Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 Oct 2008 09:19:10 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224516031yfyrti7aahdfr5n.htm/, Retrieved Tue, 28 May 2024 16:27:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17455, Retrieved Tue, 28 May 2024 16:27:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [invoer vanuit vs] [2008-10-13 19:11:39] [57ce5bd741080980f0f51979adb31ad8]
-   PD  [Univariate Data Series] [Productie voedsel...] [2008-10-19 13:35:18] [ed2ba3b6182103c15c0ab511ae4e6284]
-   PD    [Univariate Data Series] [Productie Voedsel...] [2008-10-19 14:08:24] [ed2ba3b6182103c15c0ab511ae4e6284]
F RMPD        [Central Tendency] [Central tend voed...] [2008-10-20 15:19:10] [a8228479d4547a92e2d3f176a5299609] [Current]
- RM            [Percentiles] [Percentielen pred...] [2008-10-22 16:03:31] [ed2ba3b6182103c15c0ab511ae4e6284]
Feedback Forum
2008-10-22 16:06:20 [Tom Ardies] [reply
Ik had beter met percentielen gewerkt om een schatting te maken naar de toekomst toe. Dan had mijn predictie tussen 113,2 en 136,3 in het betrouwheidsinterval van 80% gelegen. http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/22/t1224691458hatn4bycbk3ozes.htm
2008-10-24 11:28:21 [2df1bcd103d52957f4a39bd4617794c8] [reply
De schatting die de student maakt ligt niet in dezelfde lijn als de gegevens die we uit de grafiek kunnen afleiden. De curve stijgt tot boven de 130.

Post a new message
Dataseries X:
113.5
121.2
130.4
115.2
117.9
110.7
107.6
124.3
115.1
112.5
127.9
117.4
119.3
130.4
126
125.4
130.5
115.9
108.7
124
119.4
118.6
131.3
111.1
124.8
132.3
126.7
131.7
130.9
122.1
113.2
133.6
119.2
129.4
131.4
117.1
130.5
132.3
140.8
137.5
128.6
126.7
120.8
139.3
128.6
131.3
136.3
128.8
133.2
136.3
151.1
145
134.4
135.7
128.7
129.2
138.6
132.7
132.5
135.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17455&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17455&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17455&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean126.681.19790966713750105.750878780962
Geometric Mean126.342921807406
Harmonic Mean126.002836082217
Quadratic Mean127.013726292345
Winsorized Mean ( 1 / 20 )126.5966666666671.16176849086440108.968927684098
Winsorized Mean ( 2 / 20 )126.5233333333331.11088188784327113.894496541818
Winsorized Mean ( 3 / 20 )126.4683333333331.09042440207831115.980835619865
Winsorized Mean ( 4 / 20 )126.5151.05963916947776119.394416178813
Winsorized Mean ( 5 / 20 )126.4816666666671.02953966913381122.852640319416
Winsorized Mean ( 6 / 20 )126.3916666666671.00203829461726126.134567257176
Winsorized Mean ( 7 / 20 )126.5783333333330.962796925120098131.469399237585
Winsorized Mean ( 8 / 20 )126.5116666666670.946671515663558133.638399987127
Winsorized Mean ( 9 / 20 )126.5416666666670.913471962550218138.528243727798
Winsorized Mean ( 10 / 20 )126.6083333333330.85378615611677148.290450045687
Winsorized Mean ( 11 / 20 )126.5166666666670.821347131918722154.035561518447
Winsorized Mean ( 12 / 20 )126.5366666666670.791126518079305159.944918764538
Winsorized Mean ( 13 / 20 )126.580.748126851082578169.195905502967
Winsorized Mean ( 14 / 20 )126.6733333333330.716641833757123176.759613193701
Winsorized Mean ( 15 / 20 )126.6483333333330.70538482371624179.545021490682
Winsorized Mean ( 16 / 20 )126.6750.70068418944153180.787581493689
Winsorized Mean ( 17 / 20 )126.9016666666670.609090697961108208.346092119715
Winsorized Mean ( 18 / 20 )126.9316666666670.576877880068426220.032126472956
Winsorized Mean ( 19 / 20 )127.1850.525291552082524242.122683100030
Winsorized Mean ( 20 / 20 )127.8183333333330.424686602074009300.970957664114
Trimmed Mean ( 1 / 20 )126.5879310344831.11620380539835113.409334766876
Trimmed Mean ( 2 / 20 )126.5785714285711.05989375320786119.425717007455
Trimmed Mean ( 3 / 20 )126.6092592592591.02477441576387123.548419351282
Trimmed Mean ( 4 / 20 )126.6634615384620.990874763392508127.829939986359
Trimmed Mean ( 5 / 20 )126.7080.960577377392984131.908165840722
Trimmed Mean ( 6 / 20 )126.7645833333330.93245980644336135.946431639607
Trimmed Mean ( 7 / 20 )126.8456521739130.90473102481521140.202611267610
Trimmed Mean ( 8 / 20 )126.8977272727270.880523872490113144.116169064061
Trimmed Mean ( 9 / 20 )126.9666666666670.852812976507586148.879848412505
Trimmed Mean ( 10 / 20 )127.03750.825061672131552153.973338346693
Trimmed Mean ( 11 / 20 )127.1052631578950.803972598915437158.096511410165
Trimmed Mean ( 12 / 20 )127.1944444444440.782820951415653162.482166853641
Trimmed Mean ( 13 / 20 )127.2911764705880.760761974330672167.320634791954
Trimmed Mean ( 14 / 20 )127.393750.740694115122714171.992388489403
Trimmed Mean ( 15 / 20 )127.4966666666670.71976182735861177.137299896211
Trimmed Mean ( 16 / 20 )127.6178571428570.690104922078481184.925296226686
Trimmed Mean ( 17 / 20 )127.7538461538460.64462823559799198.182206578859
Trimmed Mean ( 18 / 20 )127.8791666666670.610594245080646209.433953393676
Trimmed Mean ( 19 / 20 )128.0227272727270.566638596892579225.933651492853
Trimmed Mean ( 20 / 20 )128.1550.518523967877241247.153473974689
Median128.65
Midrange129.35
Midmean - Weighted Average at Xnp127.229032258065
Midmean - Weighted Average at X(n+1)p127.496666666667
Midmean - Empirical Distribution Function127.229032258065
Midmean - Empirical Distribution Function - Averaging127.496666666667
Midmean - Empirical Distribution Function - Interpolation127.496666666667
Midmean - Closest Observation127.229032258065
Midmean - True Basic - Statistics Graphics Toolkit127.496666666667
Midmean - MS Excel (old versions)127.39375
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 126.68 & 1.19790966713750 & 105.750878780962 \tabularnewline
Geometric Mean & 126.342921807406 &  &  \tabularnewline
Harmonic Mean & 126.002836082217 &  &  \tabularnewline
Quadratic Mean & 127.013726292345 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 126.596666666667 & 1.16176849086440 & 108.968927684098 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 126.523333333333 & 1.11088188784327 & 113.894496541818 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 126.468333333333 & 1.09042440207831 & 115.980835619865 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 126.515 & 1.05963916947776 & 119.394416178813 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 126.481666666667 & 1.02953966913381 & 122.852640319416 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 126.391666666667 & 1.00203829461726 & 126.134567257176 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 126.578333333333 & 0.962796925120098 & 131.469399237585 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 126.511666666667 & 0.946671515663558 & 133.638399987127 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 126.541666666667 & 0.913471962550218 & 138.528243727798 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 126.608333333333 & 0.85378615611677 & 148.290450045687 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 126.516666666667 & 0.821347131918722 & 154.035561518447 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 126.536666666667 & 0.791126518079305 & 159.944918764538 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 126.58 & 0.748126851082578 & 169.195905502967 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 126.673333333333 & 0.716641833757123 & 176.759613193701 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 126.648333333333 & 0.70538482371624 & 179.545021490682 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 126.675 & 0.70068418944153 & 180.787581493689 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 126.901666666667 & 0.609090697961108 & 208.346092119715 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 126.931666666667 & 0.576877880068426 & 220.032126472956 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 127.185 & 0.525291552082524 & 242.122683100030 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 127.818333333333 & 0.424686602074009 & 300.970957664114 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 126.587931034483 & 1.11620380539835 & 113.409334766876 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 126.578571428571 & 1.05989375320786 & 119.425717007455 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 126.609259259259 & 1.02477441576387 & 123.548419351282 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 126.663461538462 & 0.990874763392508 & 127.829939986359 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 126.708 & 0.960577377392984 & 131.908165840722 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 126.764583333333 & 0.93245980644336 & 135.946431639607 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 126.845652173913 & 0.90473102481521 & 140.202611267610 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 126.897727272727 & 0.880523872490113 & 144.116169064061 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 126.966666666667 & 0.852812976507586 & 148.879848412505 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 127.0375 & 0.825061672131552 & 153.973338346693 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 127.105263157895 & 0.803972598915437 & 158.096511410165 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 127.194444444444 & 0.782820951415653 & 162.482166853641 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 127.291176470588 & 0.760761974330672 & 167.320634791954 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 127.39375 & 0.740694115122714 & 171.992388489403 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 127.496666666667 & 0.71976182735861 & 177.137299896211 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 127.617857142857 & 0.690104922078481 & 184.925296226686 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 127.753846153846 & 0.64462823559799 & 198.182206578859 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 127.879166666667 & 0.610594245080646 & 209.433953393676 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 128.022727272727 & 0.566638596892579 & 225.933651492853 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 128.155 & 0.518523967877241 & 247.153473974689 \tabularnewline
Median & 128.65 &  &  \tabularnewline
Midrange & 129.35 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 127.229032258065 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 127.496666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 127.229032258065 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 127.496666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 127.496666666667 &  &  \tabularnewline
Midmean - Closest Observation & 127.229032258065 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 127.496666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 127.39375 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17455&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]126.68[/C][C]1.19790966713750[/C][C]105.750878780962[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]126.342921807406[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]126.002836082217[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]127.013726292345[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]126.596666666667[/C][C]1.16176849086440[/C][C]108.968927684098[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]126.523333333333[/C][C]1.11088188784327[/C][C]113.894496541818[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]126.468333333333[/C][C]1.09042440207831[/C][C]115.980835619865[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]126.515[/C][C]1.05963916947776[/C][C]119.394416178813[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]126.481666666667[/C][C]1.02953966913381[/C][C]122.852640319416[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]126.391666666667[/C][C]1.00203829461726[/C][C]126.134567257176[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]126.578333333333[/C][C]0.962796925120098[/C][C]131.469399237585[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]126.511666666667[/C][C]0.946671515663558[/C][C]133.638399987127[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]126.541666666667[/C][C]0.913471962550218[/C][C]138.528243727798[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]126.608333333333[/C][C]0.85378615611677[/C][C]148.290450045687[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]126.516666666667[/C][C]0.821347131918722[/C][C]154.035561518447[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]126.536666666667[/C][C]0.791126518079305[/C][C]159.944918764538[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]126.58[/C][C]0.748126851082578[/C][C]169.195905502967[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]126.673333333333[/C][C]0.716641833757123[/C][C]176.759613193701[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]126.648333333333[/C][C]0.70538482371624[/C][C]179.545021490682[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]126.675[/C][C]0.70068418944153[/C][C]180.787581493689[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]126.901666666667[/C][C]0.609090697961108[/C][C]208.346092119715[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]126.931666666667[/C][C]0.576877880068426[/C][C]220.032126472956[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]127.185[/C][C]0.525291552082524[/C][C]242.122683100030[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]127.818333333333[/C][C]0.424686602074009[/C][C]300.970957664114[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]126.587931034483[/C][C]1.11620380539835[/C][C]113.409334766876[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]126.578571428571[/C][C]1.05989375320786[/C][C]119.425717007455[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]126.609259259259[/C][C]1.02477441576387[/C][C]123.548419351282[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]126.663461538462[/C][C]0.990874763392508[/C][C]127.829939986359[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]126.708[/C][C]0.960577377392984[/C][C]131.908165840722[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]126.764583333333[/C][C]0.93245980644336[/C][C]135.946431639607[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]126.845652173913[/C][C]0.90473102481521[/C][C]140.202611267610[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]126.897727272727[/C][C]0.880523872490113[/C][C]144.116169064061[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]126.966666666667[/C][C]0.852812976507586[/C][C]148.879848412505[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]127.0375[/C][C]0.825061672131552[/C][C]153.973338346693[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]127.105263157895[/C][C]0.803972598915437[/C][C]158.096511410165[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]127.194444444444[/C][C]0.782820951415653[/C][C]162.482166853641[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]127.291176470588[/C][C]0.760761974330672[/C][C]167.320634791954[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]127.39375[/C][C]0.740694115122714[/C][C]171.992388489403[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]127.496666666667[/C][C]0.71976182735861[/C][C]177.137299896211[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]127.617857142857[/C][C]0.690104922078481[/C][C]184.925296226686[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]127.753846153846[/C][C]0.64462823559799[/C][C]198.182206578859[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]127.879166666667[/C][C]0.610594245080646[/C][C]209.433953393676[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]128.022727272727[/C][C]0.566638596892579[/C][C]225.933651492853[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]128.155[/C][C]0.518523967877241[/C][C]247.153473974689[/C][/ROW]
[ROW][C]Median[/C][C]128.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]129.35[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]127.229032258065[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]127.496666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]127.229032258065[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]127.496666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]127.496666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]127.229032258065[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]127.496666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]127.39375[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17455&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17455&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 Mean126.681.19790966713750105.750878780962
Geometric Mean126.342921807406
Harmonic Mean126.002836082217
Quadratic Mean127.013726292345
Winsorized Mean ( 1 / 20 )126.5966666666671.16176849086440108.968927684098
Winsorized Mean ( 2 / 20 )126.5233333333331.11088188784327113.894496541818
Winsorized Mean ( 3 / 20 )126.4683333333331.09042440207831115.980835619865
Winsorized Mean ( 4 / 20 )126.5151.05963916947776119.394416178813
Winsorized Mean ( 5 / 20 )126.4816666666671.02953966913381122.852640319416
Winsorized Mean ( 6 / 20 )126.3916666666671.00203829461726126.134567257176
Winsorized Mean ( 7 / 20 )126.5783333333330.962796925120098131.469399237585
Winsorized Mean ( 8 / 20 )126.5116666666670.946671515663558133.638399987127
Winsorized Mean ( 9 / 20 )126.5416666666670.913471962550218138.528243727798
Winsorized Mean ( 10 / 20 )126.6083333333330.85378615611677148.290450045687
Winsorized Mean ( 11 / 20 )126.5166666666670.821347131918722154.035561518447
Winsorized Mean ( 12 / 20 )126.5366666666670.791126518079305159.944918764538
Winsorized Mean ( 13 / 20 )126.580.748126851082578169.195905502967
Winsorized Mean ( 14 / 20 )126.6733333333330.716641833757123176.759613193701
Winsorized Mean ( 15 / 20 )126.6483333333330.70538482371624179.545021490682
Winsorized Mean ( 16 / 20 )126.6750.70068418944153180.787581493689
Winsorized Mean ( 17 / 20 )126.9016666666670.609090697961108208.346092119715
Winsorized Mean ( 18 / 20 )126.9316666666670.576877880068426220.032126472956
Winsorized Mean ( 19 / 20 )127.1850.525291552082524242.122683100030
Winsorized Mean ( 20 / 20 )127.8183333333330.424686602074009300.970957664114
Trimmed Mean ( 1 / 20 )126.5879310344831.11620380539835113.409334766876
Trimmed Mean ( 2 / 20 )126.5785714285711.05989375320786119.425717007455
Trimmed Mean ( 3 / 20 )126.6092592592591.02477441576387123.548419351282
Trimmed Mean ( 4 / 20 )126.6634615384620.990874763392508127.829939986359
Trimmed Mean ( 5 / 20 )126.7080.960577377392984131.908165840722
Trimmed Mean ( 6 / 20 )126.7645833333330.93245980644336135.946431639607
Trimmed Mean ( 7 / 20 )126.8456521739130.90473102481521140.202611267610
Trimmed Mean ( 8 / 20 )126.8977272727270.880523872490113144.116169064061
Trimmed Mean ( 9 / 20 )126.9666666666670.852812976507586148.879848412505
Trimmed Mean ( 10 / 20 )127.03750.825061672131552153.973338346693
Trimmed Mean ( 11 / 20 )127.1052631578950.803972598915437158.096511410165
Trimmed Mean ( 12 / 20 )127.1944444444440.782820951415653162.482166853641
Trimmed Mean ( 13 / 20 )127.2911764705880.760761974330672167.320634791954
Trimmed Mean ( 14 / 20 )127.393750.740694115122714171.992388489403
Trimmed Mean ( 15 / 20 )127.4966666666670.71976182735861177.137299896211
Trimmed Mean ( 16 / 20 )127.6178571428570.690104922078481184.925296226686
Trimmed Mean ( 17 / 20 )127.7538461538460.64462823559799198.182206578859
Trimmed Mean ( 18 / 20 )127.8791666666670.610594245080646209.433953393676
Trimmed Mean ( 19 / 20 )128.0227272727270.566638596892579225.933651492853
Trimmed Mean ( 20 / 20 )128.1550.518523967877241247.153473974689
Median128.65
Midrange129.35
Midmean - Weighted Average at Xnp127.229032258065
Midmean - Weighted Average at X(n+1)p127.496666666667
Midmean - Empirical Distribution Function127.229032258065
Midmean - Empirical Distribution Function - Averaging127.496666666667
Midmean - Empirical Distribution Function - Interpolation127.496666666667
Midmean - Closest Observation127.229032258065
Midmean - True Basic - Statistics Graphics Toolkit127.496666666667
Midmean - MS Excel (old versions)127.39375
Number of observations60



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')