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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sun, 08 Jan 2017 09:32:08 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jan/08/t1483867946ynf00coekrrlw4e.htm/, Retrieved Wed, 15 May 2024 00:45:40 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 15 May 2024 00:45:40 +0200

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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	'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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.4105	0.0176763838342164	0.052
2	1.43525	0.00430908131951371	0.0129999999999999
3	1.41533333333333	0.00230940107675851	0.00800000000000001
4	1.42708333333333	0.00666685605791588	0.0249999999999999
5	1.44525	0.0020056737702646	0.00600000000000001
6	1.44741666666667	0.00206522432562456	0.0069999999999999
7	1.46258333333333	0.00437884030586209	0.0130000000000001
8	1.46058333333333	0.00271220585613639	0.0069999999999999
9	1.45625	0.000965307299163416	0.00299999999999989
10	1.44708333333333	0.00342340429539033	0.012
11	1.44025	0.0066895440801298	0.0189999999999999
12	1.42441666666667	0.00137895436890244	0.004
13	1.41408333333333	0.00380091695475837	0.0109999999999999
14	1.3905	0.0079943161626928	0.0270000000000001
15	1.37025	0.00413686310670734	0.0109999999999999
16	1.3755	0.00958692291139815	0.026
17	1.41125	0.0148882198703906	0.0410000000000001
18	1.43675	0.00062158156050809	0.002
19	1.44525	0.00804673846971552	0.022
20	1.47108333333333	0.00485158518299729	0.016
21	1.47616666666667	0.00111464085804542	0.004
22	1.47516666666667	0.00212488858887979	0.00700000000000012
23	1.47266666666667	0.0061693278451227	0.02
24	1.48891666666667	0.0058225007644066	0.0150000000000001
25	1.49558333333333	0.00450168318689256	0.0129999999999999
26	1.48383333333333	0.0015859229221975	0.00499999999999989
27	1.47458333333333	0.00290636709604442	0.0089999999999999
28	1.47258333333333	0.00188092498199126	0.00700000000000012
29	1.45775	0.00913658977558216	0.0249999999999999
30	1.43975	0.00488271533994247	0.0130000000000001
31	1.43816666666667	0.00478317759222757	0.0109999999999999
32	1.45108333333333	0.00357919069911147	0.0110000000000001
33	1.45533333333333	0.00249848438906954	0.00800000000000001
34	1.46208333333333	0.00239158879611376	0.0089999999999999
35	1.47791666666667	0.00407784108061945	0.0129999999999999
36	1.47216666666667	0.00715838139822297	0.02
37	1.45325	0.00746050205476087	0.02
38	1.43458333333333	0.00326018218490748	0.0130000000000001
39	1.43841666666667	0.0025390883594254	0.0089999999999999
40	1.40408333333333	0.0139769832441074	0.0329999999999999
41	1.38783333333333	0.00426045950004401	0.012
42	1.38441666666667	0.00362963392427424	0.0129999999999999
43	1.398	0.00127920429813368	0.004
44	1.39508333333333	0.00427377485545879	0.0110000000000001
45	1.3925	0.00183402190925745	0.00600000000000001
46	1.39708333333333	0.00246644143115812	0.0089999999999999
47	1.41533333333333	0.00524548868220605	0.014
48	1.42725	0.00256284642891103	0.00900000000000012
49	1.42683333333333	0.00368863939767235	0.012
50	1.42058333333333	0.0039648073054938	0.012
51	1.43575	0.00694294933400393	0.018
52	1.4435	0.00131425748134555	0.004
53	1.43475	0.00864580823289531	0.026
54	1.41233333333333	0.00123091490979333	0.004
55	1.40941666666667	0.00308834563931545	0.0089999999999999
56	1.39541666666667	0.0073664884113906	0.0210000000000001
57	1.38191666666667	0.00496273995679684	0.014
58	1.387	0.00674199862463241	0.0189999999999999
59	1.40616666666667	0.00212488858887978	0.00700000000000012
60	1.40366666666667	0.00400756859711798	0.012
61	1.40525	0.0110874622065565	0.0409999999999999
62	1.43758333333333	0.00219330938551907	0.00700000000000012
63	1.42625	0.0033608710992025	0.012
64	1.42658333333333	0.00124011240937214	0.004
65	1.43383333333333	0.00487728190572158	0.0130000000000001
66	1.43933333333333	0.00249848438906953	0.0069999999999999
67	1.426	0.00796583614283807	0.0249999999999999
68	1.40525	0.00433012701892222	0.0110000000000001
69	1.41475	0.00445431353756211	0.0129999999999999
70	1.42108333333333	0.00407784108061948	0.012
71	1.42941666666667	0.00116450015288134	0.00300000000000011
72	1.42166666666667	0.00305505046330389	0.01
73	1.42766666666667	0.0029024545516239	0.01
74	1.42808333333333	0.00271220585613642	0.00900000000000012
75	1.42408333333333	0.00433711955802534	0.0109999999999999
76	1.446	0.00424264068711931	0.0150000000000001
77	1.43325	0.00863528701423308	0.0290000000000001
78	1.41825	0.00252712556798503	0.00800000000000001
79	1.4225	0.00372948936304838	0.01
80	1.41933333333333	0.00143548112513057	0.004
81	1.41266666666667	0.0040301891075264	0.0130000000000001
82	1.42483333333333	0.00244329633276379	0.0069999999999999
83	1.41258333333333	0.00485158518299729	0.0149999999999999
84	1.408	0.00301511344577764	0.01
85	1.38658333333333	0.0158082736297015	0.048
86	1.35316666666667	0.00294906251153983	0.00800000000000001
87	1.36125	0.00402548698352705	0.0110000000000001
88	1.36583333333333	0.00613237805472401	0.018
89	1.33891666666667	0.0118203086664307	0.0350000000000001
90	1.29191666666667	0.0165774125261033	0.0429999999999999
91	1.23266666666667	0.0125505040343068	0.0399999999999998
92	1.21041666666667	0.00665320610797168	0.02
93	1.19233333333333	0.0073772787953447	0.0210000000000001
94	1.18741666666667	0.00253908835942542	0.00800000000000001
95	1.22716666666667	0.0204754102338006	0.0660000000000001
96	1.27758333333333	0.00577547059606927	0.016
97	1.29116666666667	0.00318614424524614	0.012
98	1.28941666666667	0.00519542339395206	0.016
99	1.27733333333333	0.00201509455376322	0.00700000000000012
100	1.26666666666667	0.00322865953984661	0.00900000000000012
101	1.29233333333333	0.0133575537589876	0.0410000000000001
102	1.30933333333333	0.00280691786106896	0.0069999999999999
103	1.31116666666667	0.00152752523165194	0.004
104	1.30866666666667	0.00253460892925168	0.0089999999999999
105	1.30458333333333	0.00372847356856867	0.00900000000000012
106	1.301	0.00371728150913835	0.01
107	1.29408333333333	0.000900336637378518	0.002
108	1.27425	0.0120463121478582	0.0349999999999999
109	1.23758333333333	0.0112205844389459	0.0349999999999999
110	1.20975	0.00808056028660477	0.0229999999999999
111	1.19008333333333	0.00559964825735155	0.0129999999999999
112	1.16633333333333	0.0109489172012025	0.0309999999999999
113	1.19708333333333	0.00403300775044528	0.0130000000000001
114	1.19091666666667	0.00494438769687104	0.0150000000000001
115	1.18675	0.00587947121926639	0.016
116	1.1885	0.0100317677224089	0.0290000000000001
117	1.17383333333333	0.00513160143944691	0.018
118	1.20291666666667	0.00427377485545876	0.012
119	1.187	0.00601513243260849	0.0190000000000001
120	1.16383333333333	0.0120667336345036	0.0389999999999999
121	1.11183333333333	0.0176935187585908	0.052

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.4105 & 0.0176763838342164 & 0.052 \tabularnewline
2 & 1.43525 & 0.00430908131951371 & 0.0129999999999999 \tabularnewline
3 & 1.41533333333333 & 0.00230940107675851 & 0.00800000000000001 \tabularnewline
4 & 1.42708333333333 & 0.00666685605791588 & 0.0249999999999999 \tabularnewline
5 & 1.44525 & 0.0020056737702646 & 0.00600000000000001 \tabularnewline
6 & 1.44741666666667 & 0.00206522432562456 & 0.0069999999999999 \tabularnewline
7 & 1.46258333333333 & 0.00437884030586209 & 0.0130000000000001 \tabularnewline
8 & 1.46058333333333 & 0.00271220585613639 & 0.0069999999999999 \tabularnewline
9 & 1.45625 & 0.000965307299163416 & 0.00299999999999989 \tabularnewline
10 & 1.44708333333333 & 0.00342340429539033 & 0.012 \tabularnewline
11 & 1.44025 & 0.0066895440801298 & 0.0189999999999999 \tabularnewline
12 & 1.42441666666667 & 0.00137895436890244 & 0.004 \tabularnewline
13 & 1.41408333333333 & 0.00380091695475837 & 0.0109999999999999 \tabularnewline
14 & 1.3905 & 0.0079943161626928 & 0.0270000000000001 \tabularnewline
15 & 1.37025 & 0.00413686310670734 & 0.0109999999999999 \tabularnewline
16 & 1.3755 & 0.00958692291139815 & 0.026 \tabularnewline
17 & 1.41125 & 0.0148882198703906 & 0.0410000000000001 \tabularnewline
18 & 1.43675 & 0.00062158156050809 & 0.002 \tabularnewline
19 & 1.44525 & 0.00804673846971552 & 0.022 \tabularnewline
20 & 1.47108333333333 & 0.00485158518299729 & 0.016 \tabularnewline
21 & 1.47616666666667 & 0.00111464085804542 & 0.004 \tabularnewline
22 & 1.47516666666667 & 0.00212488858887979 & 0.00700000000000012 \tabularnewline
23 & 1.47266666666667 & 0.0061693278451227 & 0.02 \tabularnewline
24 & 1.48891666666667 & 0.0058225007644066 & 0.0150000000000001 \tabularnewline
25 & 1.49558333333333 & 0.00450168318689256 & 0.0129999999999999 \tabularnewline
26 & 1.48383333333333 & 0.0015859229221975 & 0.00499999999999989 \tabularnewline
27 & 1.47458333333333 & 0.00290636709604442 & 0.0089999999999999 \tabularnewline
28 & 1.47258333333333 & 0.00188092498199126 & 0.00700000000000012 \tabularnewline
29 & 1.45775 & 0.00913658977558216 & 0.0249999999999999 \tabularnewline
30 & 1.43975 & 0.00488271533994247 & 0.0130000000000001 \tabularnewline
31 & 1.43816666666667 & 0.00478317759222757 & 0.0109999999999999 \tabularnewline
32 & 1.45108333333333 & 0.00357919069911147 & 0.0110000000000001 \tabularnewline
33 & 1.45533333333333 & 0.00249848438906954 & 0.00800000000000001 \tabularnewline
34 & 1.46208333333333 & 0.00239158879611376 & 0.0089999999999999 \tabularnewline
35 & 1.47791666666667 & 0.00407784108061945 & 0.0129999999999999 \tabularnewline
36 & 1.47216666666667 & 0.00715838139822297 & 0.02 \tabularnewline
37 & 1.45325 & 0.00746050205476087 & 0.02 \tabularnewline
38 & 1.43458333333333 & 0.00326018218490748 & 0.0130000000000001 \tabularnewline
39 & 1.43841666666667 & 0.0025390883594254 & 0.0089999999999999 \tabularnewline
40 & 1.40408333333333 & 0.0139769832441074 & 0.0329999999999999 \tabularnewline
41 & 1.38783333333333 & 0.00426045950004401 & 0.012 \tabularnewline
42 & 1.38441666666667 & 0.00362963392427424 & 0.0129999999999999 \tabularnewline
43 & 1.398 & 0.00127920429813368 & 0.004 \tabularnewline
44 & 1.39508333333333 & 0.00427377485545879 & 0.0110000000000001 \tabularnewline
45 & 1.3925 & 0.00183402190925745 & 0.00600000000000001 \tabularnewline
46 & 1.39708333333333 & 0.00246644143115812 & 0.0089999999999999 \tabularnewline
47 & 1.41533333333333 & 0.00524548868220605 & 0.014 \tabularnewline
48 & 1.42725 & 0.00256284642891103 & 0.00900000000000012 \tabularnewline
49 & 1.42683333333333 & 0.00368863939767235 & 0.012 \tabularnewline
50 & 1.42058333333333 & 0.0039648073054938 & 0.012 \tabularnewline
51 & 1.43575 & 0.00694294933400393 & 0.018 \tabularnewline
52 & 1.4435 & 0.00131425748134555 & 0.004 \tabularnewline
53 & 1.43475 & 0.00864580823289531 & 0.026 \tabularnewline
54 & 1.41233333333333 & 0.00123091490979333 & 0.004 \tabularnewline
55 & 1.40941666666667 & 0.00308834563931545 & 0.0089999999999999 \tabularnewline
56 & 1.39541666666667 & 0.0073664884113906 & 0.0210000000000001 \tabularnewline
57 & 1.38191666666667 & 0.00496273995679684 & 0.014 \tabularnewline
58 & 1.387 & 0.00674199862463241 & 0.0189999999999999 \tabularnewline
59 & 1.40616666666667 & 0.00212488858887978 & 0.00700000000000012 \tabularnewline
60 & 1.40366666666667 & 0.00400756859711798 & 0.012 \tabularnewline
61 & 1.40525 & 0.0110874622065565 & 0.0409999999999999 \tabularnewline
62 & 1.43758333333333 & 0.00219330938551907 & 0.00700000000000012 \tabularnewline
63 & 1.42625 & 0.0033608710992025 & 0.012 \tabularnewline
64 & 1.42658333333333 & 0.00124011240937214 & 0.004 \tabularnewline
65 & 1.43383333333333 & 0.00487728190572158 & 0.0130000000000001 \tabularnewline
66 & 1.43933333333333 & 0.00249848438906953 & 0.0069999999999999 \tabularnewline
67 & 1.426 & 0.00796583614283807 & 0.0249999999999999 \tabularnewline
68 & 1.40525 & 0.00433012701892222 & 0.0110000000000001 \tabularnewline
69 & 1.41475 & 0.00445431353756211 & 0.0129999999999999 \tabularnewline
70 & 1.42108333333333 & 0.00407784108061948 & 0.012 \tabularnewline
71 & 1.42941666666667 & 0.00116450015288134 & 0.00300000000000011 \tabularnewline
72 & 1.42166666666667 & 0.00305505046330389 & 0.01 \tabularnewline
73 & 1.42766666666667 & 0.0029024545516239 & 0.01 \tabularnewline
74 & 1.42808333333333 & 0.00271220585613642 & 0.00900000000000012 \tabularnewline
75 & 1.42408333333333 & 0.00433711955802534 & 0.0109999999999999 \tabularnewline
76 & 1.446 & 0.00424264068711931 & 0.0150000000000001 \tabularnewline
77 & 1.43325 & 0.00863528701423308 & 0.0290000000000001 \tabularnewline
78 & 1.41825 & 0.00252712556798503 & 0.00800000000000001 \tabularnewline
79 & 1.4225 & 0.00372948936304838 & 0.01 \tabularnewline
80 & 1.41933333333333 & 0.00143548112513057 & 0.004 \tabularnewline
81 & 1.41266666666667 & 0.0040301891075264 & 0.0130000000000001 \tabularnewline
82 & 1.42483333333333 & 0.00244329633276379 & 0.0069999999999999 \tabularnewline
83 & 1.41258333333333 & 0.00485158518299729 & 0.0149999999999999 \tabularnewline
84 & 1.408 & 0.00301511344577764 & 0.01 \tabularnewline
85 & 1.38658333333333 & 0.0158082736297015 & 0.048 \tabularnewline
86 & 1.35316666666667 & 0.00294906251153983 & 0.00800000000000001 \tabularnewline
87 & 1.36125 & 0.00402548698352705 & 0.0110000000000001 \tabularnewline
88 & 1.36583333333333 & 0.00613237805472401 & 0.018 \tabularnewline
89 & 1.33891666666667 & 0.0118203086664307 & 0.0350000000000001 \tabularnewline
90 & 1.29191666666667 & 0.0165774125261033 & 0.0429999999999999 \tabularnewline
91 & 1.23266666666667 & 0.0125505040343068 & 0.0399999999999998 \tabularnewline
92 & 1.21041666666667 & 0.00665320610797168 & 0.02 \tabularnewline
93 & 1.19233333333333 & 0.0073772787953447 & 0.0210000000000001 \tabularnewline
94 & 1.18741666666667 & 0.00253908835942542 & 0.00800000000000001 \tabularnewline
95 & 1.22716666666667 & 0.0204754102338006 & 0.0660000000000001 \tabularnewline
96 & 1.27758333333333 & 0.00577547059606927 & 0.016 \tabularnewline
97 & 1.29116666666667 & 0.00318614424524614 & 0.012 \tabularnewline
98 & 1.28941666666667 & 0.00519542339395206 & 0.016 \tabularnewline
99 & 1.27733333333333 & 0.00201509455376322 & 0.00700000000000012 \tabularnewline
100 & 1.26666666666667 & 0.00322865953984661 & 0.00900000000000012 \tabularnewline
101 & 1.29233333333333 & 0.0133575537589876 & 0.0410000000000001 \tabularnewline
102 & 1.30933333333333 & 0.00280691786106896 & 0.0069999999999999 \tabularnewline
103 & 1.31116666666667 & 0.00152752523165194 & 0.004 \tabularnewline
104 & 1.30866666666667 & 0.00253460892925168 & 0.0089999999999999 \tabularnewline
105 & 1.30458333333333 & 0.00372847356856867 & 0.00900000000000012 \tabularnewline
106 & 1.301 & 0.00371728150913835 & 0.01 \tabularnewline
107 & 1.29408333333333 & 0.000900336637378518 & 0.002 \tabularnewline
108 & 1.27425 & 0.0120463121478582 & 0.0349999999999999 \tabularnewline
109 & 1.23758333333333 & 0.0112205844389459 & 0.0349999999999999 \tabularnewline
110 & 1.20975 & 0.00808056028660477 & 0.0229999999999999 \tabularnewline
111 & 1.19008333333333 & 0.00559964825735155 & 0.0129999999999999 \tabularnewline
112 & 1.16633333333333 & 0.0109489172012025 & 0.0309999999999999 \tabularnewline
113 & 1.19708333333333 & 0.00403300775044528 & 0.0130000000000001 \tabularnewline
114 & 1.19091666666667 & 0.00494438769687104 & 0.0150000000000001 \tabularnewline
115 & 1.18675 & 0.00587947121926639 & 0.016 \tabularnewline
116 & 1.1885 & 0.0100317677224089 & 0.0290000000000001 \tabularnewline
117 & 1.17383333333333 & 0.00513160143944691 & 0.018 \tabularnewline
118 & 1.20291666666667 & 0.00427377485545876 & 0.012 \tabularnewline
119 & 1.187 & 0.00601513243260849 & 0.0190000000000001 \tabularnewline
120 & 1.16383333333333 & 0.0120667336345036 & 0.0389999999999999 \tabularnewline
121 & 1.11183333333333 & 0.0176935187585908 & 0.052 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]1.4105[/C][C]0.0176763838342164[/C][C]0.052[/C][/ROW]
[ROW][C]2[/C][C]1.43525[/C][C]0.00430908131951371[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]3[/C][C]1.41533333333333[/C][C]0.00230940107675851[/C][C]0.00800000000000001[/C][/ROW]
[ROW][C]4[/C][C]1.42708333333333[/C][C]0.00666685605791588[/C][C]0.0249999999999999[/C][/ROW]
[ROW][C]5[/C][C]1.44525[/C][C]0.0020056737702646[/C][C]0.00600000000000001[/C][/ROW]
[ROW][C]6[/C][C]1.44741666666667[/C][C]0.00206522432562456[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]7[/C][C]1.46258333333333[/C][C]0.00437884030586209[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]8[/C][C]1.46058333333333[/C][C]0.00271220585613639[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]9[/C][C]1.45625[/C][C]0.000965307299163416[/C][C]0.00299999999999989[/C][/ROW]
[ROW][C]10[/C][C]1.44708333333333[/C][C]0.00342340429539033[/C][C]0.012[/C][/ROW]
[ROW][C]11[/C][C]1.44025[/C][C]0.0066895440801298[/C][C]0.0189999999999999[/C][/ROW]
[ROW][C]12[/C][C]1.42441666666667[/C][C]0.00137895436890244[/C][C]0.004[/C][/ROW]
[ROW][C]13[/C][C]1.41408333333333[/C][C]0.00380091695475837[/C][C]0.0109999999999999[/C][/ROW]
[ROW][C]14[/C][C]1.3905[/C][C]0.0079943161626928[/C][C]0.0270000000000001[/C][/ROW]
[ROW][C]15[/C][C]1.37025[/C][C]0.00413686310670734[/C][C]0.0109999999999999[/C][/ROW]
[ROW][C]16[/C][C]1.3755[/C][C]0.00958692291139815[/C][C]0.026[/C][/ROW]
[ROW][C]17[/C][C]1.41125[/C][C]0.0148882198703906[/C][C]0.0410000000000001[/C][/ROW]
[ROW][C]18[/C][C]1.43675[/C][C]0.00062158156050809[/C][C]0.002[/C][/ROW]
[ROW][C]19[/C][C]1.44525[/C][C]0.00804673846971552[/C][C]0.022[/C][/ROW]
[ROW][C]20[/C][C]1.47108333333333[/C][C]0.00485158518299729[/C][C]0.016[/C][/ROW]
[ROW][C]21[/C][C]1.47616666666667[/C][C]0.00111464085804542[/C][C]0.004[/C][/ROW]
[ROW][C]22[/C][C]1.47516666666667[/C][C]0.00212488858887979[/C][C]0.00700000000000012[/C][/ROW]
[ROW][C]23[/C][C]1.47266666666667[/C][C]0.0061693278451227[/C][C]0.02[/C][/ROW]
[ROW][C]24[/C][C]1.48891666666667[/C][C]0.0058225007644066[/C][C]0.0150000000000001[/C][/ROW]
[ROW][C]25[/C][C]1.49558333333333[/C][C]0.00450168318689256[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]26[/C][C]1.48383333333333[/C][C]0.0015859229221975[/C][C]0.00499999999999989[/C][/ROW]
[ROW][C]27[/C][C]1.47458333333333[/C][C]0.00290636709604442[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]28[/C][C]1.47258333333333[/C][C]0.00188092498199126[/C][C]0.00700000000000012[/C][/ROW]
[ROW][C]29[/C][C]1.45775[/C][C]0.00913658977558216[/C][C]0.0249999999999999[/C][/ROW]
[ROW][C]30[/C][C]1.43975[/C][C]0.00488271533994247[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]31[/C][C]1.43816666666667[/C][C]0.00478317759222757[/C][C]0.0109999999999999[/C][/ROW]
[ROW][C]32[/C][C]1.45108333333333[/C][C]0.00357919069911147[/C][C]0.0110000000000001[/C][/ROW]
[ROW][C]33[/C][C]1.45533333333333[/C][C]0.00249848438906954[/C][C]0.00800000000000001[/C][/ROW]
[ROW][C]34[/C][C]1.46208333333333[/C][C]0.00239158879611376[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]35[/C][C]1.47791666666667[/C][C]0.00407784108061945[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]36[/C][C]1.47216666666667[/C][C]0.00715838139822297[/C][C]0.02[/C][/ROW]
[ROW][C]37[/C][C]1.45325[/C][C]0.00746050205476087[/C][C]0.02[/C][/ROW]
[ROW][C]38[/C][C]1.43458333333333[/C][C]0.00326018218490748[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]39[/C][C]1.43841666666667[/C][C]0.0025390883594254[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]40[/C][C]1.40408333333333[/C][C]0.0139769832441074[/C][C]0.0329999999999999[/C][/ROW]
[ROW][C]41[/C][C]1.38783333333333[/C][C]0.00426045950004401[/C][C]0.012[/C][/ROW]
[ROW][C]42[/C][C]1.38441666666667[/C][C]0.00362963392427424[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]43[/C][C]1.398[/C][C]0.00127920429813368[/C][C]0.004[/C][/ROW]
[ROW][C]44[/C][C]1.39508333333333[/C][C]0.00427377485545879[/C][C]0.0110000000000001[/C][/ROW]
[ROW][C]45[/C][C]1.3925[/C][C]0.00183402190925745[/C][C]0.00600000000000001[/C][/ROW]
[ROW][C]46[/C][C]1.39708333333333[/C][C]0.00246644143115812[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]47[/C][C]1.41533333333333[/C][C]0.00524548868220605[/C][C]0.014[/C][/ROW]
[ROW][C]48[/C][C]1.42725[/C][C]0.00256284642891103[/C][C]0.00900000000000012[/C][/ROW]
[ROW][C]49[/C][C]1.42683333333333[/C][C]0.00368863939767235[/C][C]0.012[/C][/ROW]
[ROW][C]50[/C][C]1.42058333333333[/C][C]0.0039648073054938[/C][C]0.012[/C][/ROW]
[ROW][C]51[/C][C]1.43575[/C][C]0.00694294933400393[/C][C]0.018[/C][/ROW]
[ROW][C]52[/C][C]1.4435[/C][C]0.00131425748134555[/C][C]0.004[/C][/ROW]
[ROW][C]53[/C][C]1.43475[/C][C]0.00864580823289531[/C][C]0.026[/C][/ROW]
[ROW][C]54[/C][C]1.41233333333333[/C][C]0.00123091490979333[/C][C]0.004[/C][/ROW]
[ROW][C]55[/C][C]1.40941666666667[/C][C]0.00308834563931545[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]56[/C][C]1.39541666666667[/C][C]0.0073664884113906[/C][C]0.0210000000000001[/C][/ROW]
[ROW][C]57[/C][C]1.38191666666667[/C][C]0.00496273995679684[/C][C]0.014[/C][/ROW]
[ROW][C]58[/C][C]1.387[/C][C]0.00674199862463241[/C][C]0.0189999999999999[/C][/ROW]
[ROW][C]59[/C][C]1.40616666666667[/C][C]0.00212488858887978[/C][C]0.00700000000000012[/C][/ROW]
[ROW][C]60[/C][C]1.40366666666667[/C][C]0.00400756859711798[/C][C]0.012[/C][/ROW]
[ROW][C]61[/C][C]1.40525[/C][C]0.0110874622065565[/C][C]0.0409999999999999[/C][/ROW]
[ROW][C]62[/C][C]1.43758333333333[/C][C]0.00219330938551907[/C][C]0.00700000000000012[/C][/ROW]
[ROW][C]63[/C][C]1.42625[/C][C]0.0033608710992025[/C][C]0.012[/C][/ROW]
[ROW][C]64[/C][C]1.42658333333333[/C][C]0.00124011240937214[/C][C]0.004[/C][/ROW]
[ROW][C]65[/C][C]1.43383333333333[/C][C]0.00487728190572158[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]66[/C][C]1.43933333333333[/C][C]0.00249848438906953[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]67[/C][C]1.426[/C][C]0.00796583614283807[/C][C]0.0249999999999999[/C][/ROW]
[ROW][C]68[/C][C]1.40525[/C][C]0.00433012701892222[/C][C]0.0110000000000001[/C][/ROW]
[ROW][C]69[/C][C]1.41475[/C][C]0.00445431353756211[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]70[/C][C]1.42108333333333[/C][C]0.00407784108061948[/C][C]0.012[/C][/ROW]
[ROW][C]71[/C][C]1.42941666666667[/C][C]0.00116450015288134[/C][C]0.00300000000000011[/C][/ROW]
[ROW][C]72[/C][C]1.42166666666667[/C][C]0.00305505046330389[/C][C]0.01[/C][/ROW]
[ROW][C]73[/C][C]1.42766666666667[/C][C]0.0029024545516239[/C][C]0.01[/C][/ROW]
[ROW][C]74[/C][C]1.42808333333333[/C][C]0.00271220585613642[/C][C]0.00900000000000012[/C][/ROW]
[ROW][C]75[/C][C]1.42408333333333[/C][C]0.00433711955802534[/C][C]0.0109999999999999[/C][/ROW]
[ROW][C]76[/C][C]1.446[/C][C]0.00424264068711931[/C][C]0.0150000000000001[/C][/ROW]
[ROW][C]77[/C][C]1.43325[/C][C]0.00863528701423308[/C][C]0.0290000000000001[/C][/ROW]
[ROW][C]78[/C][C]1.41825[/C][C]0.00252712556798503[/C][C]0.00800000000000001[/C][/ROW]
[ROW][C]79[/C][C]1.4225[/C][C]0.00372948936304838[/C][C]0.01[/C][/ROW]
[ROW][C]80[/C][C]1.41933333333333[/C][C]0.00143548112513057[/C][C]0.004[/C][/ROW]
[ROW][C]81[/C][C]1.41266666666667[/C][C]0.0040301891075264[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]82[/C][C]1.42483333333333[/C][C]0.00244329633276379[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]83[/C][C]1.41258333333333[/C][C]0.00485158518299729[/C][C]0.0149999999999999[/C][/ROW]
[ROW][C]84[/C][C]1.408[/C][C]0.00301511344577764[/C][C]0.01[/C][/ROW]
[ROW][C]85[/C][C]1.38658333333333[/C][C]0.0158082736297015[/C][C]0.048[/C][/ROW]
[ROW][C]86[/C][C]1.35316666666667[/C][C]0.00294906251153983[/C][C]0.00800000000000001[/C][/ROW]
[ROW][C]87[/C][C]1.36125[/C][C]0.00402548698352705[/C][C]0.0110000000000001[/C][/ROW]
[ROW][C]88[/C][C]1.36583333333333[/C][C]0.00613237805472401[/C][C]0.018[/C][/ROW]
[ROW][C]89[/C][C]1.33891666666667[/C][C]0.0118203086664307[/C][C]0.0350000000000001[/C][/ROW]
[ROW][C]90[/C][C]1.29191666666667[/C][C]0.0165774125261033[/C][C]0.0429999999999999[/C][/ROW]
[ROW][C]91[/C][C]1.23266666666667[/C][C]0.0125505040343068[/C][C]0.0399999999999998[/C][/ROW]
[ROW][C]92[/C][C]1.21041666666667[/C][C]0.00665320610797168[/C][C]0.02[/C][/ROW]
[ROW][C]93[/C][C]1.19233333333333[/C][C]0.0073772787953447[/C][C]0.0210000000000001[/C][/ROW]
[ROW][C]94[/C][C]1.18741666666667[/C][C]0.00253908835942542[/C][C]0.00800000000000001[/C][/ROW]
[ROW][C]95[/C][C]1.22716666666667[/C][C]0.0204754102338006[/C][C]0.0660000000000001[/C][/ROW]
[ROW][C]96[/C][C]1.27758333333333[/C][C]0.00577547059606927[/C][C]0.016[/C][/ROW]
[ROW][C]97[/C][C]1.29116666666667[/C][C]0.00318614424524614[/C][C]0.012[/C][/ROW]
[ROW][C]98[/C][C]1.28941666666667[/C][C]0.00519542339395206[/C][C]0.016[/C][/ROW]
[ROW][C]99[/C][C]1.27733333333333[/C][C]0.00201509455376322[/C][C]0.00700000000000012[/C][/ROW]
[ROW][C]100[/C][C]1.26666666666667[/C][C]0.00322865953984661[/C][C]0.00900000000000012[/C][/ROW]
[ROW][C]101[/C][C]1.29233333333333[/C][C]0.0133575537589876[/C][C]0.0410000000000001[/C][/ROW]
[ROW][C]102[/C][C]1.30933333333333[/C][C]0.00280691786106896[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]103[/C][C]1.31116666666667[/C][C]0.00152752523165194[/C][C]0.004[/C][/ROW]
[ROW][C]104[/C][C]1.30866666666667[/C][C]0.00253460892925168[/C][C]0.0089999999999999[/C][/ROW]
[ROW][C]105[/C][C]1.30458333333333[/C][C]0.00372847356856867[/C][C]0.00900000000000012[/C][/ROW]
[ROW][C]106[/C][C]1.301[/C][C]0.00371728150913835[/C][C]0.01[/C][/ROW]
[ROW][C]107[/C][C]1.29408333333333[/C][C]0.000900336637378518[/C][C]0.002[/C][/ROW]
[ROW][C]108[/C][C]1.27425[/C][C]0.0120463121478582[/C][C]0.0349999999999999[/C][/ROW]
[ROW][C]109[/C][C]1.23758333333333[/C][C]0.0112205844389459[/C][C]0.0349999999999999[/C][/ROW]
[ROW][C]110[/C][C]1.20975[/C][C]0.00808056028660477[/C][C]0.0229999999999999[/C][/ROW]
[ROW][C]111[/C][C]1.19008333333333[/C][C]0.00559964825735155[/C][C]0.0129999999999999[/C][/ROW]
[ROW][C]112[/C][C]1.16633333333333[/C][C]0.0109489172012025[/C][C]0.0309999999999999[/C][/ROW]
[ROW][C]113[/C][C]1.19708333333333[/C][C]0.00403300775044528[/C][C]0.0130000000000001[/C][/ROW]
[ROW][C]114[/C][C]1.19091666666667[/C][C]0.00494438769687104[/C][C]0.0150000000000001[/C][/ROW]
[ROW][C]115[/C][C]1.18675[/C][C]0.00587947121926639[/C][C]0.016[/C][/ROW]
[ROW][C]116[/C][C]1.1885[/C][C]0.0100317677224089[/C][C]0.0290000000000001[/C][/ROW]
[ROW][C]117[/C][C]1.17383333333333[/C][C]0.00513160143944691[/C][C]0.018[/C][/ROW]
[ROW][C]118[/C][C]1.20291666666667[/C][C]0.00427377485545876[/C][C]0.012[/C][/ROW]
[ROW][C]119[/C][C]1.187[/C][C]0.00601513243260849[/C][C]0.0190000000000001[/C][/ROW]
[ROW][C]120[/C][C]1.16383333333333[/C][C]0.0120667336345036[/C][C]0.0389999999999999[/C][/ROW]
[ROW][C]121[/C][C]1.11183333333333[/C][C]0.0176935187585908[/C][C]0.052[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	1.4105	0.0176763838342164	0.052
2	1.43525	0.00430908131951371	0.0129999999999999
3	1.41533333333333	0.00230940107675851	0.00800000000000001
4	1.42708333333333	0.00666685605791588	0.0249999999999999
5	1.44525	0.0020056737702646	0.00600000000000001
6	1.44741666666667	0.00206522432562456	0.0069999999999999
7	1.46258333333333	0.00437884030586209	0.0130000000000001
8	1.46058333333333	0.00271220585613639	0.0069999999999999
9	1.45625	0.000965307299163416	0.00299999999999989
10	1.44708333333333	0.00342340429539033	0.012
11	1.44025	0.0066895440801298	0.0189999999999999
12	1.42441666666667	0.00137895436890244	0.004
13	1.41408333333333	0.00380091695475837	0.0109999999999999
14	1.3905	0.0079943161626928	0.0270000000000001
15	1.37025	0.00413686310670734	0.0109999999999999
16	1.3755	0.00958692291139815	0.026
17	1.41125	0.0148882198703906	0.0410000000000001
18	1.43675	0.00062158156050809	0.002
19	1.44525	0.00804673846971552	0.022
20	1.47108333333333	0.00485158518299729	0.016
21	1.47616666666667	0.00111464085804542	0.004
22	1.47516666666667	0.00212488858887979	0.00700000000000012
23	1.47266666666667	0.0061693278451227	0.02
24	1.48891666666667	0.0058225007644066	0.0150000000000001
25	1.49558333333333	0.00450168318689256	0.0129999999999999
26	1.48383333333333	0.0015859229221975	0.00499999999999989
27	1.47458333333333	0.00290636709604442	0.0089999999999999
28	1.47258333333333	0.00188092498199126	0.00700000000000012
29	1.45775	0.00913658977558216	0.0249999999999999
30	1.43975	0.00488271533994247	0.0130000000000001
31	1.43816666666667	0.00478317759222757	0.0109999999999999
32	1.45108333333333	0.00357919069911147	0.0110000000000001
33	1.45533333333333	0.00249848438906954	0.00800000000000001
34	1.46208333333333	0.00239158879611376	0.0089999999999999
35	1.47791666666667	0.00407784108061945	0.0129999999999999
36	1.47216666666667	0.00715838139822297	0.02
37	1.45325	0.00746050205476087	0.02
38	1.43458333333333	0.00326018218490748	0.0130000000000001
39	1.43841666666667	0.0025390883594254	0.0089999999999999
40	1.40408333333333	0.0139769832441074	0.0329999999999999
41	1.38783333333333	0.00426045950004401	0.012
42	1.38441666666667	0.00362963392427424	0.0129999999999999
43	1.398	0.00127920429813368	0.004
44	1.39508333333333	0.00427377485545879	0.0110000000000001
45	1.3925	0.00183402190925745	0.00600000000000001
46	1.39708333333333	0.00246644143115812	0.0089999999999999
47	1.41533333333333	0.00524548868220605	0.014
48	1.42725	0.00256284642891103	0.00900000000000012
49	1.42683333333333	0.00368863939767235	0.012
50	1.42058333333333	0.0039648073054938	0.012
51	1.43575	0.00694294933400393	0.018
52	1.4435	0.00131425748134555	0.004
53	1.43475	0.00864580823289531	0.026
54	1.41233333333333	0.00123091490979333	0.004
55	1.40941666666667	0.00308834563931545	0.0089999999999999
56	1.39541666666667	0.0073664884113906	0.0210000000000001
57	1.38191666666667	0.00496273995679684	0.014
58	1.387	0.00674199862463241	0.0189999999999999
59	1.40616666666667	0.00212488858887978	0.00700000000000012
60	1.40366666666667	0.00400756859711798	0.012
61	1.40525	0.0110874622065565	0.0409999999999999
62	1.43758333333333	0.00219330938551907	0.00700000000000012
63	1.42625	0.0033608710992025	0.012
64	1.42658333333333	0.00124011240937214	0.004
65	1.43383333333333	0.00487728190572158	0.0130000000000001
66	1.43933333333333	0.00249848438906953	0.0069999999999999
67	1.426	0.00796583614283807	0.0249999999999999
68	1.40525	0.00433012701892222	0.0110000000000001
69	1.41475	0.00445431353756211	0.0129999999999999
70	1.42108333333333	0.00407784108061948	0.012
71	1.42941666666667	0.00116450015288134	0.00300000000000011
72	1.42166666666667	0.00305505046330389	0.01
73	1.42766666666667	0.0029024545516239	0.01
74	1.42808333333333	0.00271220585613642	0.00900000000000012
75	1.42408333333333	0.00433711955802534	0.0109999999999999
76	1.446	0.00424264068711931	0.0150000000000001
77	1.43325	0.00863528701423308	0.0290000000000001
78	1.41825	0.00252712556798503	0.00800000000000001
79	1.4225	0.00372948936304838	0.01
80	1.41933333333333	0.00143548112513057	0.004
81	1.41266666666667	0.0040301891075264	0.0130000000000001
82	1.42483333333333	0.00244329633276379	0.0069999999999999
83	1.41258333333333	0.00485158518299729	0.0149999999999999
84	1.408	0.00301511344577764	0.01
85	1.38658333333333	0.0158082736297015	0.048
86	1.35316666666667	0.00294906251153983	0.00800000000000001
87	1.36125	0.00402548698352705	0.0110000000000001
88	1.36583333333333	0.00613237805472401	0.018
89	1.33891666666667	0.0118203086664307	0.0350000000000001
90	1.29191666666667	0.0165774125261033	0.0429999999999999
91	1.23266666666667	0.0125505040343068	0.0399999999999998
92	1.21041666666667	0.00665320610797168	0.02
93	1.19233333333333	0.0073772787953447	0.0210000000000001
94	1.18741666666667	0.00253908835942542	0.00800000000000001
95	1.22716666666667	0.0204754102338006	0.0660000000000001
96	1.27758333333333	0.00577547059606927	0.016
97	1.29116666666667	0.00318614424524614	0.012
98	1.28941666666667	0.00519542339395206	0.016
99	1.27733333333333	0.00201509455376322	0.00700000000000012
100	1.26666666666667	0.00322865953984661	0.00900000000000012
101	1.29233333333333	0.0133575537589876	0.0410000000000001
102	1.30933333333333	0.00280691786106896	0.0069999999999999
103	1.31116666666667	0.00152752523165194	0.004
104	1.30866666666667	0.00253460892925168	0.0089999999999999
105	1.30458333333333	0.00372847356856867	0.00900000000000012
106	1.301	0.00371728150913835	0.01
107	1.29408333333333	0.000900336637378518	0.002
108	1.27425	0.0120463121478582	0.0349999999999999
109	1.23758333333333	0.0112205844389459	0.0349999999999999
110	1.20975	0.00808056028660477	0.0229999999999999
111	1.19008333333333	0.00559964825735155	0.0129999999999999
112	1.16633333333333	0.0109489172012025	0.0309999999999999
113	1.19708333333333	0.00403300775044528	0.0130000000000001
114	1.19091666666667	0.00494438769687104	0.0150000000000001
115	1.18675	0.00587947121926639	0.016
116	1.1885	0.0100317677224089	0.0290000000000001
117	1.17383333333333	0.00513160143944691	0.018
118	1.20291666666667	0.00427377485545876	0.012
119	1.187	0.00601513243260849	0.0190000000000001
120	1.16383333333333	0.0120667336345036	0.0389999999999999
121	1.11183333333333	0.0176935187585908	0.052

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.0277298296993677
beta	-0.0162618946789565
S.D.	0.00366936528473701
T-STAT	-4.43180043878406
p-value	2.09206988032592e-05

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0277298296993677 \tabularnewline
beta & -0.0162618946789565 \tabularnewline
S.D. & 0.00366936528473701 \tabularnewline
T-STAT & -4.43180043878406 \tabularnewline
p-value & 2.09206988032592e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0277298296993677[/C][/ROW]
[ROW][C]beta[/C][C]-0.0162618946789565[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00366936528473701[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.43180043878406[/C][/ROW]
[ROW][C]p-value[/C][C]2.09206988032592e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	0.0277298296993677
beta	-0.0162618946789565
S.D.	0.00366936528473701
T-STAT	-4.43180043878406
p-value	2.09206988032592e-05

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-4.31652047569392
beta	-3.6619345151735
S.D.	0.865133936641957
T-STAT	-4.23279490039126
p-value	4.56579540888697e-05
Lambda	4.6619345151735

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.31652047569392 \tabularnewline
beta & -3.6619345151735 \tabularnewline
S.D. & 0.865133936641957 \tabularnewline
T-STAT & -4.23279490039126 \tabularnewline
p-value & 4.56579540888697e-05 \tabularnewline
Lambda & 4.6619345151735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.31652047569392[/C][/ROW]
[ROW][C]beta[/C][C]-3.6619345151735[/C][/ROW]
[ROW][C]S.D.[/C][C]0.865133936641957[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.23279490039126[/C][/ROW]
[ROW][C]p-value[/C][C]4.56579540888697e-05[/C][/ROW]
[ROW][C]Lambda[/C][C]4.6619345151735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	-4.31652047569392
beta	-3.6619345151735
S.D.	0.865133936641957
T-STAT	-4.23279490039126
p-value	4.56579540888697e-05
Lambda	4.6619345151735

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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