Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 26 Sep 2013 13:40:22 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Sep/26/t1380217309yyqhnj5dbsxtljv.htm/, Retrieved Mon, 29 Apr 2024 09:31:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=212169, Retrieved Mon, 29 Apr 2024 09:31:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2013-09-23 09:03:58] [ae3d1feb555b13e324db089723206180]
- R  D  [Univariate Data Series] [] [2013-09-26 17:16:09] [74be16979710d4c4e7c6647856088456]
- RMP     [Histogram] [] [2013-09-26 17:21:24] [74be16979710d4c4e7c6647856088456]
- R P         [Histogram] [] [2013-09-26 17:40:22] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1.41
1.42
1.43
1.43
1.43
1.43
1.43
1.44
1.44
1.45
1.46
1.46
1.47
1.47
1.47
1.49
1.49
1.49
1.49
1.5
1.52
1.54
1.56
1.56
1.57
1.58
1.59
1.6
1.59
1.6
1.61
1.61
1.61
1.62
1.62
1.61
1.62
1.62
1.63
1.64
1.64
1.64
1.64
1.64
1.65
1.65
1.65
1.65
1.65
1.66
1.66
1.67
1.67
1.67
1.67
1.67
1.67
1.69
1.69
1.69
1.7
1.71
1.72
1.71
1.71
1.71
1.72
1.72
1.72
1.73
1.73
1.73
1.74
1.74
1.75
1.76
1.76
1.77
1.78
1.79
1.8
1.8
1.8
1.81




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212169&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212169&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'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1.41,1.42[1.41510.0119050.0119051.190476
[1.42,1.43[1.42510.0119050.023811.190476
[1.43,1.44[1.43550.0595240.0833335.952381
[1.44,1.45[1.44520.023810.1071432.380952
[1.45,1.46[1.45510.0119050.1190481.190476
[1.46,1.47[1.46520.023810.1428572.380952
[1.47,1.48[1.47530.0357140.1785713.571429
[1.48,1.49[1.485000.1785710
[1.49,1.5[1.49540.0476190.226194.761905
[1.5,1.51[1.50510.0119050.2380951.190476
[1.51,1.52[1.515000.2380950
[1.52,1.53[1.52510.0119050.251.190476
[1.53,1.54[1.535000.250
[1.54,1.55[1.54510.0119050.2619051.190476
[1.55,1.56[1.555000.2619050
[1.56,1.57[1.56520.023810.2857142.380952
[1.57,1.58[1.57510.0119050.2976191.190476
[1.58,1.59[1.58510.0119050.3095241.190476
[1.59,1.6[1.59520.023810.3333332.380952
[1.6,1.61[1.60520.023810.3571432.380952
[1.61,1.62[1.61540.0476190.4047624.761905
[1.62,1.63[1.62540.0476190.4523814.761905
[1.63,1.64[1.63510.0119050.4642861.190476
[1.64,1.65[1.64550.0595240.523815.952381
[1.65,1.66[1.65550.0595240.5833335.952381
[1.66,1.67[1.66520.023810.6071432.380952
[1.67,1.68[1.67560.0714290.6785717.142857
[1.68,1.69[1.685000.6785710
[1.69,1.7[1.69530.0357140.7142863.571429
[1.7,1.71[1.70510.0119050.726191.190476
[1.71,1.72[1.71540.0476190.773814.761905
[1.72,1.73[1.72540.0476190.8214294.761905
[1.73,1.74[1.73530.0357140.8571433.571429
[1.74,1.75[1.74520.023810.8809522.380952
[1.75,1.76[1.75510.0119050.8928571.190476
[1.76,1.77[1.76520.023810.9166672.380952
[1.77,1.78[1.77510.0119050.9285711.190476
[1.78,1.79[1.78510.0119050.9404761.190476
[1.79,1.8[1.79510.0119050.9523811.190476
[1.8,1.81]1.80540.04761914.761905

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1.41,1.42[ & 1.415 & 1 & 0.011905 & 0.011905 & 1.190476 \tabularnewline
[1.42,1.43[ & 1.425 & 1 & 0.011905 & 0.02381 & 1.190476 \tabularnewline
[1.43,1.44[ & 1.435 & 5 & 0.059524 & 0.083333 & 5.952381 \tabularnewline
[1.44,1.45[ & 1.445 & 2 & 0.02381 & 0.107143 & 2.380952 \tabularnewline
[1.45,1.46[ & 1.455 & 1 & 0.011905 & 0.119048 & 1.190476 \tabularnewline
[1.46,1.47[ & 1.465 & 2 & 0.02381 & 0.142857 & 2.380952 \tabularnewline
[1.47,1.48[ & 1.475 & 3 & 0.035714 & 0.178571 & 3.571429 \tabularnewline
[1.48,1.49[ & 1.485 & 0 & 0 & 0.178571 & 0 \tabularnewline
[1.49,1.5[ & 1.495 & 4 & 0.047619 & 0.22619 & 4.761905 \tabularnewline
[1.5,1.51[ & 1.505 & 1 & 0.011905 & 0.238095 & 1.190476 \tabularnewline
[1.51,1.52[ & 1.515 & 0 & 0 & 0.238095 & 0 \tabularnewline
[1.52,1.53[ & 1.525 & 1 & 0.011905 & 0.25 & 1.190476 \tabularnewline
[1.53,1.54[ & 1.535 & 0 & 0 & 0.25 & 0 \tabularnewline
[1.54,1.55[ & 1.545 & 1 & 0.011905 & 0.261905 & 1.190476 \tabularnewline
[1.55,1.56[ & 1.555 & 0 & 0 & 0.261905 & 0 \tabularnewline
[1.56,1.57[ & 1.565 & 2 & 0.02381 & 0.285714 & 2.380952 \tabularnewline
[1.57,1.58[ & 1.575 & 1 & 0.011905 & 0.297619 & 1.190476 \tabularnewline
[1.58,1.59[ & 1.585 & 1 & 0.011905 & 0.309524 & 1.190476 \tabularnewline
[1.59,1.6[ & 1.595 & 2 & 0.02381 & 0.333333 & 2.380952 \tabularnewline
[1.6,1.61[ & 1.605 & 2 & 0.02381 & 0.357143 & 2.380952 \tabularnewline
[1.61,1.62[ & 1.615 & 4 & 0.047619 & 0.404762 & 4.761905 \tabularnewline
[1.62,1.63[ & 1.625 & 4 & 0.047619 & 0.452381 & 4.761905 \tabularnewline
[1.63,1.64[ & 1.635 & 1 & 0.011905 & 0.464286 & 1.190476 \tabularnewline
[1.64,1.65[ & 1.645 & 5 & 0.059524 & 0.52381 & 5.952381 \tabularnewline
[1.65,1.66[ & 1.655 & 5 & 0.059524 & 0.583333 & 5.952381 \tabularnewline
[1.66,1.67[ & 1.665 & 2 & 0.02381 & 0.607143 & 2.380952 \tabularnewline
[1.67,1.68[ & 1.675 & 6 & 0.071429 & 0.678571 & 7.142857 \tabularnewline
[1.68,1.69[ & 1.685 & 0 & 0 & 0.678571 & 0 \tabularnewline
[1.69,1.7[ & 1.695 & 3 & 0.035714 & 0.714286 & 3.571429 \tabularnewline
[1.7,1.71[ & 1.705 & 1 & 0.011905 & 0.72619 & 1.190476 \tabularnewline
[1.71,1.72[ & 1.715 & 4 & 0.047619 & 0.77381 & 4.761905 \tabularnewline
[1.72,1.73[ & 1.725 & 4 & 0.047619 & 0.821429 & 4.761905 \tabularnewline
[1.73,1.74[ & 1.735 & 3 & 0.035714 & 0.857143 & 3.571429 \tabularnewline
[1.74,1.75[ & 1.745 & 2 & 0.02381 & 0.880952 & 2.380952 \tabularnewline
[1.75,1.76[ & 1.755 & 1 & 0.011905 & 0.892857 & 1.190476 \tabularnewline
[1.76,1.77[ & 1.765 & 2 & 0.02381 & 0.916667 & 2.380952 \tabularnewline
[1.77,1.78[ & 1.775 & 1 & 0.011905 & 0.928571 & 1.190476 \tabularnewline
[1.78,1.79[ & 1.785 & 1 & 0.011905 & 0.940476 & 1.190476 \tabularnewline
[1.79,1.8[ & 1.795 & 1 & 0.011905 & 0.952381 & 1.190476 \tabularnewline
[1.8,1.81] & 1.805 & 4 & 0.047619 & 1 & 4.761905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212169&T=1

[TABLE]
[ROW][C]Frequency Table (Histogram)[/C][/ROW]
[ROW][C]Bins[/C][C]Midpoint[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][C]Cumul. Rel. Freq.[/C][C]Density[/C][/ROW]
[ROW][C][1.41,1.42[[/C][C]1.415[/C][C]1[/C][C]0.011905[/C][C]0.011905[/C][C]1.190476[/C][/ROW]
[ROW][C][1.42,1.43[[/C][C]1.425[/C][C]1[/C][C]0.011905[/C][C]0.02381[/C][C]1.190476[/C][/ROW]
[ROW][C][1.43,1.44[[/C][C]1.435[/C][C]5[/C][C]0.059524[/C][C]0.083333[/C][C]5.952381[/C][/ROW]
[ROW][C][1.44,1.45[[/C][C]1.445[/C][C]2[/C][C]0.02381[/C][C]0.107143[/C][C]2.380952[/C][/ROW]
[ROW][C][1.45,1.46[[/C][C]1.455[/C][C]1[/C][C]0.011905[/C][C]0.119048[/C][C]1.190476[/C][/ROW]
[ROW][C][1.46,1.47[[/C][C]1.465[/C][C]2[/C][C]0.02381[/C][C]0.142857[/C][C]2.380952[/C][/ROW]
[ROW][C][1.47,1.48[[/C][C]1.475[/C][C]3[/C][C]0.035714[/C][C]0.178571[/C][C]3.571429[/C][/ROW]
[ROW][C][1.48,1.49[[/C][C]1.485[/C][C]0[/C][C]0[/C][C]0.178571[/C][C]0[/C][/ROW]
[ROW][C][1.49,1.5[[/C][C]1.495[/C][C]4[/C][C]0.047619[/C][C]0.22619[/C][C]4.761905[/C][/ROW]
[ROW][C][1.5,1.51[[/C][C]1.505[/C][C]1[/C][C]0.011905[/C][C]0.238095[/C][C]1.190476[/C][/ROW]
[ROW][C][1.51,1.52[[/C][C]1.515[/C][C]0[/C][C]0[/C][C]0.238095[/C][C]0[/C][/ROW]
[ROW][C][1.52,1.53[[/C][C]1.525[/C][C]1[/C][C]0.011905[/C][C]0.25[/C][C]1.190476[/C][/ROW]
[ROW][C][1.53,1.54[[/C][C]1.535[/C][C]0[/C][C]0[/C][C]0.25[/C][C]0[/C][/ROW]
[ROW][C][1.54,1.55[[/C][C]1.545[/C][C]1[/C][C]0.011905[/C][C]0.261905[/C][C]1.190476[/C][/ROW]
[ROW][C][1.55,1.56[[/C][C]1.555[/C][C]0[/C][C]0[/C][C]0.261905[/C][C]0[/C][/ROW]
[ROW][C][1.56,1.57[[/C][C]1.565[/C][C]2[/C][C]0.02381[/C][C]0.285714[/C][C]2.380952[/C][/ROW]
[ROW][C][1.57,1.58[[/C][C]1.575[/C][C]1[/C][C]0.011905[/C][C]0.297619[/C][C]1.190476[/C][/ROW]
[ROW][C][1.58,1.59[[/C][C]1.585[/C][C]1[/C][C]0.011905[/C][C]0.309524[/C][C]1.190476[/C][/ROW]
[ROW][C][1.59,1.6[[/C][C]1.595[/C][C]2[/C][C]0.02381[/C][C]0.333333[/C][C]2.380952[/C][/ROW]
[ROW][C][1.6,1.61[[/C][C]1.605[/C][C]2[/C][C]0.02381[/C][C]0.357143[/C][C]2.380952[/C][/ROW]
[ROW][C][1.61,1.62[[/C][C]1.615[/C][C]4[/C][C]0.047619[/C][C]0.404762[/C][C]4.761905[/C][/ROW]
[ROW][C][1.62,1.63[[/C][C]1.625[/C][C]4[/C][C]0.047619[/C][C]0.452381[/C][C]4.761905[/C][/ROW]
[ROW][C][1.63,1.64[[/C][C]1.635[/C][C]1[/C][C]0.011905[/C][C]0.464286[/C][C]1.190476[/C][/ROW]
[ROW][C][1.64,1.65[[/C][C]1.645[/C][C]5[/C][C]0.059524[/C][C]0.52381[/C][C]5.952381[/C][/ROW]
[ROW][C][1.65,1.66[[/C][C]1.655[/C][C]5[/C][C]0.059524[/C][C]0.583333[/C][C]5.952381[/C][/ROW]
[ROW][C][1.66,1.67[[/C][C]1.665[/C][C]2[/C][C]0.02381[/C][C]0.607143[/C][C]2.380952[/C][/ROW]
[ROW][C][1.67,1.68[[/C][C]1.675[/C][C]6[/C][C]0.071429[/C][C]0.678571[/C][C]7.142857[/C][/ROW]
[ROW][C][1.68,1.69[[/C][C]1.685[/C][C]0[/C][C]0[/C][C]0.678571[/C][C]0[/C][/ROW]
[ROW][C][1.69,1.7[[/C][C]1.695[/C][C]3[/C][C]0.035714[/C][C]0.714286[/C][C]3.571429[/C][/ROW]
[ROW][C][1.7,1.71[[/C][C]1.705[/C][C]1[/C][C]0.011905[/C][C]0.72619[/C][C]1.190476[/C][/ROW]
[ROW][C][1.71,1.72[[/C][C]1.715[/C][C]4[/C][C]0.047619[/C][C]0.77381[/C][C]4.761905[/C][/ROW]
[ROW][C][1.72,1.73[[/C][C]1.725[/C][C]4[/C][C]0.047619[/C][C]0.821429[/C][C]4.761905[/C][/ROW]
[ROW][C][1.73,1.74[[/C][C]1.735[/C][C]3[/C][C]0.035714[/C][C]0.857143[/C][C]3.571429[/C][/ROW]
[ROW][C][1.74,1.75[[/C][C]1.745[/C][C]2[/C][C]0.02381[/C][C]0.880952[/C][C]2.380952[/C][/ROW]
[ROW][C][1.75,1.76[[/C][C]1.755[/C][C]1[/C][C]0.011905[/C][C]0.892857[/C][C]1.190476[/C][/ROW]
[ROW][C][1.76,1.77[[/C][C]1.765[/C][C]2[/C][C]0.02381[/C][C]0.916667[/C][C]2.380952[/C][/ROW]
[ROW][C][1.77,1.78[[/C][C]1.775[/C][C]1[/C][C]0.011905[/C][C]0.928571[/C][C]1.190476[/C][/ROW]
[ROW][C][1.78,1.79[[/C][C]1.785[/C][C]1[/C][C]0.011905[/C][C]0.940476[/C][C]1.190476[/C][/ROW]
[ROW][C][1.79,1.8[[/C][C]1.795[/C][C]1[/C][C]0.011905[/C][C]0.952381[/C][C]1.190476[/C][/ROW]
[ROW][C][1.8,1.81][/C][C]1.805[/C][C]4[/C][C]0.047619[/C][C]1[/C][C]4.761905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212169&T=1

As an alternative you can also use a QR Code:  

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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1.41,1.42[1.41510.0119050.0119051.190476
[1.42,1.43[1.42510.0119050.023811.190476
[1.43,1.44[1.43550.0595240.0833335.952381
[1.44,1.45[1.44520.023810.1071432.380952
[1.45,1.46[1.45510.0119050.1190481.190476
[1.46,1.47[1.46520.023810.1428572.380952
[1.47,1.48[1.47530.0357140.1785713.571429
[1.48,1.49[1.485000.1785710
[1.49,1.5[1.49540.0476190.226194.761905
[1.5,1.51[1.50510.0119050.2380951.190476
[1.51,1.52[1.515000.2380950
[1.52,1.53[1.52510.0119050.251.190476
[1.53,1.54[1.535000.250
[1.54,1.55[1.54510.0119050.2619051.190476
[1.55,1.56[1.555000.2619050
[1.56,1.57[1.56520.023810.2857142.380952
[1.57,1.58[1.57510.0119050.2976191.190476
[1.58,1.59[1.58510.0119050.3095241.190476
[1.59,1.6[1.59520.023810.3333332.380952
[1.6,1.61[1.60520.023810.3571432.380952
[1.61,1.62[1.61540.0476190.4047624.761905
[1.62,1.63[1.62540.0476190.4523814.761905
[1.63,1.64[1.63510.0119050.4642861.190476
[1.64,1.65[1.64550.0595240.523815.952381
[1.65,1.66[1.65550.0595240.5833335.952381
[1.66,1.67[1.66520.023810.6071432.380952
[1.67,1.68[1.67560.0714290.6785717.142857
[1.68,1.69[1.685000.6785710
[1.69,1.7[1.69530.0357140.7142863.571429
[1.7,1.71[1.70510.0119050.726191.190476
[1.71,1.72[1.71540.0476190.773814.761905
[1.72,1.73[1.72540.0476190.8214294.761905
[1.73,1.74[1.73530.0357140.8571433.571429
[1.74,1.75[1.74520.023810.8809522.380952
[1.75,1.76[1.75510.0119050.8928571.190476
[1.76,1.77[1.76520.023810.9166672.380952
[1.77,1.78[1.77510.0119050.9285711.190476
[1.78,1.79[1.78510.0119050.9404761.190476
[1.79,1.8[1.79510.0119050.9523811.190476
[1.8,1.81]1.80540.04761914.761905



Parameters (Session):
par1 = 80 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 80 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '80'
par1 <- as.numeric(par1)
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
if (par4 == 'Unknown') par1 <- as.numeric(par1)
if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1)
if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5)
if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5)
if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5)
if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5)
if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5)
if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5)
if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5)
if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5)
bitmap(file='test1.png')
if(is.numeric(x[1])) {
if (is.na(par1)) {
myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3)
} else {
if (par1 < 0) par1 <- 3
if (par1 > 50) par1 <- 50
myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3)
}
} else {
plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency')
}
dev.off()
if(is.numeric(x[1])) {
myhist
n <- length(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('histogram.htm','Frequency Table (Histogram)',''),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Bins',header=TRUE)
a<-table.element(a,'Midpoint',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
a<-table.element(a,'Density',header=TRUE)
a<-table.row.end(a)
crf <- 0
if (par3 == FALSE) mybracket <- '[' else mybracket <- ']'
mynumrows <- (length(myhist$breaks)-1)
for (i in 1:mynumrows) {
a<-table.row.start(a)
if (i == 1)
dum <- paste('[',myhist$breaks[i],sep='')
else
dum <- paste(mybracket,myhist$breaks[i],sep='')
dum <- paste(dum,myhist$breaks[i+1],sep=',')
if (i==mynumrows)
dum <- paste(dum,']',sep='')
else
dum <- paste(dum,mybracket,sep='')
a<-table.element(a,dum,header=TRUE)
a<-table.element(a,myhist$mids[i])
a<-table.element(a,myhist$counts[i])
rf <- myhist$counts[i]/n
crf <- crf + rf
a<-table.element(a,round(rf,6))
a<-table.element(a,round(crf,6))
a<-table.element(a,round(myhist$density[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
} else {
mytab
reltab <- mytab / sum(mytab)
n <- length(mytab)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Category',header=TRUE)
a<-table.element(a,'Abs. Frequency',header=TRUE)
a<-table.element(a,'Rel. Frequency',header=TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,labels(mytab)$x[i],header=TRUE)
a<-table.element(a,mytab[i])
a<-table.element(a,round(reltab[i],4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}