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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_boxcoxnorm.wasp
Title produced by softwareBox-Cox Normality Plot
Date of computationThu, 29 Oct 2020 16:03:40 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Oct/29/t1603984183towfjig680aqdfn.htm/, Retrieved Wed, 21 Apr 2021 07:34:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319280, Retrieved Wed, 21 Apr 2021 07:34:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact32
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Box-Cox Normality Plot] [] [2020-10-29 15:03:40] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0
0
0
2
2
2
2
3
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
7
7
7
7
7
8
8
8
8
8
8
8
9
9
9
9
9
9
9
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
0
0
0
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
7
7
7
7
7
7
7
7
7
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
9
9
9
9
9
9
9
9
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319280&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319280&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319280&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 Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Box-Cox Normality Plot
# observations x281
maximum correlation0.910761049065933
optimal lambda1.33
transformation formulafor all lambda <> 0 : T(Y) = (Y^lambda - 1) / lambda

\begin{tabular}{lllllllll}
\hline
Box-Cox Normality Plot \tabularnewline
# observations x & 281 \tabularnewline
maximum correlation & 0.910761049065933 \tabularnewline
optimal lambda & 1.33 \tabularnewline
transformation formula & for all lambda <> 0 : T(Y) = (Y^lambda - 1) / lambda \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319280&T=1

[TABLE]
[ROW][C]Box-Cox Normality Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]281[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.910761049065933[/C][/ROW]
[ROW][C]optimal lambda[/C][C]1.33[/C][/ROW]
[ROW][C]transformation formula[/C][C]for all lambda <> 0 : T(Y) = (Y^lambda - 1) / lambda[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319280&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319280&T=1

As an alternative you can also use a QR Code:  

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

Box-Cox Normality Plot
# observations x281
maximum correlation0.910761049065933
optimal lambda1.33
transformation formulafor all lambda <> 0 : T(Y) = (Y^lambda - 1) / lambda







Obs.OriginalTransformed
10.5-0.452805833174843
20.5-0.452805833174843
30.5-0.452805833174843
42.51.79148459816347
52.51.79148459816347
62.51.79148459816347
72.51.79148459816347
83.53.22698213006964
94.54.80615178223382
104.54.80615178223382
114.54.80615178223382
124.54.80615178223382
134.54.80615178223382
145.56.50635046757566
155.56.50635046757566
165.56.50635046757566
175.56.50635046757566
185.56.50635046757566
195.56.50635046757566
205.56.50635046757566
215.56.50635046757566
225.56.50635046757566
235.56.50635046757566
245.56.50635046757566
255.56.50635046757566
265.56.50635046757566
275.56.50635046757566
285.56.50635046757566
296.58.31218764035623
306.58.31218764035623
316.58.31218764035623
326.58.31218764035623
336.58.31218764035623
346.58.31218764035623
356.58.31218764035623
366.58.31218764035623
376.58.31218764035623
386.58.31218764035623
397.510.2123932709877
407.510.2123932709877
417.510.2123932709877
427.510.2123932709877
437.510.2123932709877
447.510.2123932709877
457.510.2123932709877
467.510.2123932709877
477.510.2123932709877
487.510.2123932709877
497.510.2123932709877
507.510.2123932709877
517.510.2123932709877
527.510.2123932709877
538.512.1982921104588
548.512.1982921104588
558.512.1982921104588
568.512.1982921104588
578.512.1982921104588
588.512.1982921104588
598.512.1982921104588
609.514.2629618704801
619.514.2629618704801
629.514.2629618704801
639.514.2629618704801
649.514.2629618704801
659.514.2629618704801
669.514.2629618704801
6710.516.4007268903347
6810.516.4007268903347
6910.516.4007268903347
7010.516.4007268903347
7110.516.4007268903347
7210.516.4007268903347
7310.516.4007268903347
7410.516.4007268903347
7510.516.4007268903347
7610.516.4007268903347
7710.516.4007268903347
7810.516.4007268903347
7910.516.4007268903347
8010.516.4007268903347
8110.516.4007268903347
8210.516.4007268903347
8310.516.4007268903347
8410.516.4007268903347
8510.516.4007268903347
8610.516.4007268903347
8710.516.4007268903347
8810.516.4007268903347
8910.516.4007268903347
9010.516.4007268903347
9110.516.4007268903347
9210.516.4007268903347
9310.516.4007268903347
9410.516.4007268903347
9510.516.4007268903347
9610.516.4007268903347
9710.516.4007268903347
9810.516.4007268903347
9910.516.4007268903347
10010.516.4007268903347
10110.516.4007268903347
10210.516.4007268903347
10310.516.4007268903347
10410.516.4007268903347
10510.516.4007268903347
10610.516.4007268903347
10710.516.4007268903347
10810.516.4007268903347
10910.516.4007268903347
11010.516.4007268903347
11110.516.4007268903347
11210.516.4007268903347
11310.516.4007268903347
11410.516.4007268903347
11510.516.4007268903347
11610.516.4007268903347
11710.516.4007268903347
11810.516.4007268903347
1190.5-0.452805833174843
1200.5-0.452805833174843
1210.5-0.452805833174843
1222.51.79148459816347
1232.51.79148459816347
1242.51.79148459816347
1252.51.79148459816347
1263.53.22698213006964
1273.53.22698213006964
1283.53.22698213006964
1293.53.22698213006964
1303.53.22698213006964
1313.53.22698213006964
1323.53.22698213006964
1334.54.80615178223382
1344.54.80615178223382
1354.54.80615178223382
1364.54.80615178223382
1374.54.80615178223382
1384.54.80615178223382
1394.54.80615178223382
1405.56.50635046757566
1415.56.50635046757566
1425.56.50635046757566
1435.56.50635046757566
1445.56.50635046757566
1455.56.50635046757566
1465.56.50635046757566
1475.56.50635046757566
1485.56.50635046757566
1495.56.50635046757566
1505.56.50635046757566
1515.56.50635046757566
1525.56.50635046757566
1535.56.50635046757566
1545.56.50635046757566
1555.56.50635046757566
1565.56.50635046757566
1575.56.50635046757566
1585.56.50635046757566
1596.58.31218764035623
1606.58.31218764035623
1616.58.31218764035623
1626.58.31218764035623
1636.58.31218764035623
1646.58.31218764035623
1656.58.31218764035623
1666.58.31218764035623
1676.58.31218764035623
1686.58.31218764035623
1696.58.31218764035623
1706.58.31218764035623
1716.58.31218764035623
1726.58.31218764035623
1736.58.31218764035623
1746.58.31218764035623
1757.510.2123932709877
1767.510.2123932709877
1777.510.2123932709877
1787.510.2123932709877
1797.510.2123932709877
1807.510.2123932709877
1817.510.2123932709877
1827.510.2123932709877
1837.510.2123932709877
1848.512.1982921104588
1858.512.1982921104588
1868.512.1982921104588
1878.512.1982921104588
1888.512.1982921104588
1898.512.1982921104588
1908.512.1982921104588
1918.512.1982921104588
1928.512.1982921104588
1938.512.1982921104588
1948.512.1982921104588
1958.512.1982921104588
1968.512.1982921104588
1978.512.1982921104588
1988.512.1982921104588
1999.514.2629618704801
2009.514.2629618704801
2019.514.2629618704801
2029.514.2629618704801
2039.514.2629618704801
2049.514.2629618704801
2059.514.2629618704801
2069.514.2629618704801
20710.516.4007268903347
20810.516.4007268903347
20910.516.4007268903347
21010.516.4007268903347
21110.516.4007268903347
21210.516.4007268903347
21310.516.4007268903347
21410.516.4007268903347
21510.516.4007268903347
21610.516.4007268903347
21710.516.4007268903347
21810.516.4007268903347
21910.516.4007268903347
22010.516.4007268903347
22110.516.4007268903347
22210.516.4007268903347
22310.516.4007268903347
22410.516.4007268903347
22510.516.4007268903347
22610.516.4007268903347
22710.516.4007268903347
22810.516.4007268903347
22910.516.4007268903347
23010.516.4007268903347
23110.516.4007268903347
23210.516.4007268903347
23310.516.4007268903347
23410.516.4007268903347
23510.516.4007268903347
23610.516.4007268903347
23710.516.4007268903347
23810.516.4007268903347
23910.516.4007268903347
24010.516.4007268903347
24110.516.4007268903347
24210.516.4007268903347
24310.516.4007268903347
24410.516.4007268903347
24510.516.4007268903347
24610.516.4007268903347
24710.516.4007268903347
24810.516.4007268903347
24910.516.4007268903347
25010.516.4007268903347
25110.516.4007268903347
25210.516.4007268903347
25310.516.4007268903347
25410.516.4007268903347
25510.516.4007268903347
25610.516.4007268903347
25710.516.4007268903347
25810.516.4007268903347
25910.516.4007268903347
26010.516.4007268903347
26110.516.4007268903347
26210.516.4007268903347
26310.516.4007268903347
26410.516.4007268903347
26510.516.4007268903347
26610.516.4007268903347
26710.516.4007268903347
26810.516.4007268903347
26910.516.4007268903347
27010.516.4007268903347
27110.516.4007268903347
27210.516.4007268903347
27310.516.4007268903347
27410.516.4007268903347
27510.516.4007268903347
27610.516.4007268903347
27710.516.4007268903347
27810.516.4007268903347
27910.516.4007268903347
28010.516.4007268903347
28110.516.4007268903347

\begin{tabular}{lllllllll}
\hline
Obs. & Original & Transformed \tabularnewline
1 & 0.5 & -0.452805833174843 \tabularnewline
2 & 0.5 & -0.452805833174843 \tabularnewline
3 & 0.5 & -0.452805833174843 \tabularnewline
4 & 2.5 & 1.79148459816347 \tabularnewline
5 & 2.5 & 1.79148459816347 \tabularnewline
6 & 2.5 & 1.79148459816347 \tabularnewline
7 & 2.5 & 1.79148459816347 \tabularnewline
8 & 3.5 & 3.22698213006964 \tabularnewline
9 & 4.5 & 4.80615178223382 \tabularnewline
10 & 4.5 & 4.80615178223382 \tabularnewline
11 & 4.5 & 4.80615178223382 \tabularnewline
12 & 4.5 & 4.80615178223382 \tabularnewline
13 & 4.5 & 4.80615178223382 \tabularnewline
14 & 5.5 & 6.50635046757566 \tabularnewline
15 & 5.5 & 6.50635046757566 \tabularnewline
16 & 5.5 & 6.50635046757566 \tabularnewline
17 & 5.5 & 6.50635046757566 \tabularnewline
18 & 5.5 & 6.50635046757566 \tabularnewline
19 & 5.5 & 6.50635046757566 \tabularnewline
20 & 5.5 & 6.50635046757566 \tabularnewline
21 & 5.5 & 6.50635046757566 \tabularnewline
22 & 5.5 & 6.50635046757566 \tabularnewline
23 & 5.5 & 6.50635046757566 \tabularnewline
24 & 5.5 & 6.50635046757566 \tabularnewline
25 & 5.5 & 6.50635046757566 \tabularnewline
26 & 5.5 & 6.50635046757566 \tabularnewline
27 & 5.5 & 6.50635046757566 \tabularnewline
28 & 5.5 & 6.50635046757566 \tabularnewline
29 & 6.5 & 8.31218764035623 \tabularnewline
30 & 6.5 & 8.31218764035623 \tabularnewline
31 & 6.5 & 8.31218764035623 \tabularnewline
32 & 6.5 & 8.31218764035623 \tabularnewline
33 & 6.5 & 8.31218764035623 \tabularnewline
34 & 6.5 & 8.31218764035623 \tabularnewline
35 & 6.5 & 8.31218764035623 \tabularnewline
36 & 6.5 & 8.31218764035623 \tabularnewline
37 & 6.5 & 8.31218764035623 \tabularnewline
38 & 6.5 & 8.31218764035623 \tabularnewline
39 & 7.5 & 10.2123932709877 \tabularnewline
40 & 7.5 & 10.2123932709877 \tabularnewline
41 & 7.5 & 10.2123932709877 \tabularnewline
42 & 7.5 & 10.2123932709877 \tabularnewline
43 & 7.5 & 10.2123932709877 \tabularnewline
44 & 7.5 & 10.2123932709877 \tabularnewline
45 & 7.5 & 10.2123932709877 \tabularnewline
46 & 7.5 & 10.2123932709877 \tabularnewline
47 & 7.5 & 10.2123932709877 \tabularnewline
48 & 7.5 & 10.2123932709877 \tabularnewline
49 & 7.5 & 10.2123932709877 \tabularnewline
50 & 7.5 & 10.2123932709877 \tabularnewline
51 & 7.5 & 10.2123932709877 \tabularnewline
52 & 7.5 & 10.2123932709877 \tabularnewline
53 & 8.5 & 12.1982921104588 \tabularnewline
54 & 8.5 & 12.1982921104588 \tabularnewline
55 & 8.5 & 12.1982921104588 \tabularnewline
56 & 8.5 & 12.1982921104588 \tabularnewline
57 & 8.5 & 12.1982921104588 \tabularnewline
58 & 8.5 & 12.1982921104588 \tabularnewline
59 & 8.5 & 12.1982921104588 \tabularnewline
60 & 9.5 & 14.2629618704801 \tabularnewline
61 & 9.5 & 14.2629618704801 \tabularnewline
62 & 9.5 & 14.2629618704801 \tabularnewline
63 & 9.5 & 14.2629618704801 \tabularnewline
64 & 9.5 & 14.2629618704801 \tabularnewline
65 & 9.5 & 14.2629618704801 \tabularnewline
66 & 9.5 & 14.2629618704801 \tabularnewline
67 & 10.5 & 16.4007268903347 \tabularnewline
68 & 10.5 & 16.4007268903347 \tabularnewline
69 & 10.5 & 16.4007268903347 \tabularnewline
70 & 10.5 & 16.4007268903347 \tabularnewline
71 & 10.5 & 16.4007268903347 \tabularnewline
72 & 10.5 & 16.4007268903347 \tabularnewline
73 & 10.5 & 16.4007268903347 \tabularnewline
74 & 10.5 & 16.4007268903347 \tabularnewline
75 & 10.5 & 16.4007268903347 \tabularnewline
76 & 10.5 & 16.4007268903347 \tabularnewline
77 & 10.5 & 16.4007268903347 \tabularnewline
78 & 10.5 & 16.4007268903347 \tabularnewline
79 & 10.5 & 16.4007268903347 \tabularnewline
80 & 10.5 & 16.4007268903347 \tabularnewline
81 & 10.5 & 16.4007268903347 \tabularnewline
82 & 10.5 & 16.4007268903347 \tabularnewline
83 & 10.5 & 16.4007268903347 \tabularnewline
84 & 10.5 & 16.4007268903347 \tabularnewline
85 & 10.5 & 16.4007268903347 \tabularnewline
86 & 10.5 & 16.4007268903347 \tabularnewline
87 & 10.5 & 16.4007268903347 \tabularnewline
88 & 10.5 & 16.4007268903347 \tabularnewline
89 & 10.5 & 16.4007268903347 \tabularnewline
90 & 10.5 & 16.4007268903347 \tabularnewline
91 & 10.5 & 16.4007268903347 \tabularnewline
92 & 10.5 & 16.4007268903347 \tabularnewline
93 & 10.5 & 16.4007268903347 \tabularnewline
94 & 10.5 & 16.4007268903347 \tabularnewline
95 & 10.5 & 16.4007268903347 \tabularnewline
96 & 10.5 & 16.4007268903347 \tabularnewline
97 & 10.5 & 16.4007268903347 \tabularnewline
98 & 10.5 & 16.4007268903347 \tabularnewline
99 & 10.5 & 16.4007268903347 \tabularnewline
100 & 10.5 & 16.4007268903347 \tabularnewline
101 & 10.5 & 16.4007268903347 \tabularnewline
102 & 10.5 & 16.4007268903347 \tabularnewline
103 & 10.5 & 16.4007268903347 \tabularnewline
104 & 10.5 & 16.4007268903347 \tabularnewline
105 & 10.5 & 16.4007268903347 \tabularnewline
106 & 10.5 & 16.4007268903347 \tabularnewline
107 & 10.5 & 16.4007268903347 \tabularnewline
108 & 10.5 & 16.4007268903347 \tabularnewline
109 & 10.5 & 16.4007268903347 \tabularnewline
110 & 10.5 & 16.4007268903347 \tabularnewline
111 & 10.5 & 16.4007268903347 \tabularnewline
112 & 10.5 & 16.4007268903347 \tabularnewline
113 & 10.5 & 16.4007268903347 \tabularnewline
114 & 10.5 & 16.4007268903347 \tabularnewline
115 & 10.5 & 16.4007268903347 \tabularnewline
116 & 10.5 & 16.4007268903347 \tabularnewline
117 & 10.5 & 16.4007268903347 \tabularnewline
118 & 10.5 & 16.4007268903347 \tabularnewline
119 & 0.5 & -0.452805833174843 \tabularnewline
120 & 0.5 & -0.452805833174843 \tabularnewline
121 & 0.5 & -0.452805833174843 \tabularnewline
122 & 2.5 & 1.79148459816347 \tabularnewline
123 & 2.5 & 1.79148459816347 \tabularnewline
124 & 2.5 & 1.79148459816347 \tabularnewline
125 & 2.5 & 1.79148459816347 \tabularnewline
126 & 3.5 & 3.22698213006964 \tabularnewline
127 & 3.5 & 3.22698213006964 \tabularnewline
128 & 3.5 & 3.22698213006964 \tabularnewline
129 & 3.5 & 3.22698213006964 \tabularnewline
130 & 3.5 & 3.22698213006964 \tabularnewline
131 & 3.5 & 3.22698213006964 \tabularnewline
132 & 3.5 & 3.22698213006964 \tabularnewline
133 & 4.5 & 4.80615178223382 \tabularnewline
134 & 4.5 & 4.80615178223382 \tabularnewline
135 & 4.5 & 4.80615178223382 \tabularnewline
136 & 4.5 & 4.80615178223382 \tabularnewline
137 & 4.5 & 4.80615178223382 \tabularnewline
138 & 4.5 & 4.80615178223382 \tabularnewline
139 & 4.5 & 4.80615178223382 \tabularnewline
140 & 5.5 & 6.50635046757566 \tabularnewline
141 & 5.5 & 6.50635046757566 \tabularnewline
142 & 5.5 & 6.50635046757566 \tabularnewline
143 & 5.5 & 6.50635046757566 \tabularnewline
144 & 5.5 & 6.50635046757566 \tabularnewline
145 & 5.5 & 6.50635046757566 \tabularnewline
146 & 5.5 & 6.50635046757566 \tabularnewline
147 & 5.5 & 6.50635046757566 \tabularnewline
148 & 5.5 & 6.50635046757566 \tabularnewline
149 & 5.5 & 6.50635046757566 \tabularnewline
150 & 5.5 & 6.50635046757566 \tabularnewline
151 & 5.5 & 6.50635046757566 \tabularnewline
152 & 5.5 & 6.50635046757566 \tabularnewline
153 & 5.5 & 6.50635046757566 \tabularnewline
154 & 5.5 & 6.50635046757566 \tabularnewline
155 & 5.5 & 6.50635046757566 \tabularnewline
156 & 5.5 & 6.50635046757566 \tabularnewline
157 & 5.5 & 6.50635046757566 \tabularnewline
158 & 5.5 & 6.50635046757566 \tabularnewline
159 & 6.5 & 8.31218764035623 \tabularnewline
160 & 6.5 & 8.31218764035623 \tabularnewline
161 & 6.5 & 8.31218764035623 \tabularnewline
162 & 6.5 & 8.31218764035623 \tabularnewline
163 & 6.5 & 8.31218764035623 \tabularnewline
164 & 6.5 & 8.31218764035623 \tabularnewline
165 & 6.5 & 8.31218764035623 \tabularnewline
166 & 6.5 & 8.31218764035623 \tabularnewline
167 & 6.5 & 8.31218764035623 \tabularnewline
168 & 6.5 & 8.31218764035623 \tabularnewline
169 & 6.5 & 8.31218764035623 \tabularnewline
170 & 6.5 & 8.31218764035623 \tabularnewline
171 & 6.5 & 8.31218764035623 \tabularnewline
172 & 6.5 & 8.31218764035623 \tabularnewline
173 & 6.5 & 8.31218764035623 \tabularnewline
174 & 6.5 & 8.31218764035623 \tabularnewline
175 & 7.5 & 10.2123932709877 \tabularnewline
176 & 7.5 & 10.2123932709877 \tabularnewline
177 & 7.5 & 10.2123932709877 \tabularnewline
178 & 7.5 & 10.2123932709877 \tabularnewline
179 & 7.5 & 10.2123932709877 \tabularnewline
180 & 7.5 & 10.2123932709877 \tabularnewline
181 & 7.5 & 10.2123932709877 \tabularnewline
182 & 7.5 & 10.2123932709877 \tabularnewline
183 & 7.5 & 10.2123932709877 \tabularnewline
184 & 8.5 & 12.1982921104588 \tabularnewline
185 & 8.5 & 12.1982921104588 \tabularnewline
186 & 8.5 & 12.1982921104588 \tabularnewline
187 & 8.5 & 12.1982921104588 \tabularnewline
188 & 8.5 & 12.1982921104588 \tabularnewline
189 & 8.5 & 12.1982921104588 \tabularnewline
190 & 8.5 & 12.1982921104588 \tabularnewline
191 & 8.5 & 12.1982921104588 \tabularnewline
192 & 8.5 & 12.1982921104588 \tabularnewline
193 & 8.5 & 12.1982921104588 \tabularnewline
194 & 8.5 & 12.1982921104588 \tabularnewline
195 & 8.5 & 12.1982921104588 \tabularnewline
196 & 8.5 & 12.1982921104588 \tabularnewline
197 & 8.5 & 12.1982921104588 \tabularnewline
198 & 8.5 & 12.1982921104588 \tabularnewline
199 & 9.5 & 14.2629618704801 \tabularnewline
200 & 9.5 & 14.2629618704801 \tabularnewline
201 & 9.5 & 14.2629618704801 \tabularnewline
202 & 9.5 & 14.2629618704801 \tabularnewline
203 & 9.5 & 14.2629618704801 \tabularnewline
204 & 9.5 & 14.2629618704801 \tabularnewline
205 & 9.5 & 14.2629618704801 \tabularnewline
206 & 9.5 & 14.2629618704801 \tabularnewline
207 & 10.5 & 16.4007268903347 \tabularnewline
208 & 10.5 & 16.4007268903347 \tabularnewline
209 & 10.5 & 16.4007268903347 \tabularnewline
210 & 10.5 & 16.4007268903347 \tabularnewline
211 & 10.5 & 16.4007268903347 \tabularnewline
212 & 10.5 & 16.4007268903347 \tabularnewline
213 & 10.5 & 16.4007268903347 \tabularnewline
214 & 10.5 & 16.4007268903347 \tabularnewline
215 & 10.5 & 16.4007268903347 \tabularnewline
216 & 10.5 & 16.4007268903347 \tabularnewline
217 & 10.5 & 16.4007268903347 \tabularnewline
218 & 10.5 & 16.4007268903347 \tabularnewline
219 & 10.5 & 16.4007268903347 \tabularnewline
220 & 10.5 & 16.4007268903347 \tabularnewline
221 & 10.5 & 16.4007268903347 \tabularnewline
222 & 10.5 & 16.4007268903347 \tabularnewline
223 & 10.5 & 16.4007268903347 \tabularnewline
224 & 10.5 & 16.4007268903347 \tabularnewline
225 & 10.5 & 16.4007268903347 \tabularnewline
226 & 10.5 & 16.4007268903347 \tabularnewline
227 & 10.5 & 16.4007268903347 \tabularnewline
228 & 10.5 & 16.4007268903347 \tabularnewline
229 & 10.5 & 16.4007268903347 \tabularnewline
230 & 10.5 & 16.4007268903347 \tabularnewline
231 & 10.5 & 16.4007268903347 \tabularnewline
232 & 10.5 & 16.4007268903347 \tabularnewline
233 & 10.5 & 16.4007268903347 \tabularnewline
234 & 10.5 & 16.4007268903347 \tabularnewline
235 & 10.5 & 16.4007268903347 \tabularnewline
236 & 10.5 & 16.4007268903347 \tabularnewline
237 & 10.5 & 16.4007268903347 \tabularnewline
238 & 10.5 & 16.4007268903347 \tabularnewline
239 & 10.5 & 16.4007268903347 \tabularnewline
240 & 10.5 & 16.4007268903347 \tabularnewline
241 & 10.5 & 16.4007268903347 \tabularnewline
242 & 10.5 & 16.4007268903347 \tabularnewline
243 & 10.5 & 16.4007268903347 \tabularnewline
244 & 10.5 & 16.4007268903347 \tabularnewline
245 & 10.5 & 16.4007268903347 \tabularnewline
246 & 10.5 & 16.4007268903347 \tabularnewline
247 & 10.5 & 16.4007268903347 \tabularnewline
248 & 10.5 & 16.4007268903347 \tabularnewline
249 & 10.5 & 16.4007268903347 \tabularnewline
250 & 10.5 & 16.4007268903347 \tabularnewline
251 & 10.5 & 16.4007268903347 \tabularnewline
252 & 10.5 & 16.4007268903347 \tabularnewline
253 & 10.5 & 16.4007268903347 \tabularnewline
254 & 10.5 & 16.4007268903347 \tabularnewline
255 & 10.5 & 16.4007268903347 \tabularnewline
256 & 10.5 & 16.4007268903347 \tabularnewline
257 & 10.5 & 16.4007268903347 \tabularnewline
258 & 10.5 & 16.4007268903347 \tabularnewline
259 & 10.5 & 16.4007268903347 \tabularnewline
260 & 10.5 & 16.4007268903347 \tabularnewline
261 & 10.5 & 16.4007268903347 \tabularnewline
262 & 10.5 & 16.4007268903347 \tabularnewline
263 & 10.5 & 16.4007268903347 \tabularnewline
264 & 10.5 & 16.4007268903347 \tabularnewline
265 & 10.5 & 16.4007268903347 \tabularnewline
266 & 10.5 & 16.4007268903347 \tabularnewline
267 & 10.5 & 16.4007268903347 \tabularnewline
268 & 10.5 & 16.4007268903347 \tabularnewline
269 & 10.5 & 16.4007268903347 \tabularnewline
270 & 10.5 & 16.4007268903347 \tabularnewline
271 & 10.5 & 16.4007268903347 \tabularnewline
272 & 10.5 & 16.4007268903347 \tabularnewline
273 & 10.5 & 16.4007268903347 \tabularnewline
274 & 10.5 & 16.4007268903347 \tabularnewline
275 & 10.5 & 16.4007268903347 \tabularnewline
276 & 10.5 & 16.4007268903347 \tabularnewline
277 & 10.5 & 16.4007268903347 \tabularnewline
278 & 10.5 & 16.4007268903347 \tabularnewline
279 & 10.5 & 16.4007268903347 \tabularnewline
280 & 10.5 & 16.4007268903347 \tabularnewline
281 & 10.5 & 16.4007268903347 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319280&T=2

[TABLE]
[ROW][C]Obs.[/C][C]Original[/C][C]Transformed[/C][/ROW]
[ROW][C]1[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]2[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]3[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]4[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]5[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]6[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]7[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]8[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]11[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]12[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]13[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]14[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]15[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]16[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]19[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]20[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]21[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]22[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]23[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]24[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]27[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]28[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]29[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]30[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]31[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]32[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]33[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]34[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]35[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]36[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]37[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]38[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]39[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]40[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]41[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]42[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]43[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]44[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]45[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]46[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]47[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]48[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]50[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]52[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]53[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]54[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]55[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]56[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]57[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]59[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]60[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]61[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]62[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]63[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]64[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]65[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]66[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]67[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]68[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]69[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]70[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]71[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]72[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]73[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]74[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]75[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]76[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]77[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]78[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]79[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]80[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]83[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]84[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]86[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]87[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]88[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]89[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]90[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]91[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]92[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]93[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]94[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]95[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]96[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]97[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]98[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]99[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]100[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]101[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]102[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]103[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]104[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]105[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]106[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]107[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]108[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]109[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]110[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]111[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]112[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]113[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]114[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]115[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]116[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]117[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]118[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]119[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]120[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]121[/C][C]0.5[/C][C]-0.452805833174843[/C][/ROW]
[ROW][C]122[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]123[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]124[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]125[/C][C]2.5[/C][C]1.79148459816347[/C][/ROW]
[ROW][C]126[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]127[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]128[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]129[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]130[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]131[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]132[/C][C]3.5[/C][C]3.22698213006964[/C][/ROW]
[ROW][C]133[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]134[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]135[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]136[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]137[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]138[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]139[/C][C]4.5[/C][C]4.80615178223382[/C][/ROW]
[ROW][C]140[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]141[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]142[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]143[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]144[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]145[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]146[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]151[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]153[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]154[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]156[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]157[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]158[/C][C]5.5[/C][C]6.50635046757566[/C][/ROW]
[ROW][C]159[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]160[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]161[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]162[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]163[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]164[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]165[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]168[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]169[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]170[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]171[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]173[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]174[/C][C]6.5[/C][C]8.31218764035623[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]177[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]178[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]179[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]182[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]183[/C][C]7.5[/C][C]10.2123932709877[/C][/ROW]
[ROW][C]184[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]185[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]186[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]187[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]188[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]189[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]190[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]191[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]194[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]195[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]12.1982921104588[/C][/ROW]
[ROW][C]199[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]201[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]202[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]203[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]204[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]205[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]206[/C][C]9.5[/C][C]14.2629618704801[/C][/ROW]
[ROW][C]207[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]208[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]209[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]210[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]211[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]212[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]213[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]214[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]215[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]216[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]217[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]218[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]219[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]220[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]221[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]222[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]223[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]224[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]227[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]228[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]229[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]230[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]231[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]232[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]234[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]235[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]236[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]237[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]238[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]239[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]240[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]241[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]242[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]243[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]246[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]247[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]248[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]249[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]250[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]251[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]253[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]254[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]255[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]256[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]257[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]258[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]259[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]260[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]261[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]262[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]263[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]264[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]265[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]266[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]267[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]268[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]269[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]270[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]271[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]272[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]273[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]274[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]275[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]276[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]277[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]278[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]279[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]280[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[ROW][C]281[/C][C]10.5[/C][C]16.4007268903347[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319280&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319280&T=2

As an alternative you can also use a QR Code:  

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

Obs.OriginalTransformed
10.5-0.452805833174843
20.5-0.452805833174843
30.5-0.452805833174843
42.51.79148459816347
52.51.79148459816347
62.51.79148459816347
72.51.79148459816347
83.53.22698213006964
94.54.80615178223382
104.54.80615178223382
114.54.80615178223382
124.54.80615178223382
134.54.80615178223382
145.56.50635046757566
155.56.50635046757566
165.56.50635046757566
175.56.50635046757566
185.56.50635046757566
195.56.50635046757566
205.56.50635046757566
215.56.50635046757566
225.56.50635046757566
235.56.50635046757566
245.56.50635046757566
255.56.50635046757566
265.56.50635046757566
275.56.50635046757566
285.56.50635046757566
296.58.31218764035623
306.58.31218764035623
316.58.31218764035623
326.58.31218764035623
336.58.31218764035623
346.58.31218764035623
356.58.31218764035623
366.58.31218764035623
376.58.31218764035623
386.58.31218764035623
397.510.2123932709877
407.510.2123932709877
417.510.2123932709877
427.510.2123932709877
437.510.2123932709877
447.510.2123932709877
457.510.2123932709877
467.510.2123932709877
477.510.2123932709877
487.510.2123932709877
497.510.2123932709877
507.510.2123932709877
517.510.2123932709877
527.510.2123932709877
538.512.1982921104588
548.512.1982921104588
558.512.1982921104588
568.512.1982921104588
578.512.1982921104588
588.512.1982921104588
598.512.1982921104588
609.514.2629618704801
619.514.2629618704801
629.514.2629618704801
639.514.2629618704801
649.514.2629618704801
659.514.2629618704801
669.514.2629618704801
6710.516.4007268903347
6810.516.4007268903347
6910.516.4007268903347
7010.516.4007268903347
7110.516.4007268903347
7210.516.4007268903347
7310.516.4007268903347
7410.516.4007268903347
7510.516.4007268903347
7610.516.4007268903347
7710.516.4007268903347
7810.516.4007268903347
7910.516.4007268903347
8010.516.4007268903347
8110.516.4007268903347
8210.516.4007268903347
8310.516.4007268903347
8410.516.4007268903347
8510.516.4007268903347
8610.516.4007268903347
8710.516.4007268903347
8810.516.4007268903347
8910.516.4007268903347
9010.516.4007268903347
9110.516.4007268903347
9210.516.4007268903347
9310.516.4007268903347
9410.516.4007268903347
9510.516.4007268903347
9610.516.4007268903347
9710.516.4007268903347
9810.516.4007268903347
9910.516.4007268903347
10010.516.4007268903347
10110.516.4007268903347
10210.516.4007268903347
10310.516.4007268903347
10410.516.4007268903347
10510.516.4007268903347
10610.516.4007268903347
10710.516.4007268903347
10810.516.4007268903347
10910.516.4007268903347
11010.516.4007268903347
11110.516.4007268903347
11210.516.4007268903347
11310.516.4007268903347
11410.516.4007268903347
11510.516.4007268903347
11610.516.4007268903347
11710.516.4007268903347
11810.516.4007268903347
1190.5-0.452805833174843
1200.5-0.452805833174843
1210.5-0.452805833174843
1222.51.79148459816347
1232.51.79148459816347
1242.51.79148459816347
1252.51.79148459816347
1263.53.22698213006964
1273.53.22698213006964
1283.53.22698213006964
1293.53.22698213006964
1303.53.22698213006964
1313.53.22698213006964
1323.53.22698213006964
1334.54.80615178223382
1344.54.80615178223382
1354.54.80615178223382
1364.54.80615178223382
1374.54.80615178223382
1384.54.80615178223382
1394.54.80615178223382
1405.56.50635046757566
1415.56.50635046757566
1425.56.50635046757566
1435.56.50635046757566
1445.56.50635046757566
1455.56.50635046757566
1465.56.50635046757566
1475.56.50635046757566
1485.56.50635046757566
1495.56.50635046757566
1505.56.50635046757566
1515.56.50635046757566
1525.56.50635046757566
1535.56.50635046757566
1545.56.50635046757566
1555.56.50635046757566
1565.56.50635046757566
1575.56.50635046757566
1585.56.50635046757566
1596.58.31218764035623
1606.58.31218764035623
1616.58.31218764035623
1626.58.31218764035623
1636.58.31218764035623
1646.58.31218764035623
1656.58.31218764035623
1666.58.31218764035623
1676.58.31218764035623
1686.58.31218764035623
1696.58.31218764035623
1706.58.31218764035623
1716.58.31218764035623
1726.58.31218764035623
1736.58.31218764035623
1746.58.31218764035623
1757.510.2123932709877
1767.510.2123932709877
1777.510.2123932709877
1787.510.2123932709877
1797.510.2123932709877
1807.510.2123932709877
1817.510.2123932709877
1827.510.2123932709877
1837.510.2123932709877
1848.512.1982921104588
1858.512.1982921104588
1868.512.1982921104588
1878.512.1982921104588
1888.512.1982921104588
1898.512.1982921104588
1908.512.1982921104588
1918.512.1982921104588
1928.512.1982921104588
1938.512.1982921104588
1948.512.1982921104588
1958.512.1982921104588
1968.512.1982921104588
1978.512.1982921104588
1988.512.1982921104588
1999.514.2629618704801
2009.514.2629618704801
2019.514.2629618704801
2029.514.2629618704801
2039.514.2629618704801
2049.514.2629618704801
2059.514.2629618704801
2069.514.2629618704801
20710.516.4007268903347
20810.516.4007268903347
20910.516.4007268903347
21010.516.4007268903347
21110.516.4007268903347
21210.516.4007268903347
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Maximum Likelihood Estimation of Lambda
> summary(mypT)
bcPower Transformation to Normality 
  Est Power Rounded Pwr Wald Lwr Bnd Wald Upr Bnd
x    1.7401           2       1.4142        2.066
Likelihood ratio test that transformation parameter is equal to 0
 (log transformation)
                          LRT df       pval
LR test, lambda = (0) 253.175  1 < 2.22e-16
Likelihood ratio test that no transformation is needed
                           LRT df       pval
LR test, lambda = (1) 26.16003  1 3.1426e-07

\begin{tabular}{lllllllll}
\hline
Maximum Likelihood Estimation of Lambda \tabularnewline
> summary(mypT)
bcPower Transformation to Normality 
  Est Power Rounded Pwr Wald Lwr Bnd Wald Upr Bnd
x    1.7401           2       1.4142        2.066
Likelihood ratio test that transformation parameter is equal to 0
 (log transformation)
                          LRT df       pval
LR test, lambda = (0) 253.175  1 < 2.22e-16
Likelihood ratio test that no transformation is needed
                           LRT df       pval
LR test, lambda = (1) 26.16003  1 3.1426e-07
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=319280&T=3

[TABLE]
[ROW][C]Maximum Likelihood Estimation of Lambda[/C][/ROW]
[ROW][C]
> summary(mypT)
bcPower Transformation to Normality 
  Est Power Rounded Pwr Wald Lwr Bnd Wald Upr Bnd
x    1.7401           2       1.4142        2.066
Likelihood ratio test that transformation parameter is equal to 0
 (log transformation)
                          LRT df       pval
LR test, lambda = (0) 253.175  1 < 2.22e-16
Likelihood ratio test that no transformation is needed
                           LRT df       pval
LR test, lambda = (1) 26.16003  1 3.1426e-07
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319280&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319280&T=3

As an alternative you can also use a QR Code:  

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

Maximum Likelihood Estimation of Lambda
> summary(mypT)
bcPower Transformation to Normality 
  Est Power Rounded Pwr Wald Lwr Bnd Wald Upr Bnd
x    1.7401           2       1.4142        2.066
Likelihood ratio test that transformation parameter is equal to 0
 (log transformation)
                          LRT df       pval
LR test, lambda = (0) 253.175  1 < 2.22e-16
Likelihood ratio test that no transformation is needed
                           LRT df       pval
LR test, lambda = (1) 26.16003  1 3.1426e-07



Parameters (Session):
par1 = Full Box-Cox transform ; par2 = -5 ; par3 = 5 ; par4 = 0.5 ; par5 = Yes ;
Parameters (R input):
par1 = Full Box-Cox transform ; par2 = -5 ; par3 = 5 ; par4 = 0.5 ; par5 = Yes ;
R code (references can be found in the software module):
library(car)
par2 <- abs(as.numeric(par2)*100)
par3 <- as.numeric(par3)*100
if(par4=='') par4 <- 0
par4 <- as.numeric(par4)
numlam <- par2 + par3 + 1
x <- x + par4
n <- length(x)
c <- array(NA,dim=c(numlam))
l <- array(NA,dim=c(numlam))
mx <- -1
mxli <- -999
for (i in 1:numlam)
{
l[i] <- (i-par2-1)/100
if (l[i] != 0)
{
if (par1 == 'Full Box-Cox transform') x1 <- (x^l[i] - 1) / l[i]
if (par1 == 'Simple Box-Cox transform') x1 <- x^l[i]
} else {
x1 <- log(x)
}
c[i] <- cor(qnorm(ppoints(x), mean=0, sd=1),sort(x1))
if (mx < c[i])
{
mx <- c[i]
mxli <- l[i]
x1.best <- x1
}
}
print(c)
print(mx)
print(mxli)
print(x1.best)
if (mxli != 0)
{
if (par1 == 'Full Box-Cox transform') x1 <- (x^mxli - 1) / mxli
if (par1 == 'Simple Box-Cox transform') x1 <- x^mxli
} else {
x1 <- log(x)
}
mypT <- powerTransform(x)
summary(mypT)
bitmap(file='test1.png')
plot(l,c,main='Box-Cox Normality Plot', xlab='Lambda',ylab='correlation')
mtext(paste('Optimal Lambda =',mxli))
grid()
dev.off()
bitmap(file='test2.png')
hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test3.png')
hist(x1,main='Histogram of Transformed Data', xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test4.png')
qqPlot(x)
grid()
mtext('Original Data')
dev.off()
bitmap(file='test5.png')
qqPlot(x1)
grid()
mtext('Transformed Data')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Box-Cox Normality Plot',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations x',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum correlation',header=TRUE)
a<-table.element(a,mx)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'optimal lambda',header=TRUE)
a<-table.element(a,mxli)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'transformation formula',header=TRUE)
if (par1 == 'Full Box-Cox transform') {
a<-table.element(a,'for all lambda <> 0 : T(Y) = (Y^lambda - 1) / lambda')
} else {
a<-table.element(a,'for all lambda <> 0 : T(Y) = Y^lambda')
}
a<-table.row.end(a)
if(mx<0) {
a<-table.row.start(a)
a<-table.element(a,'Warning: maximum correlation is negative! The Box-Cox transformation must not be used.',2)
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if(par5=='Yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Obs.',header=T)
a<-table.element(a,'Original',header=T)
a<-table.element(a,'Transformed',header=T)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,x[i])
a<-table.element(a,x1.best[i])
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,'Maximum Likelihood Estimation of Lambda',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste('
',RC.texteval('summary(mypT)'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')