Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 16 Aug 2010 11:23:24 +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/Aug/16/t128195778722sseh2borfuho1.htm/, Retrieved Thu, 16 May 2024 13:28:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78961, Retrieved Thu, 16 May 2024 13:28:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSebastien Delforge
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Centrummaten aant...] [2010-08-16 11:23:24] [923770d86edf74ed976a539eae527e37] [Current]
Feedback Forum

Post a new message
Dataseries X:
152
151
150
148
146
145
146
148
149
149
150
152
154
164
167
162
164
172
169
174
181
181
172
181
183
200
199
190
197
194
190
195
204
197
185
193
192
211
210
197
191
182
170
166
175
163
153
171
165
184
179
163
163
148
132
127
130
118
113
137
133
155
151
132
134
118
102
98
91
77
74
102
98
113
114
96
102
90
72
67
62
48
43
75




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78961&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78961&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78961&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean148.1071428571434.4399808841501533.3576082243633
Geometric Mean141.057180038355
Harmonic Mean131.917557089629
Quadratic Mean153.53156182424
Winsorized Mean ( 1 / 28 )148.1547619047624.4213498498128833.5089434080934
Winsorized Mean ( 2 / 28 )148.3452380952384.3124356214313534.399409317095
Winsorized Mean ( 3 / 28 )148.3809523809524.2487183704866934.9236968521299
Winsorized Mean ( 4 / 28 )148.5714285714294.1880730343837935.4748896095334
Winsorized Mean ( 5 / 28 )148.5714285714294.1450426506281735.8431603952044
Winsorized Mean ( 6 / 28 )148.6428571428574.129628016555335.9942485247973
Winsorized Mean ( 7 / 28 )148.8095238095244.0941121749406436.3472023850156
Winsorized Mean ( 8 / 28 )149.8571428571433.8188372241360639.2415633507514
Winsorized Mean ( 9 / 28 )149.8571428571433.7835188862607239.607874933921
Winsorized Mean ( 10 / 28 )150.3333333333333.6576977879082341.1005342842461
Winsorized Mean ( 11 / 28 )150.4642857142863.5928966075149541.8782676349697
Winsorized Mean ( 12 / 28 )150.3214285714293.5731500440932342.0697218746592
Winsorized Mean ( 13 / 28 )150.7857142857143.4444643837007143.7762442832145
Winsorized Mean ( 14 / 28 )150.7857142857143.4444643837007143.7762442832145
Winsorized Mean ( 15 / 28 )149.8928571428573.3263848054770645.0617910760207
Winsorized Mean ( 16 / 28 )151.7976190476192.9532977843735251.3993610298325
Winsorized Mean ( 17 / 28 )151.5952380952382.9269220922177851.7933970631831
Winsorized Mean ( 18 / 28 )151.5952380952382.8654128257491352.9051998137844
Winsorized Mean ( 19 / 28 )152.273809523812.6955558924404256.4906889710042
Winsorized Mean ( 20 / 28 )152.273809523812.6955558924404256.4906889710042
Winsorized Mean ( 21 / 28 )154.523809523812.3644840681089165.3520197526204
Winsorized Mean ( 22 / 28 )154.7857142857142.1853362705074770.8292432494935
Winsorized Mean ( 23 / 28 )154.2380952380951.9677272134572878.3838807448826
Winsorized Mean ( 24 / 28 )153.9523809523811.9317013480554979.697817215562
Winsorized Mean ( 25 / 28 )153.6547619047621.8175132942461984.5412038476946
Winsorized Mean ( 26 / 28 )153.9642857142861.7753529000856886.7232006137232
Winsorized Mean ( 27 / 28 )154.6071428571431.6068750972204996.2160301846584
Winsorized Mean ( 28 / 28 )156.9404761904761.23062741304618127.528831656692
Trimmed Mean ( 1 / 28 )148.6219512195124.2931091275789334.6187219571859
Trimmed Mean ( 2 / 28 )149.11254.1435092504093535.987007869059
Trimmed Mean ( 3 / 28 )149.5256410256414.0371948814097337.0370134258737
Trimmed Mean ( 4 / 28 )149.9473684210533.9407851536162438.0501251846867
Trimmed Mean ( 5 / 28 )150.3378378378383.8489278344298739.0596665629889
Trimmed Mean ( 6 / 28 )150.753.7531807063756640.1659317239683
Trimmed Mean ( 7 / 28 )151.1714285714293.6435354380081641.490313774489
Trimmed Mean ( 8 / 28 )151.5882352941183.5217395393247943.0435679871945
Trimmed Mean ( 9 / 28 )151.8636363636363.4419519563411344.1213701672555
Trimmed Mean ( 10 / 28 )152.156253.3533046622306945.3750151943493
Trimmed Mean ( 11 / 28 )152.4032258064523.2729246537649346.5648439633764
Trimmed Mean ( 12 / 28 )152.653.1881511742081147.8804145910415
Trimmed Mean ( 13 / 28 )152.9310344827593.087733284373849.5285765958808
Trimmed Mean ( 14 / 28 )153.1785714285712.9906897895702451.2184754041585
Trimmed Mean ( 15 / 28 )153.4444444444442.8697154411638353.470264766814
Trimmed Mean ( 16 / 28 )153.8269230769232.7406389630846156.1281238240113
Trimmed Mean ( 17 / 28 )154.042.6603605709277357.9019256574993
Trimmed Mean ( 18 / 28 )154.2916666666672.5625090093827760.2111704199748
Trimmed Mean ( 19 / 28 )154.5652173913042.4494211430760363.1027530027762
Trimmed Mean ( 20 / 28 )154.7954545454552.3424070003841766.0839275668434
Trimmed Mean ( 21 / 28 )155.0476190476192.2004519599508570.4617150792431
Trimmed Mean ( 22 / 28 )155.12.0996947275063573.8678808724737
Trimmed Mean ( 23 / 28 )155.1315789473682.0092853632284777.2073403740455
Trimmed Mean ( 24 / 28 )155.2222222222221.9408356534002879.9770047248863
Trimmed Mean ( 25 / 28 )155.3529411764711.8533018917208183.8249514935874
Trimmed Mean ( 26 / 28 )155.531251.760901743311388.3247748437855
Trimmed Mean ( 27 / 28 )155.71.6401219466856794.9319654642971
Trimmed Mean ( 28 / 28 )155.8214285714291.52410401420222102.238054043176
Median152.5
Midrange127
Midmean - Weighted Average at Xnp154.565217391304
Midmean - Weighted Average at X(n+1)p156.227272727273
Midmean - Empirical Distribution Function154.565217391304
Midmean - Empirical Distribution Function - Averaging156.227272727273
Midmean - Empirical Distribution Function - Interpolation156.227272727273
Midmean - Closest Observation154.565217391304
Midmean - True Basic - Statistics Graphics Toolkit156.227272727273
Midmean - MS Excel (old versions)154.565217391304
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 148.107142857143 & 4.43998088415015 & 33.3576082243633 \tabularnewline
Geometric Mean & 141.057180038355 &  &  \tabularnewline
Harmonic Mean & 131.917557089629 &  &  \tabularnewline
Quadratic Mean & 153.53156182424 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 148.154761904762 & 4.42134984981288 & 33.5089434080934 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 148.345238095238 & 4.31243562143135 & 34.399409317095 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 148.380952380952 & 4.24871837048669 & 34.9236968521299 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 148.571428571429 & 4.18807303438379 & 35.4748896095334 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 148.571428571429 & 4.14504265062817 & 35.8431603952044 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 148.642857142857 & 4.1296280165553 & 35.9942485247973 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 148.809523809524 & 4.09411217494064 & 36.3472023850156 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 149.857142857143 & 3.81883722413606 & 39.2415633507514 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 149.857142857143 & 3.78351888626072 & 39.607874933921 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 150.333333333333 & 3.65769778790823 & 41.1005342842461 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 150.464285714286 & 3.59289660751495 & 41.8782676349697 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 150.321428571429 & 3.57315004409323 & 42.0697218746592 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 150.785714285714 & 3.44446438370071 & 43.7762442832145 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 150.785714285714 & 3.44446438370071 & 43.7762442832145 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 149.892857142857 & 3.32638480547706 & 45.0617910760207 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 151.797619047619 & 2.95329778437352 & 51.3993610298325 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 151.595238095238 & 2.92692209221778 & 51.7933970631831 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 151.595238095238 & 2.86541282574913 & 52.9051998137844 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 152.27380952381 & 2.69555589244042 & 56.4906889710042 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 152.27380952381 & 2.69555589244042 & 56.4906889710042 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 154.52380952381 & 2.36448406810891 & 65.3520197526204 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 154.785714285714 & 2.18533627050747 & 70.8292432494935 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 154.238095238095 & 1.96772721345728 & 78.3838807448826 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 153.952380952381 & 1.93170134805549 & 79.697817215562 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 153.654761904762 & 1.81751329424619 & 84.5412038476946 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 153.964285714286 & 1.77535290008568 & 86.7232006137232 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 154.607142857143 & 1.60687509722049 & 96.2160301846584 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 156.940476190476 & 1.23062741304618 & 127.528831656692 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 148.621951219512 & 4.29310912757893 & 34.6187219571859 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 149.1125 & 4.14350925040935 & 35.987007869059 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 149.525641025641 & 4.03719488140973 & 37.0370134258737 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 149.947368421053 & 3.94078515361624 & 38.0501251846867 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 150.337837837838 & 3.84892783442987 & 39.0596665629889 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 150.75 & 3.75318070637566 & 40.1659317239683 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 151.171428571429 & 3.64353543800816 & 41.490313774489 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 151.588235294118 & 3.52173953932479 & 43.0435679871945 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 151.863636363636 & 3.44195195634113 & 44.1213701672555 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 152.15625 & 3.35330466223069 & 45.3750151943493 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 152.403225806452 & 3.27292465376493 & 46.5648439633764 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 152.65 & 3.18815117420811 & 47.8804145910415 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 152.931034482759 & 3.0877332843738 & 49.5285765958808 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 153.178571428571 & 2.99068978957024 & 51.2184754041585 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 153.444444444444 & 2.86971544116383 & 53.470264766814 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 153.826923076923 & 2.74063896308461 & 56.1281238240113 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 154.04 & 2.66036057092773 & 57.9019256574993 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 154.291666666667 & 2.56250900938277 & 60.2111704199748 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 154.565217391304 & 2.44942114307603 & 63.1027530027762 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 154.795454545455 & 2.34240700038417 & 66.0839275668434 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 155.047619047619 & 2.20045195995085 & 70.4617150792431 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 155.1 & 2.09969472750635 & 73.8678808724737 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 155.131578947368 & 2.00928536322847 & 77.2073403740455 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 155.222222222222 & 1.94083565340028 & 79.9770047248863 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 155.352941176471 & 1.85330189172081 & 83.8249514935874 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 155.53125 & 1.7609017433113 & 88.3247748437855 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 155.7 & 1.64012194668567 & 94.9319654642971 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 155.821428571429 & 1.52410401420222 & 102.238054043176 \tabularnewline
Median & 152.5 &  &  \tabularnewline
Midrange & 127 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 154.565217391304 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 156.227272727273 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 154.565217391304 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 156.227272727273 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 156.227272727273 &  &  \tabularnewline
Midmean - Closest Observation & 154.565217391304 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 156.227272727273 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 154.565217391304 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78961&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]148.107142857143[/C][C]4.43998088415015[/C][C]33.3576082243633[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]141.057180038355[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]131.917557089629[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]153.53156182424[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]148.154761904762[/C][C]4.42134984981288[/C][C]33.5089434080934[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]148.345238095238[/C][C]4.31243562143135[/C][C]34.399409317095[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]148.380952380952[/C][C]4.24871837048669[/C][C]34.9236968521299[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]148.571428571429[/C][C]4.18807303438379[/C][C]35.4748896095334[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]148.571428571429[/C][C]4.14504265062817[/C][C]35.8431603952044[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]148.642857142857[/C][C]4.1296280165553[/C][C]35.9942485247973[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]148.809523809524[/C][C]4.09411217494064[/C][C]36.3472023850156[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]149.857142857143[/C][C]3.81883722413606[/C][C]39.2415633507514[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]149.857142857143[/C][C]3.78351888626072[/C][C]39.607874933921[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]150.333333333333[/C][C]3.65769778790823[/C][C]41.1005342842461[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]150.464285714286[/C][C]3.59289660751495[/C][C]41.8782676349697[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]150.321428571429[/C][C]3.57315004409323[/C][C]42.0697218746592[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]150.785714285714[/C][C]3.44446438370071[/C][C]43.7762442832145[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]150.785714285714[/C][C]3.44446438370071[/C][C]43.7762442832145[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]149.892857142857[/C][C]3.32638480547706[/C][C]45.0617910760207[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]151.797619047619[/C][C]2.95329778437352[/C][C]51.3993610298325[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]151.595238095238[/C][C]2.92692209221778[/C][C]51.7933970631831[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]151.595238095238[/C][C]2.86541282574913[/C][C]52.9051998137844[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]152.27380952381[/C][C]2.69555589244042[/C][C]56.4906889710042[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]152.27380952381[/C][C]2.69555589244042[/C][C]56.4906889710042[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]154.52380952381[/C][C]2.36448406810891[/C][C]65.3520197526204[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]154.785714285714[/C][C]2.18533627050747[/C][C]70.8292432494935[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]154.238095238095[/C][C]1.96772721345728[/C][C]78.3838807448826[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]153.952380952381[/C][C]1.93170134805549[/C][C]79.697817215562[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]153.654761904762[/C][C]1.81751329424619[/C][C]84.5412038476946[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]153.964285714286[/C][C]1.77535290008568[/C][C]86.7232006137232[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]154.607142857143[/C][C]1.60687509722049[/C][C]96.2160301846584[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]156.940476190476[/C][C]1.23062741304618[/C][C]127.528831656692[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]148.621951219512[/C][C]4.29310912757893[/C][C]34.6187219571859[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]149.1125[/C][C]4.14350925040935[/C][C]35.987007869059[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]149.525641025641[/C][C]4.03719488140973[/C][C]37.0370134258737[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]149.947368421053[/C][C]3.94078515361624[/C][C]38.0501251846867[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]150.337837837838[/C][C]3.84892783442987[/C][C]39.0596665629889[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]150.75[/C][C]3.75318070637566[/C][C]40.1659317239683[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]151.171428571429[/C][C]3.64353543800816[/C][C]41.490313774489[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]151.588235294118[/C][C]3.52173953932479[/C][C]43.0435679871945[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]151.863636363636[/C][C]3.44195195634113[/C][C]44.1213701672555[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]152.15625[/C][C]3.35330466223069[/C][C]45.3750151943493[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]152.403225806452[/C][C]3.27292465376493[/C][C]46.5648439633764[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]152.65[/C][C]3.18815117420811[/C][C]47.8804145910415[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]152.931034482759[/C][C]3.0877332843738[/C][C]49.5285765958808[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]153.178571428571[/C][C]2.99068978957024[/C][C]51.2184754041585[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]153.444444444444[/C][C]2.86971544116383[/C][C]53.470264766814[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]153.826923076923[/C][C]2.74063896308461[/C][C]56.1281238240113[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]154.04[/C][C]2.66036057092773[/C][C]57.9019256574993[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]154.291666666667[/C][C]2.56250900938277[/C][C]60.2111704199748[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]154.565217391304[/C][C]2.44942114307603[/C][C]63.1027530027762[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]154.795454545455[/C][C]2.34240700038417[/C][C]66.0839275668434[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]155.047619047619[/C][C]2.20045195995085[/C][C]70.4617150792431[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]155.1[/C][C]2.09969472750635[/C][C]73.8678808724737[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]155.131578947368[/C][C]2.00928536322847[/C][C]77.2073403740455[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]155.222222222222[/C][C]1.94083565340028[/C][C]79.9770047248863[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]155.352941176471[/C][C]1.85330189172081[/C][C]83.8249514935874[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]155.53125[/C][C]1.7609017433113[/C][C]88.3247748437855[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]155.7[/C][C]1.64012194668567[/C][C]94.9319654642971[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]155.821428571429[/C][C]1.52410401420222[/C][C]102.238054043176[/C][/ROW]
[ROW][C]Median[/C][C]152.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]127[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]154.565217391304[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]156.227272727273[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]154.565217391304[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]156.227272727273[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]156.227272727273[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]154.565217391304[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]156.227272727273[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]154.565217391304[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78961&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78961&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean148.1071428571434.4399808841501533.3576082243633
Geometric Mean141.057180038355
Harmonic Mean131.917557089629
Quadratic Mean153.53156182424
Winsorized Mean ( 1 / 28 )148.1547619047624.4213498498128833.5089434080934
Winsorized Mean ( 2 / 28 )148.3452380952384.3124356214313534.399409317095
Winsorized Mean ( 3 / 28 )148.3809523809524.2487183704866934.9236968521299
Winsorized Mean ( 4 / 28 )148.5714285714294.1880730343837935.4748896095334
Winsorized Mean ( 5 / 28 )148.5714285714294.1450426506281735.8431603952044
Winsorized Mean ( 6 / 28 )148.6428571428574.129628016555335.9942485247973
Winsorized Mean ( 7 / 28 )148.8095238095244.0941121749406436.3472023850156
Winsorized Mean ( 8 / 28 )149.8571428571433.8188372241360639.2415633507514
Winsorized Mean ( 9 / 28 )149.8571428571433.7835188862607239.607874933921
Winsorized Mean ( 10 / 28 )150.3333333333333.6576977879082341.1005342842461
Winsorized Mean ( 11 / 28 )150.4642857142863.5928966075149541.8782676349697
Winsorized Mean ( 12 / 28 )150.3214285714293.5731500440932342.0697218746592
Winsorized Mean ( 13 / 28 )150.7857142857143.4444643837007143.7762442832145
Winsorized Mean ( 14 / 28 )150.7857142857143.4444643837007143.7762442832145
Winsorized Mean ( 15 / 28 )149.8928571428573.3263848054770645.0617910760207
Winsorized Mean ( 16 / 28 )151.7976190476192.9532977843735251.3993610298325
Winsorized Mean ( 17 / 28 )151.5952380952382.9269220922177851.7933970631831
Winsorized Mean ( 18 / 28 )151.5952380952382.8654128257491352.9051998137844
Winsorized Mean ( 19 / 28 )152.273809523812.6955558924404256.4906889710042
Winsorized Mean ( 20 / 28 )152.273809523812.6955558924404256.4906889710042
Winsorized Mean ( 21 / 28 )154.523809523812.3644840681089165.3520197526204
Winsorized Mean ( 22 / 28 )154.7857142857142.1853362705074770.8292432494935
Winsorized Mean ( 23 / 28 )154.2380952380951.9677272134572878.3838807448826
Winsorized Mean ( 24 / 28 )153.9523809523811.9317013480554979.697817215562
Winsorized Mean ( 25 / 28 )153.6547619047621.8175132942461984.5412038476946
Winsorized Mean ( 26 / 28 )153.9642857142861.7753529000856886.7232006137232
Winsorized Mean ( 27 / 28 )154.6071428571431.6068750972204996.2160301846584
Winsorized Mean ( 28 / 28 )156.9404761904761.23062741304618127.528831656692
Trimmed Mean ( 1 / 28 )148.6219512195124.2931091275789334.6187219571859
Trimmed Mean ( 2 / 28 )149.11254.1435092504093535.987007869059
Trimmed Mean ( 3 / 28 )149.5256410256414.0371948814097337.0370134258737
Trimmed Mean ( 4 / 28 )149.9473684210533.9407851536162438.0501251846867
Trimmed Mean ( 5 / 28 )150.3378378378383.8489278344298739.0596665629889
Trimmed Mean ( 6 / 28 )150.753.7531807063756640.1659317239683
Trimmed Mean ( 7 / 28 )151.1714285714293.6435354380081641.490313774489
Trimmed Mean ( 8 / 28 )151.5882352941183.5217395393247943.0435679871945
Trimmed Mean ( 9 / 28 )151.8636363636363.4419519563411344.1213701672555
Trimmed Mean ( 10 / 28 )152.156253.3533046622306945.3750151943493
Trimmed Mean ( 11 / 28 )152.4032258064523.2729246537649346.5648439633764
Trimmed Mean ( 12 / 28 )152.653.1881511742081147.8804145910415
Trimmed Mean ( 13 / 28 )152.9310344827593.087733284373849.5285765958808
Trimmed Mean ( 14 / 28 )153.1785714285712.9906897895702451.2184754041585
Trimmed Mean ( 15 / 28 )153.4444444444442.8697154411638353.470264766814
Trimmed Mean ( 16 / 28 )153.8269230769232.7406389630846156.1281238240113
Trimmed Mean ( 17 / 28 )154.042.6603605709277357.9019256574993
Trimmed Mean ( 18 / 28 )154.2916666666672.5625090093827760.2111704199748
Trimmed Mean ( 19 / 28 )154.5652173913042.4494211430760363.1027530027762
Trimmed Mean ( 20 / 28 )154.7954545454552.3424070003841766.0839275668434
Trimmed Mean ( 21 / 28 )155.0476190476192.2004519599508570.4617150792431
Trimmed Mean ( 22 / 28 )155.12.0996947275063573.8678808724737
Trimmed Mean ( 23 / 28 )155.1315789473682.0092853632284777.2073403740455
Trimmed Mean ( 24 / 28 )155.2222222222221.9408356534002879.9770047248863
Trimmed Mean ( 25 / 28 )155.3529411764711.8533018917208183.8249514935874
Trimmed Mean ( 26 / 28 )155.531251.760901743311388.3247748437855
Trimmed Mean ( 27 / 28 )155.71.6401219466856794.9319654642971
Trimmed Mean ( 28 / 28 )155.8214285714291.52410401420222102.238054043176
Median152.5
Midrange127
Midmean - Weighted Average at Xnp154.565217391304
Midmean - Weighted Average at X(n+1)p156.227272727273
Midmean - Empirical Distribution Function154.565217391304
Midmean - Empirical Distribution Function - Averaging156.227272727273
Midmean - Empirical Distribution Function - Interpolation156.227272727273
Midmean - Closest Observation154.565217391304
Midmean - True Basic - Statistics Graphics Toolkit156.227272727273
Midmean - MS Excel (old versions)154.565217391304
Number of observations84



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')