## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 07 Jun 2010 06:35:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/07/t12758925712g6bjik3zx8klyi.htm/, Retrieved Fri, 24 Mar 2023 13:41:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77842, Retrieved Fri, 24 Mar 2023 13:41:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Datareeks - Maand...] [2010-02-10 10:03:07] [718fc9b3d403b712b51e1f070e50e17e]
- RMPD  [Quartiles] [] [2010-03-03 14:47:39] [8c48e27933b6e9b9039434b966f024a4]
- RM      [Variability] [] [2010-05-26 19:41:23] [8c48e27933b6e9b9039434b966f024a4]
- RMP       [Standard Deviation-Mean Plot] [] [2010-05-26 19:49:59] [8c48e27933b6e9b9039434b966f024a4]
-   P           [Standard Deviation-Mean Plot] [] [2010-06-07 06:35:41] [abee0efc8e8d52b36c60065f2f882b43] [Current]
Feedback Forum

Post a new message
Dataseries X:
93.2
96
95.2
77.1
70.9
64.8
70.1
77.3
79.5
100.6
100.7
107.1
95.9
82.8
83.3
80
80.4
67.5
75.7
71.1
89.3
101.1
105.2
114.1
96.3
84.4
91.2
81.9
80.5
70.4
74.8
75.9
86.3
98.7
100.9
113.8
89.8
84.4
87.2
85.6
72
69.2
77.5
78.1
94.3
97.7
100.2
116.4
97.1
93
96
80.5
76.1
69.9
73.6
92.6
94.2
93.5
108.5
109.4
105.1
92.5
97.1
81.4
79.1
72.1
78.7
87.1
91.4
109.9
116.3
113
100
84.8
94.3
87.1
90.3
72.4
84.9
92.7
92.2
114.9
112.5
118.3
106
91.2
96.6
96.3
88.2
70.2
86.5
88.2
102.8
119.1
119.2
125.1
106.1
102.1
105.2
101
84.3
87.5
92.7
94.4
113
113.9
122.9
132.7
106.9
96.6
127.3
98.2
100.2
89.4
95.3
104.2
106.4
116.2
135.9
134
104.6
107.1
123.5
98.8
98.6
90.6
89.1
105.2
114
122.1
138
142.2
116.4
112.6
123.8
103.6
113.9
98.6
95
116
113.9
127.5
131.4
145.9
131.5
131
130.5
118.9
114.3
85.7
104.6
105.1
117.3
142.5
140
159.8
131.2
125.4
126.5
119.4
113.5
98.7
114.5
113.8
133.1
143.4
137.3
165.2
126.9
124
135.7
130
109.4
117.8
120.3
121
132.3
142.9
147.4
175.9
132.6
123.7
153.3
134
119.6
116.2
118.6
130.7
129.3
144.4
163.2
179.4
128.1
138.4
152.7
120
140.5
116.2
121.4
127.8
143.6
157.6
166.2
182.3
153.1
147.6
157.7
137.2
151.5
98.7
145.8
151.7
129.4
174.1
197
193.9
164.1
142.8
157.9
159.2
162.2
123.1
130
150.1
169.4
179.7
182.1
194.3
161.4
169.4
168.8
158.1
158.5
135.3
149.3
143.4
142.2
188.4
166.2
199.2
182.7
145.2
182.1
158.7
141.6
132.6
139.6
147
166.6
157
180.4
210.2
159.8
157.8
168.2
158.4
152
142.2
137.2
152.6
166.8
165.6
198.6
201.5
170.7
164.4
179.7
157
168
139.3
138.6
153.4
138.9
172.1
198.4
217.8
173.7
153.8
175.6
147.1
160.3
135.2
148.8
151
148.2
182.2
189.2
183.1
170
158.4
176.1
156.2
153.2
117.9
149.8
156.6
166.7
156.8
158.6
210.8
203.6
175.2
168.7
155.9
147.3
137
141.1
167.4
160.2
191.9
174.4
208.2
159.4
161.1
172.1
158.4
114.6
159.6
159.7
159.4
160.7
165.5
205
205.2
141.6
148.1
184.9
132.5
137.3
135.5
121.7
166.1
146.8
162.8
186.8
185.5
151.5
158.1
143
151.2
147.6
130.7
137.5
146.1
133.6
167.9
181.9
202
166.5
151.3
146.2
148.3
144.7
123.6
151.6
133.9
137.4
181.6
182
190
161.2
155.5
141.9
164.6
136.2
126.8
152.5
126.6
150.1
186.3
147.5
200.4
177.2
127.4
177.1
154.4
135.2
126.4
147.3
140.6
152.3
151.2
172.2
215.3
154.1
159.3
160.4
151.9
148.4
139.6
148.2
153.5
145.1
183.7
210.5
203.3
153.3
144.3
169.6
143.7
160.1
135.6
141.8
159.9
145.7
183.5
198.2
186.8
172
150.6
163.3
153.7
152.9
135.5
148.5
148.4
133.6
194.1
208.6
197.3
164.4
148.1
152
144.1
155
124.5
153
146
138
190
192
192
147
133
163
150
129
131
145
137
138
168
176
188
139
143
150
154
137
129
128
140
143
151
177
184
151
134
164
126
131
125
127
143
143
160
190
182
138
136
152
127
151
130
119
153

 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 '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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77842&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77842&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77842&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 'Gwilym Jenkins' @ 72.249.127.135

 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 86.0416666666667 14.2647982704618 42.3 2 87.2 14.2481896776717 46.6 3 87.925 12.6682225918384 43.4 4 87.7 13.2404339396068 47.2 5 90.3666666666667 12.8115241683085 39.5 6 93.6416666666667 14.7508679765160 44.2 7 95.3666666666667 13.7624874425396 45.9 8 99.1166666666667 16.0945972489547 54.9 9 104.65 14.3130264889270 48.4 10 109.216666666667 15.634102197285 46.5 11 111.15 17.2648091898994 53.1 12 116.55 14.2659480136188 50.9 13 123.433333333333 19.9749540144349 74.1 14 126.833333333333 17.2231521417239 66.5 15 131.966666666667 17.4804999581785 66.5 16 137.083333333333 19.5000155400094 63.2 17 141.233333333333 20.3316740505294 66.1 18 153.141666666667 26.8258850005103 98.3 19 159.575 20.935707860886 71.2 20 161.683333333333 18.6796843137299 63.9 21 161.975 23.0431660151117 77.6 22 163.391666666667 19.4979932922402 64.3 23 166.525 24.1605661056494 79.2 24 162.35 17.6056034468368 54 25 160.925 21.1873085939330 92.9 26 169.241666666667 23.0613986145812 71.2 27 165.058333333333 23.3628476756399 90.6 28 154.133333333333 22.5904780155201 65.1 29 154.258333333333 20.8051330350484 71.3 30 154.758333333333 20.8625570791020 66.4 31 154.133333333333 22.1072729017289 73.8 32 156.383333333333 25.4963752622829 88.9 33 163.166666666667 23.2022464952048 70.9 34 160.208333333333 20.2474446573269 62.6 35 163.208333333333 24.6611751667689 75 36 158.258333333333 22.1639124513592 67.5 37 150.416666666667 19.1854979954478 59 38 147.916666666667 17.2229146162544 56 39 148 21.9875998111332 65

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 86.0416666666667 & 14.2647982704618 & 42.3 \tabularnewline
2 & 87.2 & 14.2481896776717 & 46.6 \tabularnewline
3 & 87.925 & 12.6682225918384 & 43.4 \tabularnewline
4 & 87.7 & 13.2404339396068 & 47.2 \tabularnewline
5 & 90.3666666666667 & 12.8115241683085 & 39.5 \tabularnewline
6 & 93.6416666666667 & 14.7508679765160 & 44.2 \tabularnewline
7 & 95.3666666666667 & 13.7624874425396 & 45.9 \tabularnewline
8 & 99.1166666666667 & 16.0945972489547 & 54.9 \tabularnewline
9 & 104.65 & 14.3130264889270 & 48.4 \tabularnewline
10 & 109.216666666667 & 15.634102197285 & 46.5 \tabularnewline
11 & 111.15 & 17.2648091898994 & 53.1 \tabularnewline
12 & 116.55 & 14.2659480136188 & 50.9 \tabularnewline
13 & 123.433333333333 & 19.9749540144349 & 74.1 \tabularnewline
14 & 126.833333333333 & 17.2231521417239 & 66.5 \tabularnewline
15 & 131.966666666667 & 17.4804999581785 & 66.5 \tabularnewline
16 & 137.083333333333 & 19.5000155400094 & 63.2 \tabularnewline
17 & 141.233333333333 & 20.3316740505294 & 66.1 \tabularnewline
18 & 153.141666666667 & 26.8258850005103 & 98.3 \tabularnewline
19 & 159.575 & 20.935707860886 & 71.2 \tabularnewline
20 & 161.683333333333 & 18.6796843137299 & 63.9 \tabularnewline
21 & 161.975 & 23.0431660151117 & 77.6 \tabularnewline
22 & 163.391666666667 & 19.4979932922402 & 64.3 \tabularnewline
23 & 166.525 & 24.1605661056494 & 79.2 \tabularnewline
24 & 162.35 & 17.6056034468368 & 54 \tabularnewline
25 & 160.925 & 21.1873085939330 & 92.9 \tabularnewline
26 & 169.241666666667 & 23.0613986145812 & 71.2 \tabularnewline
27 & 165.058333333333 & 23.3628476756399 & 90.6 \tabularnewline
28 & 154.133333333333 & 22.5904780155201 & 65.1 \tabularnewline
29 & 154.258333333333 & 20.8051330350484 & 71.3 \tabularnewline
30 & 154.758333333333 & 20.8625570791020 & 66.4 \tabularnewline
31 & 154.133333333333 & 22.1072729017289 & 73.8 \tabularnewline
32 & 156.383333333333 & 25.4963752622829 & 88.9 \tabularnewline
33 & 163.166666666667 & 23.2022464952048 & 70.9 \tabularnewline
34 & 160.208333333333 & 20.2474446573269 & 62.6 \tabularnewline
35 & 163.208333333333 & 24.6611751667689 & 75 \tabularnewline
36 & 158.258333333333 & 22.1639124513592 & 67.5 \tabularnewline
37 & 150.416666666667 & 19.1854979954478 & 59 \tabularnewline
38 & 147.916666666667 & 17.2229146162544 & 56 \tabularnewline
39 & 148 & 21.9875998111332 & 65 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77842&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]86.0416666666667[/C][C]14.2647982704618[/C][C]42.3[/C][/ROW]
[ROW][C]2[/C][C]87.2[/C][C]14.2481896776717[/C][C]46.6[/C][/ROW]
[ROW][C]3[/C][C]87.925[/C][C]12.6682225918384[/C][C]43.4[/C][/ROW]
[ROW][C]4[/C][C]87.7[/C][C]13.2404339396068[/C][C]47.2[/C][/ROW]
[ROW][C]5[/C][C]90.3666666666667[/C][C]12.8115241683085[/C][C]39.5[/C][/ROW]
[ROW][C]6[/C][C]93.6416666666667[/C][C]14.7508679765160[/C][C]44.2[/C][/ROW]
[ROW][C]7[/C][C]95.3666666666667[/C][C]13.7624874425396[/C][C]45.9[/C][/ROW]
[ROW][C]8[/C][C]99.1166666666667[/C][C]16.0945972489547[/C][C]54.9[/C][/ROW]
[ROW][C]9[/C][C]104.65[/C][C]14.3130264889270[/C][C]48.4[/C][/ROW]
[ROW][C]10[/C][C]109.216666666667[/C][C]15.634102197285[/C][C]46.5[/C][/ROW]
[ROW][C]11[/C][C]111.15[/C][C]17.2648091898994[/C][C]53.1[/C][/ROW]
[ROW][C]12[/C][C]116.55[/C][C]14.2659480136188[/C][C]50.9[/C][/ROW]
[ROW][C]13[/C][C]123.433333333333[/C][C]19.9749540144349[/C][C]74.1[/C][/ROW]
[ROW][C]14[/C][C]126.833333333333[/C][C]17.2231521417239[/C][C]66.5[/C][/ROW]
[ROW][C]15[/C][C]131.966666666667[/C][C]17.4804999581785[/C][C]66.5[/C][/ROW]
[ROW][C]16[/C][C]137.083333333333[/C][C]19.5000155400094[/C][C]63.2[/C][/ROW]
[ROW][C]17[/C][C]141.233333333333[/C][C]20.3316740505294[/C][C]66.1[/C][/ROW]
[ROW][C]18[/C][C]153.141666666667[/C][C]26.8258850005103[/C][C]98.3[/C][/ROW]
[ROW][C]19[/C][C]159.575[/C][C]20.935707860886[/C][C]71.2[/C][/ROW]
[ROW][C]20[/C][C]161.683333333333[/C][C]18.6796843137299[/C][C]63.9[/C][/ROW]
[ROW][C]21[/C][C]161.975[/C][C]23.0431660151117[/C][C]77.6[/C][/ROW]
[ROW][C]22[/C][C]163.391666666667[/C][C]19.4979932922402[/C][C]64.3[/C][/ROW]
[ROW][C]23[/C][C]166.525[/C][C]24.1605661056494[/C][C]79.2[/C][/ROW]
[ROW][C]24[/C][C]162.35[/C][C]17.6056034468368[/C][C]54[/C][/ROW]
[ROW][C]25[/C][C]160.925[/C][C]21.1873085939330[/C][C]92.9[/C][/ROW]
[ROW][C]26[/C][C]169.241666666667[/C][C]23.0613986145812[/C][C]71.2[/C][/ROW]
[ROW][C]27[/C][C]165.058333333333[/C][C]23.3628476756399[/C][C]90.6[/C][/ROW]
[ROW][C]28[/C][C]154.133333333333[/C][C]22.5904780155201[/C][C]65.1[/C][/ROW]
[ROW][C]29[/C][C]154.258333333333[/C][C]20.8051330350484[/C][C]71.3[/C][/ROW]
[ROW][C]30[/C][C]154.758333333333[/C][C]20.8625570791020[/C][C]66.4[/C][/ROW]
[ROW][C]31[/C][C]154.133333333333[/C][C]22.1072729017289[/C][C]73.8[/C][/ROW]
[ROW][C]32[/C][C]156.383333333333[/C][C]25.4963752622829[/C][C]88.9[/C][/ROW]
[ROW][C]33[/C][C]163.166666666667[/C][C]23.2022464952048[/C][C]70.9[/C][/ROW]
[ROW][C]34[/C][C]160.208333333333[/C][C]20.2474446573269[/C][C]62.6[/C][/ROW]
[ROW][C]35[/C][C]163.208333333333[/C][C]24.6611751667689[/C][C]75[/C][/ROW]
[ROW][C]36[/C][C]158.258333333333[/C][C]22.1639124513592[/C][C]67.5[/C][/ROW]
[ROW][C]37[/C][C]150.416666666667[/C][C]19.1854979954478[/C][C]59[/C][/ROW]
[ROW][C]38[/C][C]147.916666666667[/C][C]17.2229146162544[/C][C]56[/C][/ROW]
[ROW][C]39[/C][C]148[/C][C]21.9875998111332[/C][C]65[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77842&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77842&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 86.0416666666667 14.2647982704618 42.3 2 87.2 14.2481896776717 46.6 3 87.925 12.6682225918384 43.4 4 87.7 13.2404339396068 47.2 5 90.3666666666667 12.8115241683085 39.5 6 93.6416666666667 14.7508679765160 44.2 7 95.3666666666667 13.7624874425396 45.9 8 99.1166666666667 16.0945972489547 54.9 9 104.65 14.3130264889270 48.4 10 109.216666666667 15.634102197285 46.5 11 111.15 17.2648091898994 53.1 12 116.55 14.2659480136188 50.9 13 123.433333333333 19.9749540144349 74.1 14 126.833333333333 17.2231521417239 66.5 15 131.966666666667 17.4804999581785 66.5 16 137.083333333333 19.5000155400094 63.2 17 141.233333333333 20.3316740505294 66.1 18 153.141666666667 26.8258850005103 98.3 19 159.575 20.935707860886 71.2 20 161.683333333333 18.6796843137299 63.9 21 161.975 23.0431660151117 77.6 22 163.391666666667 19.4979932922402 64.3 23 166.525 24.1605661056494 79.2 24 162.35 17.6056034468368 54 25 160.925 21.1873085939330 92.9 26 169.241666666667 23.0613986145812 71.2 27 165.058333333333 23.3628476756399 90.6 28 154.133333333333 22.5904780155201 65.1 29 154.258333333333 20.8051330350484 71.3 30 154.758333333333 20.8625570791020 66.4 31 154.133333333333 22.1072729017289 73.8 32 156.383333333333 25.4963752622829 88.9 33 163.166666666667 23.2022464952048 70.9 34 160.208333333333 20.2474446573269 62.6 35 163.208333333333 24.6611751667689 75 36 158.258333333333 22.1639124513592 67.5 37 150.416666666667 19.1854979954478 59 38 147.916666666667 17.2229146162544 56 39 148 21.9875998111332 65

 Regression: S.E.(k) = alpha + beta * Mean(k) alpha 3.23178050020992 beta 0.116709521448479 S.D. 0.0112037350160626 T-STAT 10.4170190816862 p-value 1.48891692052211e-12

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.23178050020992 \tabularnewline
beta & 0.116709521448479 \tabularnewline
S.D. & 0.0112037350160626 \tabularnewline
T-STAT & 10.4170190816862 \tabularnewline
p-value & 1.48891692052211e-12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77842&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.23178050020992[/C][/ROW]
[ROW][C]beta[/C][C]0.116709521448479[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0112037350160626[/C][/ROW]
[ROW][C]T-STAT[/C][C]10.4170190816862[/C][/ROW]
[ROW][C]p-value[/C][C]1.48891692052211e-12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77842&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77842&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 3.23178050020992 beta 0.116709521448479 S.D. 0.0112037350160626 T-STAT 10.4170190816862 p-value 1.48891692052211e-12

 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha -1.01252660216091 beta 0.806351342795126 S.D. 0.0683168082567998 T-STAT 11.8031179056856 p-value 4.15512890219667e-14 Lambda 0.193648657204874

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.01252660216091 \tabularnewline
beta & 0.806351342795126 \tabularnewline
S.D. & 0.0683168082567998 \tabularnewline
T-STAT & 11.8031179056856 \tabularnewline
p-value & 4.15512890219667e-14 \tabularnewline
Lambda & 0.193648657204874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77842&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.01252660216091[/C][/ROW]
[ROW][C]beta[/C][C]0.806351342795126[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0683168082567998[/C][/ROW]
[ROW][C]T-STAT[/C][C]11.8031179056856[/C][/ROW]
[ROW][C]p-value[/C][C]4.15512890219667e-14[/C][/ROW]
[ROW][C]Lambda[/C][C]0.193648657204874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77842&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77842&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 -1.01252660216091 beta 0.806351342795126 S.D. 0.0683168082567998 T-STAT 11.8031179056856 p-value 4.15512890219667e-14 Lambda 0.193648657204874

par1 <- as.numeric(par1)(n <- length(x))(np <- floor(n / par1))arr <- array(NA,dim=c(par1,np))j <- 0k <- 1for (i in 1:(np*par1)){j = j + 1arr[j,k] <- x[i]if (j == par1) {j = 0k=k+1}}arrarr.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.meanarr.sdarr.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')