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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Tue, 10 May 2011 20:17:55 +0000

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/2011/May/10/t1305058635p8ui8e4bfewlwkv.htm/, Retrieved Mon, 13 May 2024 02:40:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121459, Retrieved Mon, 13 May 2024 02:40:00 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [opgave8oef3] [2011-05-10 20:17:55] [06ce09a0492afa6d4f67026fd1b7902e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121459&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121459&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121459&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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	133.397	3.81807997122464	8.72200000000001
2	142.38125	1.87254147706622	4.43600000000001
3	141.11725	7.43574212279223	16.148
4	134.7315	1.74861859763643	4.101
5	122.821	6.97371460079443	15.079
6	131.94725	3.12937814642675	6.669
7	133.8175	7.20243058511037	17.336
8	146.70175	2.36384155912926	5.14400000000001
9	153.33175	5.18520975949864	10.755
10	156.42175	1.48782534257217	3.22499999999999
11	163.89425	5.11214895290296	11.999
12	173.928	1.17709954266125	2.857
13	172.38775	1.66081332986783	3.512
14	174.62625	1.13711077589946	2.328
15	175.078	1.16294597180322	2.73599999999999
16	179.04	3.07174163410054	6.14699999999999
17	185.2445	4.42338667388085	9.41500000000002
18	193.9235	3.73758937462817	8.96
19	191.09275	3.4493018013312	8.411
20	182.15975	4.41337122654931	9.79400000000001
21	171.841	2.64563602938877	5.666
22	116.67875	30.7409304822848	69.714
23	134.9875	37.1794793625014	79.201
24	153.84025	1.46522521022083	3.226
25	146.1365	1.94966364620499	4.62899999999999
26	144.0845	6.75745250322437	15.517
27	127.2615	3.00681054718561	6.24099999999999
28	116.2825	14.6744532095748	31.716
29	119.4335	9.51043614492347	21.496
30	146.1475	1.64750083459767	3.54000000000002
31	144.5395	2.08357729238282	3.99799999999999
32	149.87375	1.88155403412534	4.26000000000002
33	157.5345	2.43284216504072	5.142
34	156.94025	2.85556513671113	6.03300000000002
35	144.65275	4.60320492519433	9.802
36	136.02125	5.21250946441986	11.694
37	121.10575	1.64662632372983	3.88200000000001
38	123.8155	1.33709348962591	2.84399999999999
39	116.9625	2.60988588511707	6.099
40	118.50825	1.51537330384298	3.279
41	123.244	2.40452517835296	5.584
42	115.16625	0.685840785702729	1.63800000000001
43	114.2	0.579485403900162	1.414
44	114.2485	3.13654507380334	6.777

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 133.397 & 3.81807997122464 & 8.72200000000001 \tabularnewline
2 & 142.38125 & 1.87254147706622 & 4.43600000000001 \tabularnewline
3 & 141.11725 & 7.43574212279223 & 16.148 \tabularnewline
4 & 134.7315 & 1.74861859763643 & 4.101 \tabularnewline
5 & 122.821 & 6.97371460079443 & 15.079 \tabularnewline
6 & 131.94725 & 3.12937814642675 & 6.669 \tabularnewline
7 & 133.8175 & 7.20243058511037 & 17.336 \tabularnewline
8 & 146.70175 & 2.36384155912926 & 5.14400000000001 \tabularnewline
9 & 153.33175 & 5.18520975949864 & 10.755 \tabularnewline
10 & 156.42175 & 1.48782534257217 & 3.22499999999999 \tabularnewline
11 & 163.89425 & 5.11214895290296 & 11.999 \tabularnewline
12 & 173.928 & 1.17709954266125 & 2.857 \tabularnewline
13 & 172.38775 & 1.66081332986783 & 3.512 \tabularnewline
14 & 174.62625 & 1.13711077589946 & 2.328 \tabularnewline
15 & 175.078 & 1.16294597180322 & 2.73599999999999 \tabularnewline
16 & 179.04 & 3.07174163410054 & 6.14699999999999 \tabularnewline
17 & 185.2445 & 4.42338667388085 & 9.41500000000002 \tabularnewline
18 & 193.9235 & 3.73758937462817 & 8.96 \tabularnewline
19 & 191.09275 & 3.4493018013312 & 8.411 \tabularnewline
20 & 182.15975 & 4.41337122654931 & 9.79400000000001 \tabularnewline
21 & 171.841 & 2.64563602938877 & 5.666 \tabularnewline
22 & 116.67875 & 30.7409304822848 & 69.714 \tabularnewline
23 & 134.9875 & 37.1794793625014 & 79.201 \tabularnewline
24 & 153.84025 & 1.46522521022083 & 3.226 \tabularnewline
25 & 146.1365 & 1.94966364620499 & 4.62899999999999 \tabularnewline
26 & 144.0845 & 6.75745250322437 & 15.517 \tabularnewline
27 & 127.2615 & 3.00681054718561 & 6.24099999999999 \tabularnewline
28 & 116.2825 & 14.6744532095748 & 31.716 \tabularnewline
29 & 119.4335 & 9.51043614492347 & 21.496 \tabularnewline
30 & 146.1475 & 1.64750083459767 & 3.54000000000002 \tabularnewline
31 & 144.5395 & 2.08357729238282 & 3.99799999999999 \tabularnewline
32 & 149.87375 & 1.88155403412534 & 4.26000000000002 \tabularnewline
33 & 157.5345 & 2.43284216504072 & 5.142 \tabularnewline
34 & 156.94025 & 2.85556513671113 & 6.03300000000002 \tabularnewline
35 & 144.65275 & 4.60320492519433 & 9.802 \tabularnewline
36 & 136.02125 & 5.21250946441986 & 11.694 \tabularnewline
37 & 121.10575 & 1.64662632372983 & 3.88200000000001 \tabularnewline
38 & 123.8155 & 1.33709348962591 & 2.84399999999999 \tabularnewline
39 & 116.9625 & 2.60988588511707 & 6.099 \tabularnewline
40 & 118.50825 & 1.51537330384298 & 3.279 \tabularnewline
41 & 123.244 & 2.40452517835296 & 5.584 \tabularnewline
42 & 115.16625 & 0.685840785702729 & 1.63800000000001 \tabularnewline
43 & 114.2 & 0.579485403900162 & 1.414 \tabularnewline
44 & 114.2485 & 3.13654507380334 & 6.777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121459&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]133.397[/C][C]3.81807997122464[/C][C]8.72200000000001[/C][/ROW]
[ROW][C]2[/C][C]142.38125[/C][C]1.87254147706622[/C][C]4.43600000000001[/C][/ROW]
[ROW][C]3[/C][C]141.11725[/C][C]7.43574212279223[/C][C]16.148[/C][/ROW]
[ROW][C]4[/C][C]134.7315[/C][C]1.74861859763643[/C][C]4.101[/C][/ROW]
[ROW][C]5[/C][C]122.821[/C][C]6.97371460079443[/C][C]15.079[/C][/ROW]
[ROW][C]6[/C][C]131.94725[/C][C]3.12937814642675[/C][C]6.669[/C][/ROW]
[ROW][C]7[/C][C]133.8175[/C][C]7.20243058511037[/C][C]17.336[/C][/ROW]
[ROW][C]8[/C][C]146.70175[/C][C]2.36384155912926[/C][C]5.14400000000001[/C][/ROW]
[ROW][C]9[/C][C]153.33175[/C][C]5.18520975949864[/C][C]10.755[/C][/ROW]
[ROW][C]10[/C][C]156.42175[/C][C]1.48782534257217[/C][C]3.22499999999999[/C][/ROW]
[ROW][C]11[/C][C]163.89425[/C][C]5.11214895290296[/C][C]11.999[/C][/ROW]
[ROW][C]12[/C][C]173.928[/C][C]1.17709954266125[/C][C]2.857[/C][/ROW]
[ROW][C]13[/C][C]172.38775[/C][C]1.66081332986783[/C][C]3.512[/C][/ROW]
[ROW][C]14[/C][C]174.62625[/C][C]1.13711077589946[/C][C]2.328[/C][/ROW]
[ROW][C]15[/C][C]175.078[/C][C]1.16294597180322[/C][C]2.73599999999999[/C][/ROW]
[ROW][C]16[/C][C]179.04[/C][C]3.07174163410054[/C][C]6.14699999999999[/C][/ROW]
[ROW][C]17[/C][C]185.2445[/C][C]4.42338667388085[/C][C]9.41500000000002[/C][/ROW]
[ROW][C]18[/C][C]193.9235[/C][C]3.73758937462817[/C][C]8.96[/C][/ROW]
[ROW][C]19[/C][C]191.09275[/C][C]3.4493018013312[/C][C]8.411[/C][/ROW]
[ROW][C]20[/C][C]182.15975[/C][C]4.41337122654931[/C][C]9.79400000000001[/C][/ROW]
[ROW][C]21[/C][C]171.841[/C][C]2.64563602938877[/C][C]5.666[/C][/ROW]
[ROW][C]22[/C][C]116.67875[/C][C]30.7409304822848[/C][C]69.714[/C][/ROW]
[ROW][C]23[/C][C]134.9875[/C][C]37.1794793625014[/C][C]79.201[/C][/ROW]
[ROW][C]24[/C][C]153.84025[/C][C]1.46522521022083[/C][C]3.226[/C][/ROW]
[ROW][C]25[/C][C]146.1365[/C][C]1.94966364620499[/C][C]4.62899999999999[/C][/ROW]
[ROW][C]26[/C][C]144.0845[/C][C]6.75745250322437[/C][C]15.517[/C][/ROW]
[ROW][C]27[/C][C]127.2615[/C][C]3.00681054718561[/C][C]6.24099999999999[/C][/ROW]
[ROW][C]28[/C][C]116.2825[/C][C]14.6744532095748[/C][C]31.716[/C][/ROW]
[ROW][C]29[/C][C]119.4335[/C][C]9.51043614492347[/C][C]21.496[/C][/ROW]
[ROW][C]30[/C][C]146.1475[/C][C]1.64750083459767[/C][C]3.54000000000002[/C][/ROW]
[ROW][C]31[/C][C]144.5395[/C][C]2.08357729238282[/C][C]3.99799999999999[/C][/ROW]
[ROW][C]32[/C][C]149.87375[/C][C]1.88155403412534[/C][C]4.26000000000002[/C][/ROW]
[ROW][C]33[/C][C]157.5345[/C][C]2.43284216504072[/C][C]5.142[/C][/ROW]
[ROW][C]34[/C][C]156.94025[/C][C]2.85556513671113[/C][C]6.03300000000002[/C][/ROW]
[ROW][C]35[/C][C]144.65275[/C][C]4.60320492519433[/C][C]9.802[/C][/ROW]
[ROW][C]36[/C][C]136.02125[/C][C]5.21250946441986[/C][C]11.694[/C][/ROW]
[ROW][C]37[/C][C]121.10575[/C][C]1.64662632372983[/C][C]3.88200000000001[/C][/ROW]
[ROW][C]38[/C][C]123.8155[/C][C]1.33709348962591[/C][C]2.84399999999999[/C][/ROW]
[ROW][C]39[/C][C]116.9625[/C][C]2.60988588511707[/C][C]6.099[/C][/ROW]
[ROW][C]40[/C][C]118.50825[/C][C]1.51537330384298[/C][C]3.279[/C][/ROW]
[ROW][C]41[/C][C]123.244[/C][C]2.40452517835296[/C][C]5.584[/C][/ROW]
[ROW][C]42[/C][C]115.16625[/C][C]0.685840785702729[/C][C]1.63800000000001[/C][/ROW]
[ROW][C]43[/C][C]114.2[/C][C]0.579485403900162[/C][C]1.414[/C][/ROW]
[ROW][C]44[/C][C]114.2485[/C][C]3.13654507380334[/C][C]6.777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121459&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121459&T=1

As an alternative you can also use a QR Code:

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

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	133.397	3.81807997122464	8.72200000000001
2	142.38125	1.87254147706622	4.43600000000001
3	141.11725	7.43574212279223	16.148
4	134.7315	1.74861859763643	4.101
5	122.821	6.97371460079443	15.079
6	131.94725	3.12937814642675	6.669
7	133.8175	7.20243058511037	17.336
8	146.70175	2.36384155912926	5.14400000000001
9	153.33175	5.18520975949864	10.755
10	156.42175	1.48782534257217	3.22499999999999
11	163.89425	5.11214895290296	11.999
12	173.928	1.17709954266125	2.857
13	172.38775	1.66081332986783	3.512
14	174.62625	1.13711077589946	2.328
15	175.078	1.16294597180322	2.73599999999999
16	179.04	3.07174163410054	6.14699999999999
17	185.2445	4.42338667388085	9.41500000000002
18	193.9235	3.73758937462817	8.96
19	191.09275	3.4493018013312	8.411
20	182.15975	4.41337122654931	9.79400000000001
21	171.841	2.64563602938877	5.666
22	116.67875	30.7409304822848	69.714
23	134.9875	37.1794793625014	79.201
24	153.84025	1.46522521022083	3.226
25	146.1365	1.94966364620499	4.62899999999999
26	144.0845	6.75745250322437	15.517
27	127.2615	3.00681054718561	6.24099999999999
28	116.2825	14.6744532095748	31.716
29	119.4335	9.51043614492347	21.496
30	146.1475	1.64750083459767	3.54000000000002
31	144.5395	2.08357729238282	3.99799999999999
32	149.87375	1.88155403412534	4.26000000000002
33	157.5345	2.43284216504072	5.142
34	156.94025	2.85556513671113	6.03300000000002
35	144.65275	4.60320492519433	9.802
36	136.02125	5.21250946441986	11.694
37	121.10575	1.64662632372983	3.88200000000001
38	123.8155	1.33709348962591	2.84399999999999
39	116.9625	2.60988588511707	6.099
40	118.50825	1.51537330384298	3.279
41	123.244	2.40452517835296	5.584
42	115.16625	0.685840785702729	1.63800000000001
43	114.2	0.579485403900162	1.414
44	114.2485	3.13654507380334	6.777

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	14.8391888043318
beta	-0.0687019968936686
S.D.	0.0450844947204806
T-STAT	-1.52384976962954
p-value	0.135041284577757

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 14.8391888043318 \tabularnewline
beta & -0.0687019968936686 \tabularnewline
S.D. & 0.0450844947204806 \tabularnewline
T-STAT & -1.52384976962954 \tabularnewline
p-value & 0.135041284577757 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121459&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.8391888043318[/C][/ROW]
[ROW][C]beta[/C][C]-0.0687019968936686[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0450844947204806[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.52384976962954[/C][/ROW]
[ROW][C]p-value[/C][C]0.135041284577757[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121459&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121459&T=2

As an alternative you can also use a QR Code:

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	14.8391888043318
beta	-0.0687019968936686
S.D.	0.0450844947204806
T-STAT	-1.52384976962954
p-value	0.135041284577757

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	4.6091910098928
beta	-0.70371884967156
S.D.	0.83740200464581
T-STAT	-0.840359642999908
p-value	0.405465479359852
Lambda	1.70371884967156

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.6091910098928 \tabularnewline
beta & -0.70371884967156 \tabularnewline
S.D. & 0.83740200464581 \tabularnewline
T-STAT & -0.840359642999908 \tabularnewline
p-value & 0.405465479359852 \tabularnewline
Lambda & 1.70371884967156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121459&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.6091910098928[/C][/ROW]
[ROW][C]beta[/C][C]-0.70371884967156[/C][/ROW]
[ROW][C]S.D.[/C][C]0.83740200464581[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.840359642999908[/C][/ROW]
[ROW][C]p-value[/C][C]0.405465479359852[/C][/ROW]
[ROW][C]Lambda[/C][C]1.70371884967156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121459&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121459&T=3

As an alternative you can also use a QR Code:

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	4.6091910098928
beta	-0.70371884967156
S.D.	0.83740200464581
T-STAT	-0.840359642999908
p-value	0.405465479359852
Lambda	1.70371884967156

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
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,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code