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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 18 May 2011 09:15:11 +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/2011/May/18/t1305710118jpruyk0300g0olj.htm/, Retrieved Tue, 14 May 2024 14:27:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121763, Retrieved Tue, 14 May 2024 14:27:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequentie Goudko...] [2011-05-18 09:15:11] [c36145ff2c4b869a20a15db58f99fa4e] [Current]
- R P     [Histogram] [Frequentie Goudko...] [2011-05-18 11:02:02] [ee77ed46a5e4873119862e461c706b0b]
- RMP     [Kernel Density Estimation] [Dichtheidsgrafiek...] [2011-05-18 11:23:23] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Quartiles] [Kwartielen Maxpri...] [2011-05-18 11:38:17] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Quartiles] [Kwartielen Maxpri...] [2011-05-18 11:37:29] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Quartiles] [Kwartielen Maxpri...] [2011-05-18 11:44:43] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Notched Boxplots] [Boxplot Maxprijs ...] [2011-05-18 11:47:30] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Quartiles] [Kwartielen Goudko...] [2011-05-18 12:17:18] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Notched Boxplots] [Boxplot Goudkoers...] [2011-05-18 12:22:24] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Harrell-Davis Quantiles] [HD Quantiles Insc...] [2011-05-18 12:42:11] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Harrell-Davis Quantiles] [Decielen Inschrij...] [2011-05-18 12:46:56] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Harrell-Davis Quantiles] [HD Decielen Goudk...] [2011-05-18 13:28:35] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Central Tendency] [Centrummaten Maxp...] [2011-05-18 13:42:14] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Mean versus Median] [rekenkundig gemid...] [2011-05-18 14:22:17] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Central Tendency] [Centrummaten Goud...] [2011-05-18 14:30:36] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Mean versus Median] [rekenkundig gemid...] [2011-05-18 14:41:39] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Univariate Data Series] [Plot en beschrijv...] [2011-05-18 15:32:56] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Mean Plot] [Meanplot Inschrij...] [2011-05-18 15:41:29] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Mean Plot] [Meanplot Goudkoer...] [2011-05-18 16:12:33] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [(Partial) Autocorrelation Function] [Autocorrelatie In...] [2011-05-18 16:39:20] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [(Partial) Autocorrelation Function] [Autocorrelatie(aa...] [2011-05-18 16:57:52] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [(Partial) Autocorrelation Function] [Autocorrelatie Go...] [2011-05-18 17:07:16] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [(Partial) Autocorrelation Function] [Autocorrelatie(aa...] [2011-05-18 17:09:15] [ee77ed46a5e4873119862e461c706b0b]
- RMPD    [Bootstrap Plot - Central Tendency] [BootstrapPlot Max...] [2011-05-18 17:18:55] [ee77ed46a5e4873119862e461c706b0b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
32.819
32.700
32.242
32.810
33.865
32.226
31.077
31.293
30.236
30.160
32.436
30.695
27.525
26.434
25.739
25.204
24.977
24.320
22.680
22.052
21.467
21.383
21.777
21.928
21.814
22.937
23.595
20.830
19.650
19.195
19.644
18.483
18.079
19.178
18.391
18.441
18.584
20.108
20.148
19.394
17.745
17.696
17.032
16.438
15.683
15.594
15.713
15.937
16.171
15.928
16.348
15.579
15.305
15.648
14.954
15.137
15.839
16.050
15.168
17.064
16.005
14.886
14.931
14.544
13.812
13.031
12.574
11.964
11.451
11.346
11.353
10.702
10.646
10.556
10.463
10.407
10.625
10.872
10.805
10.653
10.574
10.431
10.383
10.296
10.872
10.635
10.297
10.570
10.662
10.709
10.413
10.846
10.371
9.924
9.828

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121763&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121763&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121763&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ www.wessa.org






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[9.5,10[9.7520.0210530.0210530.042105
[10,10.5[10.2580.0842110.1052630.168421
[10.5,11[10.75140.1473680.2526320.294737
[11,11.5[11.2530.0315790.2842110.063158
[11.5,12[11.7510.0105260.2947370.021053
[12,12.5[12.25000.2947370
[12.5,13[12.7510.0105260.3052630.021053
[13,13.5[13.2510.0105260.3157890.021053
[13.5,14[13.7510.0105260.3263160.021053
[14,14.5[14.25000.3263160
[14.5,15[14.7540.0421050.3684210.084211
[15,15.5[15.2530.0315790.40.063158
[15.5,16[15.7580.0842110.4842110.168421
[16,16.5[16.2550.0526320.5368420.105263
[16.5,17[16.75000.5368420
[17,17.5[17.2520.0210530.5578950.042105
[17.5,18[17.7520.0210530.5789470.042105
[18,18.5[18.2540.0421050.6210530.084211
[18.5,19[18.7510.0105260.6315790.021053
[19,19.5[19.2530.0315790.6631580.063158
[19.5,20[19.7520.0210530.6842110.042105
[20,20.5[20.2520.0210530.7052630.042105
[20.5,21[20.7510.0105260.7157890.021053
[21,21.5[21.2520.0210530.7368420.042105
[21.5,22[21.7530.0315790.7684210.063158
[22,22.5[22.2510.0105260.7789470.021053
[22.5,23[22.7520.0210530.80.042105
[23,23.5[23.25000.80
[23.5,24[23.7510.0105260.8105260.021053
[24,24.5[24.2510.0105260.8210530.021053
[24.5,25[24.7510.0105260.8315790.021053
[25,25.5[25.2510.0105260.8421050.021053
[25.5,26[25.7510.0105260.8526320.021053
[26,26.5[26.2510.0105260.8631580.021053
[26.5,27[26.75000.8631580
[27,27.5[27.25000.8631580
[27.5,28[27.7510.0105260.8736840.021053
[28,28.5[28.25000.8736840
[28.5,29[28.75000.8736840
[29,29.5[29.25000.8736840
[29.5,30[29.75000.8736840
[30,30.5[30.2520.0210530.8947370.042105
[30.5,31[30.7510.0105260.9052630.021053
[31,31.5[31.2520.0210530.9263160.042105
[31.5,32[31.75000.9263160
[32,32.5[32.2530.0315790.9578950.063158
[32.5,33[32.7530.0315790.9894740.063158
[33,33.5[33.25000.9894740
[33.5,34]33.7510.01052610.021053

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[9.5,10[ & 9.75 & 2 & 0.021053 & 0.021053 & 0.042105 \tabularnewline
[10,10.5[ & 10.25 & 8 & 0.084211 & 0.105263 & 0.168421 \tabularnewline
[10.5,11[ & 10.75 & 14 & 0.147368 & 0.252632 & 0.294737 \tabularnewline
[11,11.5[ & 11.25 & 3 & 0.031579 & 0.284211 & 0.063158 \tabularnewline
[11.5,12[ & 11.75 & 1 & 0.010526 & 0.294737 & 0.021053 \tabularnewline
[12,12.5[ & 12.25 & 0 & 0 & 0.294737 & 0 \tabularnewline
[12.5,13[ & 12.75 & 1 & 0.010526 & 0.305263 & 0.021053 \tabularnewline
[13,13.5[ & 13.25 & 1 & 0.010526 & 0.315789 & 0.021053 \tabularnewline
[13.5,14[ & 13.75 & 1 & 0.010526 & 0.326316 & 0.021053 \tabularnewline
[14,14.5[ & 14.25 & 0 & 0 & 0.326316 & 0 \tabularnewline
[14.5,15[ & 14.75 & 4 & 0.042105 & 0.368421 & 0.084211 \tabularnewline
[15,15.5[ & 15.25 & 3 & 0.031579 & 0.4 & 0.063158 \tabularnewline
[15.5,16[ & 15.75 & 8 & 0.084211 & 0.484211 & 0.168421 \tabularnewline
[16,16.5[ & 16.25 & 5 & 0.052632 & 0.536842 & 0.105263 \tabularnewline
[16.5,17[ & 16.75 & 0 & 0 & 0.536842 & 0 \tabularnewline
[17,17.5[ & 17.25 & 2 & 0.021053 & 0.557895 & 0.042105 \tabularnewline
[17.5,18[ & 17.75 & 2 & 0.021053 & 0.578947 & 0.042105 \tabularnewline
[18,18.5[ & 18.25 & 4 & 0.042105 & 0.621053 & 0.084211 \tabularnewline
[18.5,19[ & 18.75 & 1 & 0.010526 & 0.631579 & 0.021053 \tabularnewline
[19,19.5[ & 19.25 & 3 & 0.031579 & 0.663158 & 0.063158 \tabularnewline
[19.5,20[ & 19.75 & 2 & 0.021053 & 0.684211 & 0.042105 \tabularnewline
[20,20.5[ & 20.25 & 2 & 0.021053 & 0.705263 & 0.042105 \tabularnewline
[20.5,21[ & 20.75 & 1 & 0.010526 & 0.715789 & 0.021053 \tabularnewline
[21,21.5[ & 21.25 & 2 & 0.021053 & 0.736842 & 0.042105 \tabularnewline
[21.5,22[ & 21.75 & 3 & 0.031579 & 0.768421 & 0.063158 \tabularnewline
[22,22.5[ & 22.25 & 1 & 0.010526 & 0.778947 & 0.021053 \tabularnewline
[22.5,23[ & 22.75 & 2 & 0.021053 & 0.8 & 0.042105 \tabularnewline
[23,23.5[ & 23.25 & 0 & 0 & 0.8 & 0 \tabularnewline
[23.5,24[ & 23.75 & 1 & 0.010526 & 0.810526 & 0.021053 \tabularnewline
[24,24.5[ & 24.25 & 1 & 0.010526 & 0.821053 & 0.021053 \tabularnewline
[24.5,25[ & 24.75 & 1 & 0.010526 & 0.831579 & 0.021053 \tabularnewline
[25,25.5[ & 25.25 & 1 & 0.010526 & 0.842105 & 0.021053 \tabularnewline
[25.5,26[ & 25.75 & 1 & 0.010526 & 0.852632 & 0.021053 \tabularnewline
[26,26.5[ & 26.25 & 1 & 0.010526 & 0.863158 & 0.021053 \tabularnewline
[26.5,27[ & 26.75 & 0 & 0 & 0.863158 & 0 \tabularnewline
[27,27.5[ & 27.25 & 0 & 0 & 0.863158 & 0 \tabularnewline
[27.5,28[ & 27.75 & 1 & 0.010526 & 0.873684 & 0.021053 \tabularnewline
[28,28.5[ & 28.25 & 0 & 0 & 0.873684 & 0 \tabularnewline
[28.5,29[ & 28.75 & 0 & 0 & 0.873684 & 0 \tabularnewline
[29,29.5[ & 29.25 & 0 & 0 & 0.873684 & 0 \tabularnewline
[29.5,30[ & 29.75 & 0 & 0 & 0.873684 & 0 \tabularnewline
[30,30.5[ & 30.25 & 2 & 0.021053 & 0.894737 & 0.042105 \tabularnewline
[30.5,31[ & 30.75 & 1 & 0.010526 & 0.905263 & 0.021053 \tabularnewline
[31,31.5[ & 31.25 & 2 & 0.021053 & 0.926316 & 0.042105 \tabularnewline
[31.5,32[ & 31.75 & 0 & 0 & 0.926316 & 0 \tabularnewline
[32,32.5[ & 32.25 & 3 & 0.031579 & 0.957895 & 0.063158 \tabularnewline
[32.5,33[ & 32.75 & 3 & 0.031579 & 0.989474 & 0.063158 \tabularnewline
[33,33.5[ & 33.25 & 0 & 0 & 0.989474 & 0 \tabularnewline
[33.5,34] & 33.75 & 1 & 0.010526 & 1 & 0.021053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121763&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][9.5,10[[/C][C]9.75[/C][C]2[/C][C]0.021053[/C][C]0.021053[/C][C]0.042105[/C][/ROW]
[ROW][C][10,10.5[[/C][C]10.25[/C][C]8[/C][C]0.084211[/C][C]0.105263[/C][C]0.168421[/C][/ROW]
[ROW][C][10.5,11[[/C][C]10.75[/C][C]14[/C][C]0.147368[/C][C]0.252632[/C][C]0.294737[/C][/ROW]
[ROW][C][11,11.5[[/C][C]11.25[/C][C]3[/C][C]0.031579[/C][C]0.284211[/C][C]0.063158[/C][/ROW]
[ROW][C][11.5,12[[/C][C]11.75[/C][C]1[/C][C]0.010526[/C][C]0.294737[/C][C]0.021053[/C][/ROW]
[ROW][C][12,12.5[[/C][C]12.25[/C][C]0[/C][C]0[/C][C]0.294737[/C][C]0[/C][/ROW]
[ROW][C][12.5,13[[/C][C]12.75[/C][C]1[/C][C]0.010526[/C][C]0.305263[/C][C]0.021053[/C][/ROW]
[ROW][C][13,13.5[[/C][C]13.25[/C][C]1[/C][C]0.010526[/C][C]0.315789[/C][C]0.021053[/C][/ROW]
[ROW][C][13.5,14[[/C][C]13.75[/C][C]1[/C][C]0.010526[/C][C]0.326316[/C][C]0.021053[/C][/ROW]
[ROW][C][14,14.5[[/C][C]14.25[/C][C]0[/C][C]0[/C][C]0.326316[/C][C]0[/C][/ROW]
[ROW][C][14.5,15[[/C][C]14.75[/C][C]4[/C][C]0.042105[/C][C]0.368421[/C][C]0.084211[/C][/ROW]
[ROW][C][15,15.5[[/C][C]15.25[/C][C]3[/C][C]0.031579[/C][C]0.4[/C][C]0.063158[/C][/ROW]
[ROW][C][15.5,16[[/C][C]15.75[/C][C]8[/C][C]0.084211[/C][C]0.484211[/C][C]0.168421[/C][/ROW]
[ROW][C][16,16.5[[/C][C]16.25[/C][C]5[/C][C]0.052632[/C][C]0.536842[/C][C]0.105263[/C][/ROW]
[ROW][C][16.5,17[[/C][C]16.75[/C][C]0[/C][C]0[/C][C]0.536842[/C][C]0[/C][/ROW]
[ROW][C][17,17.5[[/C][C]17.25[/C][C]2[/C][C]0.021053[/C][C]0.557895[/C][C]0.042105[/C][/ROW]
[ROW][C][17.5,18[[/C][C]17.75[/C][C]2[/C][C]0.021053[/C][C]0.578947[/C][C]0.042105[/C][/ROW]
[ROW][C][18,18.5[[/C][C]18.25[/C][C]4[/C][C]0.042105[/C][C]0.621053[/C][C]0.084211[/C][/ROW]
[ROW][C][18.5,19[[/C][C]18.75[/C][C]1[/C][C]0.010526[/C][C]0.631579[/C][C]0.021053[/C][/ROW]
[ROW][C][19,19.5[[/C][C]19.25[/C][C]3[/C][C]0.031579[/C][C]0.663158[/C][C]0.063158[/C][/ROW]
[ROW][C][19.5,20[[/C][C]19.75[/C][C]2[/C][C]0.021053[/C][C]0.684211[/C][C]0.042105[/C][/ROW]
[ROW][C][20,20.5[[/C][C]20.25[/C][C]2[/C][C]0.021053[/C][C]0.705263[/C][C]0.042105[/C][/ROW]
[ROW][C][20.5,21[[/C][C]20.75[/C][C]1[/C][C]0.010526[/C][C]0.715789[/C][C]0.021053[/C][/ROW]
[ROW][C][21,21.5[[/C][C]21.25[/C][C]2[/C][C]0.021053[/C][C]0.736842[/C][C]0.042105[/C][/ROW]
[ROW][C][21.5,22[[/C][C]21.75[/C][C]3[/C][C]0.031579[/C][C]0.768421[/C][C]0.063158[/C][/ROW]
[ROW][C][22,22.5[[/C][C]22.25[/C][C]1[/C][C]0.010526[/C][C]0.778947[/C][C]0.021053[/C][/ROW]
[ROW][C][22.5,23[[/C][C]22.75[/C][C]2[/C][C]0.021053[/C][C]0.8[/C][C]0.042105[/C][/ROW]
[ROW][C][23,23.5[[/C][C]23.25[/C][C]0[/C][C]0[/C][C]0.8[/C][C]0[/C][/ROW]
[ROW][C][23.5,24[[/C][C]23.75[/C][C]1[/C][C]0.010526[/C][C]0.810526[/C][C]0.021053[/C][/ROW]
[ROW][C][24,24.5[[/C][C]24.25[/C][C]1[/C][C]0.010526[/C][C]0.821053[/C][C]0.021053[/C][/ROW]
[ROW][C][24.5,25[[/C][C]24.75[/C][C]1[/C][C]0.010526[/C][C]0.831579[/C][C]0.021053[/C][/ROW]
[ROW][C][25,25.5[[/C][C]25.25[/C][C]1[/C][C]0.010526[/C][C]0.842105[/C][C]0.021053[/C][/ROW]
[ROW][C][25.5,26[[/C][C]25.75[/C][C]1[/C][C]0.010526[/C][C]0.852632[/C][C]0.021053[/C][/ROW]
[ROW][C][26,26.5[[/C][C]26.25[/C][C]1[/C][C]0.010526[/C][C]0.863158[/C][C]0.021053[/C][/ROW]
[ROW][C][26.5,27[[/C][C]26.75[/C][C]0[/C][C]0[/C][C]0.863158[/C][C]0[/C][/ROW]
[ROW][C][27,27.5[[/C][C]27.25[/C][C]0[/C][C]0[/C][C]0.863158[/C][C]0[/C][/ROW]
[ROW][C][27.5,28[[/C][C]27.75[/C][C]1[/C][C]0.010526[/C][C]0.873684[/C][C]0.021053[/C][/ROW]
[ROW][C][28,28.5[[/C][C]28.25[/C][C]0[/C][C]0[/C][C]0.873684[/C][C]0[/C][/ROW]
[ROW][C][28.5,29[[/C][C]28.75[/C][C]0[/C][C]0[/C][C]0.873684[/C][C]0[/C][/ROW]
[ROW][C][29,29.5[[/C][C]29.25[/C][C]0[/C][C]0[/C][C]0.873684[/C][C]0[/C][/ROW]
[ROW][C][29.5,30[[/C][C]29.75[/C][C]0[/C][C]0[/C][C]0.873684[/C][C]0[/C][/ROW]
[ROW][C][30,30.5[[/C][C]30.25[/C][C]2[/C][C]0.021053[/C][C]0.894737[/C][C]0.042105[/C][/ROW]
[ROW][C][30.5,31[[/C][C]30.75[/C][C]1[/C][C]0.010526[/C][C]0.905263[/C][C]0.021053[/C][/ROW]
[ROW][C][31,31.5[[/C][C]31.25[/C][C]2[/C][C]0.021053[/C][C]0.926316[/C][C]0.042105[/C][/ROW]
[ROW][C][31.5,32[[/C][C]31.75[/C][C]0[/C][C]0[/C][C]0.926316[/C][C]0[/C][/ROW]
[ROW][C][32,32.5[[/C][C]32.25[/C][C]3[/C][C]0.031579[/C][C]0.957895[/C][C]0.063158[/C][/ROW]
[ROW][C][32.5,33[[/C][C]32.75[/C][C]3[/C][C]0.031579[/C][C]0.989474[/C][C]0.063158[/C][/ROW]
[ROW][C][33,33.5[[/C][C]33.25[/C][C]0[/C][C]0[/C][C]0.989474[/C][C]0[/C][/ROW]
[ROW][C][33.5,34][/C][C]33.75[/C][C]1[/C][C]0.010526[/C][C]1[/C][C]0.021053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121763&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121763&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[9.5,10[9.7520.0210530.0210530.042105
[10,10.5[10.2580.0842110.1052630.168421
[10.5,11[10.75140.1473680.2526320.294737
[11,11.5[11.2530.0315790.2842110.063158
[11.5,12[11.7510.0105260.2947370.021053
[12,12.5[12.25000.2947370
[12.5,13[12.7510.0105260.3052630.021053
[13,13.5[13.2510.0105260.3157890.021053
[13.5,14[13.7510.0105260.3263160.021053
[14,14.5[14.25000.3263160
[14.5,15[14.7540.0421050.3684210.084211
[15,15.5[15.2530.0315790.40.063158
[15.5,16[15.7580.0842110.4842110.168421
[16,16.5[16.2550.0526320.5368420.105263
[16.5,17[16.75000.5368420
[17,17.5[17.2520.0210530.5578950.042105
[17.5,18[17.7520.0210530.5789470.042105
[18,18.5[18.2540.0421050.6210530.084211
[18.5,19[18.7510.0105260.6315790.021053
[19,19.5[19.2530.0315790.6631580.063158
[19.5,20[19.7520.0210530.6842110.042105
[20,20.5[20.2520.0210530.7052630.042105
[20.5,21[20.7510.0105260.7157890.021053
[21,21.5[21.2520.0210530.7368420.042105
[21.5,22[21.7530.0315790.7684210.063158
[22,22.5[22.2510.0105260.7789470.021053
[22.5,23[22.7520.0210530.80.042105
[23,23.5[23.25000.80
[23.5,24[23.7510.0105260.8105260.021053
[24,24.5[24.2510.0105260.8210530.021053
[24.5,25[24.7510.0105260.8315790.021053
[25,25.5[25.2510.0105260.8421050.021053
[25.5,26[25.7510.0105260.8526320.021053
[26,26.5[26.2510.0105260.8631580.021053
[26.5,27[26.75000.8631580
[27,27.5[27.25000.8631580
[27.5,28[27.7510.0105260.8736840.021053
[28,28.5[28.25000.8736840
[28.5,29[28.75000.8736840
[29,29.5[29.25000.8736840
[29.5,30[29.75000.8736840
[30,30.5[30.2520.0210530.8947370.042105
[30.5,31[30.7510.0105260.9052630.021053
[31,31.5[31.2520.0210530.9263160.042105
[31.5,32[31.75000.9263160
[32,32.5[32.2530.0315790.9578950.063158
[32.5,33[32.7530.0315790.9894740.063158
[33,33.5[33.25000.9894740
[33.5,34]33.7510.01052610.021053


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 95 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 95 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
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')
}