89	0.509
70-25	25	-39.89	89.89	0.837

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
-25--10 & -8.333 & -50.22 & 33.553 & 0.997 \tabularnewline
-30--10 & -26.667 & -68.553 & 15.22 & 0.329 \tabularnewline
-45--10 & -60 & -101.886 & -18.114 & 0.006 \tabularnewline
-50--10 & -100 & -156.196 & -43.804 & 0.001 \tabularnewline
0--10 & 5 & -51.196 & 61.196 & 1 \tabularnewline
10--10 & 15 & -41.196 & 71.196 & 0.978 \tabularnewline
100--10 & 65 & 19.116 & 110.884 & 0.007 \tabularnewline
140--10 & 175 & 118.804 & 231.196 & 0 \tabularnewline
20--10 & 25 & -31.196 & 81.196 & 0.716 \tabularnewline
25--10 & 35 & -21.196 & 91.196 & 0.351 \tabularnewline
70--10 & 60 & 3.804 & 116.196 & 0.035 \tabularnewline
-30--25 & -18.333 & -55.798 & 19.131 & 0.618 \tabularnewline
-45--25 & -51.667 & -89.131 & -14.202 & 0.008 \tabularnewline
-50--25 & -91.667 & -144.649 & -38.684 & 0.002 \tabularnewline
0--25 & 13.333 & -39.649 & 66.316 & 0.985 \tabularnewline
10--25 & 23.333 & -29.649 & 76.316 & 0.726 \tabularnewline
100--25 & 73.333 & 31.447 & 115.22 & 0.002 \tabularnewline
140--25 & 183.333 & 130.351 & 236.316 & 0 \tabularnewline
20--25 & 33.333 & -19.649 & 86.316 & 0.341 \tabularnewline
25--25 & 43.333 & -9.649 & 96.316 & 0.131 \tabularnewline
70--25 & 68.333 & 15.351 & 121.316 & 0.012 \tabularnewline
-45--30 & -33.333 & -70.798 & 4.131 & 0.089 \tabularnewline
-50--30 & -73.333 & -126.316 & -20.351 & 0.008 \tabularnewline
0--30 & 31.667 & -21.316 & 84.649 & 0.395 \tabularnewline
10--30 & 41.667 & -11.316 & 94.649 & 0.154 \tabularnewline
100--30 & 91.667 & 49.78 & 133.553 & 0 \tabularnewline
140--30 & 201.667 & 148.684 & 254.649 & 0 \tabularnewline
20--30 & 51.667 & -1.316 & 104.649 & 0.057 \tabularnewline
25--30 & 61.667 & 8.684 & 114.649 & 0.022 \tabularnewline
70--30 & 86.667 & 33.684 & 139.649 & 0.003 \tabularnewline
-50--45 & -40 & -92.982 & 12.982 & 0.182 \tabularnewline
0--45 & 65 & 12.018 & 117.982 & 0.016 \tabularnewline
10--45 & 75 & 22.018 & 127.982 & 0.007 \tabularnewline
100--45 & 125 & 83.114 & 166.886 & 0 \tabularnewline
140--45 & 235 & 182.018 & 287.982 & 0 \tabularnewline
20--45 & 85 & 32.018 & 137.982 & 0.003 \tabularnewline
25--45 & 95 & 42.018 & 147.982 & 0.001 \tabularnewline
70--45 & 120 & 67.018 & 172.982 & 0 \tabularnewline
0--50 & 105 & 40.11 & 169.89 & 0.003 \tabularnewline
10--50 & 115 & 50.11 & 179.89 & 0.001 \tabularnewline
100--50 & 165 & 108.804 & 221.196 & 0 \tabularnewline
140--50 & 275 & 210.11 & 339.89 & 0 \tabularnewline
20--50 & 125 & 60.11 & 189.89 & 0.001 \tabularnewline
25--50 & 135 & 70.11 & 199.89 & 0 \tabularnewline
70--50 & 160 & 95.11 & 224.89 & 0 \tabularnewline
10-0 & 10 & -54.89 & 74.89 & 1 \tabularnewline
100-0 & 60 & 3.804 & 116.196 & 0.035 \tabularnewline
140-0 & 170 & 105.11 & 234.89 & 0 \tabularnewline
20-0 & 20 & -44.89 & 84.89 & 0.947 \tabularnewline
25-0 & 30 & -34.89 & 94.89 & 0.678 \tabularnewline
70-0 & 55 & -9.89 & 119.89 & 0.112 \tabularnewline
100-10 & 50 & -6.196 & 106.196 & 0.089 \tabularnewline
140-10 & 160 & 95.11 & 224.89 & 0 \tabularnewline
20-10 & 10 & -54.89 & 74.89 & 1 \tabularnewline
25-10 & 20 & -44.89 & 84.89 & 0.947 \tabularnewline
70-10 & 45 & -19.89 & 109.89 & 0.249 \tabularnewline
140-100 & 110 & 53.804 & 166.196 & 0.001 \tabularnewline
20-100 & -40 & -96.196 & 16.196 & 0.227 \tabularnewline
25-100 & -30 & -86.196 & 26.196 & 0.521 \tabularnewline
70-100 & -5 & -61.196 & 51.196 & 1 \tabularnewline
20-140 & -150 & -214.89 & -85.11 & 0 \tabularnewline
25-140 & -140 & -204.89 & -75.11 & 0 \tabularnewline
70-140 & -115 & -179.89 & -50.11 & 0.001 \tabularnewline
25-20 & 10 & -54.89 & 74.89 & 1 \tabularnewline
70-20 & 35 & -29.89 & 99.89 & 0.509 \tabularnewline
70-25 & 25 & -39.89 & 89.89 & 0.837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166167&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]-25--10[/C][C]-8.333[/C][C]-50.22[/C][C]33.553[/C][C]0.997[/C][/ROW]
[ROW][C]-30--10[/C][C]-26.667[/C][C]-68.553[/C][C]15.22[/C][C]0.329[/C][/ROW]
[ROW][C]-45--10[/C][C]-60[/C][C]-101.886[/C][C]-18.114[/C][C]0.006[/C][/ROW]
[ROW][C]-50--10[/C][C]-100[/C][C]-156.196[/C][C]-43.804[/C][C]0.001[/C][/ROW]
[ROW][C]0--10[/C][C]5[/C][C]-51.196[/C][C]61.196[/C][C]1[/C][/ROW]
[ROW][C]10--10[/C][C]15[/C][C]-41.196[/C][C]71.196[/C][C]0.978[/C][/ROW]
[ROW][C]100--10[/C][C]65[/C][C]19.116[/C][C]110.884[/C][C]0.007[/C][/ROW]
[ROW][C]140--10[/C][C]175[/C][C]118.804[/C][C]231.196[/C][C]0[/C][/ROW]
[ROW][C]20--10[/C][C]25[/C][C]-31.196[/C][C]81.196[/C][C]0.716[/C][/ROW]
[ROW][C]25--10[/C][C]35[/C][C]-21.196[/C][C]91.196[/C][C]0.351[/C][/ROW]
[ROW][C]70--10[/C][C]60[/C][C]3.804[/C][C]116.196[/C][C]0.035[/C][/ROW]
[ROW][C]-30--25[/C][C]-18.333[/C][C]-55.798[/C][C]19.131[/C][C]0.618[/C][/ROW]
[ROW][C]-45--25[/C][C]-51.667[/C][C]-89.131[/C][C]-14.202[/C][C]0.008[/C][/ROW]
[ROW][C]-50--25[/C][C]-91.667[/C][C]-144.649[/C][C]-38.684[/C][C]0.002[/C][/ROW]
[ROW][C]0--25[/C][C]13.333[/C][C]-39.649[/C][C]66.316[/C][C]0.985[/C][/ROW]
[ROW][C]10--25[/C][C]23.333[/C][C]-29.649[/C][C]76.316[/C][C]0.726[/C][/ROW]
[ROW][C]100--25[/C][C]73.333[/C][C]31.447[/C][C]115.22[/C][C]0.002[/C][/ROW]
[ROW][C]140--25[/C][C]183.333[/C][C]130.351[/C][C]236.316[/C][C]0[/C][/ROW]
[ROW][C]20--25[/C][C]33.333[/C][C]-19.649[/C][C]86.316[/C][C]0.341[/C][/ROW]
[ROW][C]25--25[/C][C]43.333[/C][C]-9.649[/C][C]96.316[/C][C]0.131[/C][/ROW]
[ROW][C]70--25[/C][C]68.333[/C][C]15.351[/C][C]121.316[/C][C]0.012[/C][/ROW]
[ROW][C]-45--30[/C][C]-33.333[/C][C]-70.798[/C][C]4.131[/C][C]0.089[/C][/ROW]
[ROW][C]-50--30[/C][C]-73.333[/C][C]-126.316[/C][C]-20.351[/C][C]0.008[/C][/ROW]
[ROW][C]0--30[/C][C]31.667[/C][C]-21.316[/C][C]84.649[/C][C]0.395[/C][/ROW]
[ROW][C]10--30[/C][C]41.667[/C][C]-11.316[/C][C]94.649[/C][C]0.154[/C][/ROW]
[ROW][C]100--30[/C][C]91.667[/C][C]49.78[/C][C]133.553[/C][C]0[/C][/ROW]
[ROW][C]140--30[/C][C]201.667[/C][C]148.684[/C][C]254.649[/C][C]0[/C][/ROW]
[ROW][C]20--30[/C][C]51.667[/C][C]-1.316[/C][C]104.649[/C][C]0.057[/C][/ROW]
[ROW][C]25--30[/C][C]61.667[/C][C]8.684[/C][C]114.649[/C][C]0.022[/C][/ROW]
[ROW][C]70--30[/C][C]86.667[/C][C]33.684[/C][C]139.649[/C][C]0.003[/C][/ROW]
[ROW][C]-50--45[/C][C]-40[/C][C]-92.982[/C][C]12.982[/C][C]0.182[/C][/ROW]
[ROW][C]0--45[/C][C]65[/C][C]12.018[/C][C]117.982[/C][C]0.016[/C][/ROW]
[ROW][C]10--45[/C][C]75[/C][C]22.018[/C][C]127.982[/C][C]0.007[/C][/ROW]
[ROW][C]100--45[/C][C]125[/C][C]83.114[/C][C]166.886[/C][C]0[/C][/ROW]
[ROW][C]140--45[/C][C]235[/C][C]182.018[/C][C]287.982[/C][C]0[/C][/ROW]
[ROW][C]20--45[/C][C]85[/C][C]32.018[/C][C]137.982[/C][C]0.003[/C][/ROW]
[ROW][C]25--45[/C][C]95[/C][C]42.018[/C][C]147.982[/C][C]0.001[/C][/ROW]
[ROW][C]70--45[/C][C]120[/C][C]67.018[/C][C]172.982[/C][C]0[/C][/ROW]
[ROW][C]0--50[/C][C]105[/C][C]40.11[/C][C]169.89[/C][C]0.003[/C][/ROW]
[ROW][C]10--50[/C][C]115[/C][C]50.11[/C][C]179.89[/C][C]0.001[/C][/ROW]
[ROW][C]100--50[/C][C]165[/C][C]108.804[/C][C]221.196[/C][C]0[/C][/ROW]
[ROW][C]140--50[/C][C]275[/C][C]210.11[/C][C]339.89[/C][C]0[/C][/ROW]
[ROW][C]20--50[/C][C]125[/C][C]60.11[/C][C]189.89[/C][C]0.001[/C][/ROW]
[ROW][C]25--50[/C][C]135[/C][C]70.11[/C][C]199.89[/C][C]0[/C][/ROW]
[ROW][C]70--50[/C][C]160[/C][C]95.11[/C][C]224.89[/C][C]0[/C][/ROW]
[ROW][C]10-0[/C][C]10[/C][C]-54.89[/C][C]74.89[/C][C]1[/C][/ROW]
[ROW][C]100-0[/C][C]60[/C][C]3.804[/C][C]116.196[/C][C]0.035[/C][/ROW]
[ROW][C]140-0[/C][C]170[/C][C]105.11[/C][C]234.89[/C][C]0[/C][/ROW]
[ROW][C]20-0[/C][C]20[/C][C]-44.89[/C][C]84.89[/C][C]0.947[/C][/ROW]
[ROW][C]25-0[/C][C]30[/C][C]-34.89[/C][C]94.89[/C][C]0.678[/C][/ROW]
[ROW][C]70-0[/C][C]55[/C][C]-9.89[/C][C]119.89[/C][C]0.112[/C][/ROW]
[ROW][C]100-10[/C][C]50[/C][C]-6.196[/C][C]106.196[/C][C]0.089[/C][/ROW]
[ROW][C]140-10[/C][C]160[/C][C]95.11[/C][C]224.89[/C][C]0[/C][/ROW]
[ROW][C]20-10[/C][C]10[/C][C]-54.89[/C][C]74.89[/C][C]1[/C][/ROW]
[ROW][C]25-10[/C][C]20[/C][C]-44.89[/C][C]84.89[/C][C]0.947[/C][/ROW]
[ROW][C]70-10[/C][C]45[/C][C]-19.89[/C][C]109.89[/C][C]0.249[/C][/ROW]
[ROW][C]140-100[/C][C]110[/C][C]53.804[/C][C]166.196[/C][C]0.001[/C][/ROW]
[ROW][C]20-100[/C][C]-40[/C][C]-96.196[/C][C]16.196[/C][C]0.227[/C][/ROW]
[ROW][C]25-100[/C][C]-30[/C][C]-86.196[/C][C]26.196[/C][C]0.521[/C][/ROW]
[ROW][C]70-100[/C][C]-5[/C][C]-61.196[/C][C]51.196[/C][C]1[/C][/ROW]
[ROW][C]20-140[/C][C]-150[/C][C]-214.89[/C][C]-85.11[/C][C]0[/C][/ROW]
[ROW][C]25-140[/C][C]-140[/C][C]-204.89[/C][C]-75.11[/C][C]0[/C][/ROW]
[ROW][C]70-140[/C][C]-115[/C][C]-179.89[/C][C]-50.11[/C][C]0.001[/C][/ROW]
[ROW][C]25-20[/C][C]10[/C][C]-54.89[/C][C]74.89[/C][C]1[/C][/ROW]
[ROW][C]70-20[/C][C]35[/C][C]-29.89[/C][C]99.89[/C][C]0.509[/C][/ROW]
[ROW][C]70-25[/C][C]25[/C][C]-39.89[/C][C]89.89[/C][C]0.837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166167&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166167&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
	diff	lwr	upr	p adj
-25--10	-8.333	-50.22	33.553	0.997
-30--10	-26.667	-68.553	15.22	0.329
-45--10	-60	-101.886	-18.114	0.006
-50--10	-100	-156.196	-43.804	0.001
0--10	5	-51.196	61.196	1
10--10	15	-41.196	71.196	0.978
100--10	65	19.116	110.884	0.007
140--10	175	118.804	231.196	0
20--10	25	-31.196	81.196	0.716
25--10	35	-21.196	91.196	0.351
70--10	60	3.804	116.196	0.035
-30--25	-18.333	-55.798	19.131	0.618
-45--25	-51.667	-89.131	-14.202	0.008
-50--25	-91.667	-144.649	-38.684	0.002
0--25	13.333	-39.649	66.316	0.985
10--25	23.333	-29.649	76.316	0.726
100--25	73.333	31.447	115.22	0.002
140--25	183.333	130.351	236.316	0
20--25	33.333	-19.649	86.316	0.341
25--25	43.333	-9.649	96.316	0.131
70--25	68.333	15.351	121.316	0.012
-45--30	-33.333	-70.798	4.131	0.089
-50--30	-73.333	-126.316	-20.351	0.008
0--30	31.667	-21.316	84.649	0.395
10--30	41.667	-11.316	94.649	0.154
100--30	91.667	49.78	133.553	0
140--30	201.667	148.684	254.649	0
20--30	51.667	-1.316	104.649	0.057
25--30	61.667	8.684	114.649	0.022
70--30	86.667	33.684	139.649	0.003
-50--45	-40	-92.982	12.982	0.182
0--45	65	12.018	117.982	0.016
10--45	75	22.018	127.982	0.007
100--45	125	83.114	166.886	0
140--45	235	182.018	287.982	0
20--45	85	32.018	137.982	0.003
25--45	95	42.018	147.982	0.001
70--45	120	67.018	172.982	0
0--50	105	40.11	169.89	0.003
10--50	115	50.11	179.89	0.001
100--50	165	108.804	221.196	0
140--50	275	210.11	339.89	0
20--50	125	60.11	189.89	0.001
25--50	135	70.11	199.89	0
70--50	160	95.11	224.89	0
10-0	10	-54.89	74.89	1
100-0	60	3.804	116.196	0.035
140-0	170	105.11	234.89	0
20-0	20	-44.89	84.89	0.947
25-0	30	-34.89	94.89	0.678
70-0	55	-9.89	119.89	0.112
100-10	50	-6.196	106.196	0.089
140-10	160	95.11	224.89	0
20-10	10	-54.89	74.89	1
25-10	20	-44.89	84.89	0.947
70-10	45	-19.89	109.89	0.249
140-100	110	53.804	166.196	0.001
20-100	-40	-96.196	16.196	0.227
25-100	-30	-86.196	26.196	0.521
70-100	-5	-61.196	51.196	1
20-140	-150	-214.89	-85.11	0
25-140	-140	-204.89	-75.11	0
70-140	-115	-179.89	-50.11	0.001
25-20	10	-54.89	74.89	1
70-20	35	-29.89	99.89	0.509
70-25	25	-39.89	89.89	0.837

Levenes Test for Homogeneity of Variance
	Df	F value	Pr(>F)
Group	11	0.677	0.731
	8

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 11 & 0.677 & 0.731 \tabularnewline
  & 8 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166167&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]0.677[/C][C]0.731[/C][/ROW]
[ROW][C] [/C][C]8[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166167&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166167&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
	Df	F value	Pr(>F)
Group	11	0.677	0.731
	8

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = two.sided ; par2 = 1 ; par3 = 2 ; par4 = T-Test ; par5 = unpaired ; par6 = 0.0 ; par7 = 0.95 ; par8 = 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()
}
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code