Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Sun, 03 Oct 2010 17:03:05 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/03/t1286125392mm5ywmbcsr3k45m.htm/, Retrieved Fri, 03 May 2024 11:40:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=80350, Retrieved Fri, 03 May 2024 11:40:14 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

120

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Histogram] [Bad example of Hi...] [2010-09-25 09:28:23] [b98453cac15ba1066b407e146608df68]
F   PD    [Histogram] [Task 3: Histogram...] [2010-10-03 17:03:05] [dfb0309aec67f282200eef05efe0d5bd] [Current]

Feedback Forum

2010-10-09 09:55:44 [e6db9a09cb3ba986d5f9cc28edcae776] [reply] 
 
Oplossing correct. Niet op aan te merken. 
2010-10-09 10:50:51 [536303b3a93229de4a593d72b4a11cb3] [reply] 
Oplossing is zeker verbeterd. Misschien dat de outliers er nog konden uitgehaald worden door volgende formule x <- x[x<700] in te geven in de R-code.
2010-10-09 10:56:13 [abfc2690eac87da053eb0d612ccdbe5b] [reply] 
De uitschieters zijn er niet allemaal uigehaald. Die kan je opsoren door te kijken naar verschillende klassen. Vanaf klasse [700,720[ zijn er maar weinig frequenties. Enkel [740,760[; [940,960[; [1020,1040[ en [1300,1320[ hebben 1 frequentie, alle klassen daartussen hebben frequentie 0. Daaraan kan je zien dat dat uitschiters zijn, ze komen maar zelden voor. Alle waarden boven de 700 waren dus uitschieters en hadden eruit gemoeten. Daarnaast is de paramater 'number of bins' op 1000 gezet, dat is misschien wat te hoog. Als je die lager maakte tot bv. 30 zijn de balken dikker en wordt het resultaat duidelijker leesbaar.
2010-10-09 10:56:17 [abfc2690eac87da053eb0d612ccdbe5b] [reply] 
De uitschieters zijn er niet allemaal uigehaald. Die kan je opsoren door te kijken naar verschillende klassen. Vanaf klasse [700,720[ zijn er maar weinig frequenties. Enkel [740,760[; [940,960[; [1020,1040[ en [1300,1320[ hebben 1 frequentie, alle klassen daartussen hebben frequentie 0. Daaraan kan je zien dat dat uitschiters zijn, ze komen maar zelden voor. Alle waarden boven de 700 waren dus uitschieters en hadden eruit gemoeten. Daarnaast is de paramater 'number of bins' op 1000 gezet, dat is misschien wat te hoog. Als je die lager maakte tot bv. 30 zijn de balken dikker en wordt het resultaat duidelijker leesbaar.
2010-10-10 18:03:36 [74fe445bf87529db3dd1409469f9e838] [reply] 
Goed werk. Het histogram is nu veel bruikbaarder, door het verhogen van het aantal bins en het wegnemen van (een deel van) de outliers.

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80350&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80350&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[0,20[	10	2	0.014599	0.014599	0.00073
[20,40[	30	3	0.021898	0.036496	0.001095
[40,60[	50	2	0.014599	0.051095	0.00073
[60,80[	70	4	0.029197	0.080292	0.00146
[80,100[	90	2	0.014599	0.094891	0.00073
[100,120[	110	2	0.014599	0.109489	0.00073
[120,140[	130	4	0.029197	0.138686	0.00146
[140,160[	150	4	0.029197	0.167883	0.00146
[160,180[	170	3	0.021898	0.189781	0.001095
[180,200[	190	14	0.10219	0.291971	0.005109
[200,220[	210	16	0.116788	0.408759	0.005839
[220,240[	230	12	0.087591	0.49635	0.00438
[240,260[	250	12	0.087591	0.583942	0.00438
[260,280[	270	10	0.072993	0.656934	0.00365
[280,300[	290	4	0.029197	0.686131	0.00146
[300,320[	310	5	0.036496	0.722628	0.001825
[320,340[	330	2	0.014599	0.737226	0.00073
[340,360[	350	3	0.021898	0.759124	0.001095
[360,380[	370	1	0.007299	0.766423	0.000365
[380,400[	390	6	0.043796	0.810219	0.00219
[400,420[	410	5	0.036496	0.846715	0.001825
[420,440[	430	4	0.029197	0.875912	0.00146
[440,460[	450	3	0.021898	0.89781	0.001095
[460,480[	470	1	0.007299	0.905109	0.000365
[480,500[	490	0	0	0.905109	0
[500,520[	510	1	0.007299	0.912409	0.000365
[520,540[	530	0	0	0.912409	0
[540,560[	550	1	0.007299	0.919708	0.000365
[560,580[	570	0	0	0.919708	0
[580,600[	590	0	0	0.919708	0
[600,620[	610	2	0.014599	0.934307	0.00073
[620,640[	630	0	0	0.934307	0
[640,660[	650	2	0.014599	0.948905	0.00073
[660,680[	670	1	0.007299	0.956204	0.000365
[680,700[	690	2	0.014599	0.970803	0.00073
[700,720[	710	0	0	0.970803	0
[720,740[	730	0	0	0.970803	0
[740,760[	750	1	0.007299	0.978102	0.000365
[760,780[	770	0	0	0.978102	0
[780,800[	790	0	0	0.978102	0
[800,820[	810	0	0	0.978102	0
[820,840[	830	0	0	0.978102	0
[840,860[	850	0	0	0.978102	0
[860,880[	870	0	0	0.978102	0
[880,900[	890	0	0	0.978102	0
[900,920[	910	0	0	0.978102	0
[920,940[	930	0	0	0.978102	0
[940,960[	950	1	0.007299	0.985401	0.000365
[960,980[	970	0	0	0.985401	0
[980,1000[	990	0	0	0.985401	0
[1000,1020[	1010	0	0	0.985401	0
[1020,1040[	1030	1	0.007299	0.992701	0.000365
[1040,1060[	1050	0	0	0.992701	0
[1060,1080[	1070	0	0	0.992701	0
[1080,1100[	1090	0	0	0.992701	0
[1100,1120[	1110	0	0	0.992701	0
[1120,1140[	1130	0	0	0.992701	0
[1140,1160[	1150	0	0	0.992701	0
[1160,1180[	1170	0	0	0.992701	0
[1180,1200[	1190	0	0	0.992701	0
[1200,1220[	1210	0	0	0.992701	0
[1220,1240[	1230	0	0	0.992701	0
[1240,1260[	1250	0	0	0.992701	0
[1260,1280[	1270	0	0	0.992701	0
[1280,1300[	1290	0	0	0.992701	0
[1300,1320]	1310	1	0.007299	1	0.000365

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20[ & 10 & 2 & 0.014599 & 0.014599 & 0.00073 \tabularnewline
[20,40[ & 30 & 3 & 0.021898 & 0.036496 & 0.001095 \tabularnewline
[40,60[ & 50 & 2 & 0.014599 & 0.051095 & 0.00073 \tabularnewline
[60,80[ & 70 & 4 & 0.029197 & 0.080292 & 0.00146 \tabularnewline
[80,100[ & 90 & 2 & 0.014599 & 0.094891 & 0.00073 \tabularnewline
[100,120[ & 110 & 2 & 0.014599 & 0.109489 & 0.00073 \tabularnewline
[120,140[ & 130 & 4 & 0.029197 & 0.138686 & 0.00146 \tabularnewline
[140,160[ & 150 & 4 & 0.029197 & 0.167883 & 0.00146 \tabularnewline
[160,180[ & 170 & 3 & 0.021898 & 0.189781 & 0.001095 \tabularnewline
[180,200[ & 190 & 14 & 0.10219 & 0.291971 & 0.005109 \tabularnewline
[200,220[ & 210 & 16 & 0.116788 & 0.408759 & 0.005839 \tabularnewline
[220,240[ & 230 & 12 & 0.087591 & 0.49635 & 0.00438 \tabularnewline
[240,260[ & 250 & 12 & 0.087591 & 0.583942 & 0.00438 \tabularnewline
[260,280[ & 270 & 10 & 0.072993 & 0.656934 & 0.00365 \tabularnewline
[280,300[ & 290 & 4 & 0.029197 & 0.686131 & 0.00146 \tabularnewline
[300,320[ & 310 & 5 & 0.036496 & 0.722628 & 0.001825 \tabularnewline
[320,340[ & 330 & 2 & 0.014599 & 0.737226 & 0.00073 \tabularnewline
[340,360[ & 350 & 3 & 0.021898 & 0.759124 & 0.001095 \tabularnewline
[360,380[ & 370 & 1 & 0.007299 & 0.766423 & 0.000365 \tabularnewline
[380,400[ & 390 & 6 & 0.043796 & 0.810219 & 0.00219 \tabularnewline
[400,420[ & 410 & 5 & 0.036496 & 0.846715 & 0.001825 \tabularnewline
[420,440[ & 430 & 4 & 0.029197 & 0.875912 & 0.00146 \tabularnewline
[440,460[ & 450 & 3 & 0.021898 & 0.89781 & 0.001095 \tabularnewline
[460,480[ & 470 & 1 & 0.007299 & 0.905109 & 0.000365 \tabularnewline
[480,500[ & 490 & 0 & 0 & 0.905109 & 0 \tabularnewline
[500,520[ & 510 & 1 & 0.007299 & 0.912409 & 0.000365 \tabularnewline
[520,540[ & 530 & 0 & 0 & 0.912409 & 0 \tabularnewline
[540,560[ & 550 & 1 & 0.007299 & 0.919708 & 0.000365 \tabularnewline
[560,580[ & 570 & 0 & 0 & 0.919708 & 0 \tabularnewline
[580,600[ & 590 & 0 & 0 & 0.919708 & 0 \tabularnewline
[600,620[ & 610 & 2 & 0.014599 & 0.934307 & 0.00073 \tabularnewline
[620,640[ & 630 & 0 & 0 & 0.934307 & 0 \tabularnewline
[640,660[ & 650 & 2 & 0.014599 & 0.948905 & 0.00073 \tabularnewline
[660,680[ & 670 & 1 & 0.007299 & 0.956204 & 0.000365 \tabularnewline
[680,700[ & 690 & 2 & 0.014599 & 0.970803 & 0.00073 \tabularnewline
[700,720[ & 710 & 0 & 0 & 0.970803 & 0 \tabularnewline
[720,740[ & 730 & 0 & 0 & 0.970803 & 0 \tabularnewline
[740,760[ & 750 & 1 & 0.007299 & 0.978102 & 0.000365 \tabularnewline
[760,780[ & 770 & 0 & 0 & 0.978102 & 0 \tabularnewline
[780,800[ & 790 & 0 & 0 & 0.978102 & 0 \tabularnewline
[800,820[ & 810 & 0 & 0 & 0.978102 & 0 \tabularnewline
[820,840[ & 830 & 0 & 0 & 0.978102 & 0 \tabularnewline
[840,860[ & 850 & 0 & 0 & 0.978102 & 0 \tabularnewline
[860,880[ & 870 & 0 & 0 & 0.978102 & 0 \tabularnewline
[880,900[ & 890 & 0 & 0 & 0.978102 & 0 \tabularnewline
[900,920[ & 910 & 0 & 0 & 0.978102 & 0 \tabularnewline
[920,940[ & 930 & 0 & 0 & 0.978102 & 0 \tabularnewline
[940,960[ & 950 & 1 & 0.007299 & 0.985401 & 0.000365 \tabularnewline
[960,980[ & 970 & 0 & 0 & 0.985401 & 0 \tabularnewline
[980,1000[ & 990 & 0 & 0 & 0.985401 & 0 \tabularnewline
[1000,1020[ & 1010 & 0 & 0 & 0.985401 & 0 \tabularnewline
[1020,1040[ & 1030 & 1 & 0.007299 & 0.992701 & 0.000365 \tabularnewline
[1040,1060[ & 1050 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1060,1080[ & 1070 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1080,1100[ & 1090 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1100,1120[ & 1110 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1120,1140[ & 1130 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1140,1160[ & 1150 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1160,1180[ & 1170 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1180,1200[ & 1190 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1200,1220[ & 1210 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1220,1240[ & 1230 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1240,1260[ & 1250 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1260,1280[ & 1270 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1280,1300[ & 1290 & 0 & 0 & 0.992701 & 0 \tabularnewline
[1300,1320] & 1310 & 1 & 0.007299 & 1 & 0.000365 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=80350&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][0,20[[/C][C]10[/C][C]2[/C][C]0.014599[/C][C]0.014599[/C][C]0.00073[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]3[/C][C]0.021898[/C][C]0.036496[/C][C]0.001095[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]2[/C][C]0.014599[/C][C]0.051095[/C][C]0.00073[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]4[/C][C]0.029197[/C][C]0.080292[/C][C]0.00146[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]2[/C][C]0.014599[/C][C]0.094891[/C][C]0.00073[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]2[/C][C]0.014599[/C][C]0.109489[/C][C]0.00073[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]4[/C][C]0.029197[/C][C]0.138686[/C][C]0.00146[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]4[/C][C]0.029197[/C][C]0.167883[/C][C]0.00146[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]3[/C][C]0.021898[/C][C]0.189781[/C][C]0.001095[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]14[/C][C]0.10219[/C][C]0.291971[/C][C]0.005109[/C][/ROW]
[ROW][C][200,220[[/C][C]210[/C][C]16[/C][C]0.116788[/C][C]0.408759[/C][C]0.005839[/C][/ROW]
[ROW][C][220,240[[/C][C]230[/C][C]12[/C][C]0.087591[/C][C]0.49635[/C][C]0.00438[/C][/ROW]
[ROW][C][240,260[[/C][C]250[/C][C]12[/C][C]0.087591[/C][C]0.583942[/C][C]0.00438[/C][/ROW]
[ROW][C][260,280[[/C][C]270[/C][C]10[/C][C]0.072993[/C][C]0.656934[/C][C]0.00365[/C][/ROW]
[ROW][C][280,300[[/C][C]290[/C][C]4[/C][C]0.029197[/C][C]0.686131[/C][C]0.00146[/C][/ROW]
[ROW][C][300,320[[/C][C]310[/C][C]5[/C][C]0.036496[/C][C]0.722628[/C][C]0.001825[/C][/ROW]
[ROW][C][320,340[[/C][C]330[/C][C]2[/C][C]0.014599[/C][C]0.737226[/C][C]0.00073[/C][/ROW]
[ROW][C][340,360[[/C][C]350[/C][C]3[/C][C]0.021898[/C][C]0.759124[/C][C]0.001095[/C][/ROW]
[ROW][C][360,380[[/C][C]370[/C][C]1[/C][C]0.007299[/C][C]0.766423[/C][C]0.000365[/C][/ROW]
[ROW][C][380,400[[/C][C]390[/C][C]6[/C][C]0.043796[/C][C]0.810219[/C][C]0.00219[/C][/ROW]
[ROW][C][400,420[[/C][C]410[/C][C]5[/C][C]0.036496[/C][C]0.846715[/C][C]0.001825[/C][/ROW]
[ROW][C][420,440[[/C][C]430[/C][C]4[/C][C]0.029197[/C][C]0.875912[/C][C]0.00146[/C][/ROW]
[ROW][C][440,460[[/C][C]450[/C][C]3[/C][C]0.021898[/C][C]0.89781[/C][C]0.001095[/C][/ROW]
[ROW][C][460,480[[/C][C]470[/C][C]1[/C][C]0.007299[/C][C]0.905109[/C][C]0.000365[/C][/ROW]
[ROW][C][480,500[[/C][C]490[/C][C]0[/C][C]0[/C][C]0.905109[/C][C]0[/C][/ROW]
[ROW][C][500,520[[/C][C]510[/C][C]1[/C][C]0.007299[/C][C]0.912409[/C][C]0.000365[/C][/ROW]
[ROW][C][520,540[[/C][C]530[/C][C]0[/C][C]0[/C][C]0.912409[/C][C]0[/C][/ROW]
[ROW][C][540,560[[/C][C]550[/C][C]1[/C][C]0.007299[/C][C]0.919708[/C][C]0.000365[/C][/ROW]
[ROW][C][560,580[[/C][C]570[/C][C]0[/C][C]0[/C][C]0.919708[/C][C]0[/C][/ROW]
[ROW][C][580,600[[/C][C]590[/C][C]0[/C][C]0[/C][C]0.919708[/C][C]0[/C][/ROW]
[ROW][C][600,620[[/C][C]610[/C][C]2[/C][C]0.014599[/C][C]0.934307[/C][C]0.00073[/C][/ROW]
[ROW][C][620,640[[/C][C]630[/C][C]0[/C][C]0[/C][C]0.934307[/C][C]0[/C][/ROW]
[ROW][C][640,660[[/C][C]650[/C][C]2[/C][C]0.014599[/C][C]0.948905[/C][C]0.00073[/C][/ROW]
[ROW][C][660,680[[/C][C]670[/C][C]1[/C][C]0.007299[/C][C]0.956204[/C][C]0.000365[/C][/ROW]
[ROW][C][680,700[[/C][C]690[/C][C]2[/C][C]0.014599[/C][C]0.970803[/C][C]0.00073[/C][/ROW]
[ROW][C][700,720[[/C][C]710[/C][C]0[/C][C]0[/C][C]0.970803[/C][C]0[/C][/ROW]
[ROW][C][720,740[[/C][C]730[/C][C]0[/C][C]0[/C][C]0.970803[/C][C]0[/C][/ROW]
[ROW][C][740,760[[/C][C]750[/C][C]1[/C][C]0.007299[/C][C]0.978102[/C][C]0.000365[/C][/ROW]
[ROW][C][760,780[[/C][C]770[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][780,800[[/C][C]790[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][800,820[[/C][C]810[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][820,840[[/C][C]830[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][840,860[[/C][C]850[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][860,880[[/C][C]870[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][880,900[[/C][C]890[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][900,920[[/C][C]910[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][920,940[[/C][C]930[/C][C]0[/C][C]0[/C][C]0.978102[/C][C]0[/C][/ROW]
[ROW][C][940,960[[/C][C]950[/C][C]1[/C][C]0.007299[/C][C]0.985401[/C][C]0.000365[/C][/ROW]
[ROW][C][960,980[[/C][C]970[/C][C]0[/C][C]0[/C][C]0.985401[/C][C]0[/C][/ROW]
[ROW][C][980,1000[[/C][C]990[/C][C]0[/C][C]0[/C][C]0.985401[/C][C]0[/C][/ROW]
[ROW][C][1000,1020[[/C][C]1010[/C][C]0[/C][C]0[/C][C]0.985401[/C][C]0[/C][/ROW]
[ROW][C][1020,1040[[/C][C]1030[/C][C]1[/C][C]0.007299[/C][C]0.992701[/C][C]0.000365[/C][/ROW]
[ROW][C][1040,1060[[/C][C]1050[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1060,1080[[/C][C]1070[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1080,1100[[/C][C]1090[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1100,1120[[/C][C]1110[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1120,1140[[/C][C]1130[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1140,1160[[/C][C]1150[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1160,1180[[/C][C]1170[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1180,1200[[/C][C]1190[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1200,1220[[/C][C]1210[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1220,1240[[/C][C]1230[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1240,1260[[/C][C]1250[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1260,1280[[/C][C]1270[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1280,1300[[/C][C]1290[/C][C]0[/C][C]0[/C][C]0.992701[/C][C]0[/C][/ROW]
[ROW][C][1300,1320][/C][C]1310[/C][C]1[/C][C]0.007299[/C][C]1[/C][C]0.000365[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=80350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=80350&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)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[0,20[	10	2	0.014599	0.014599	0.00073
[20,40[	30	3	0.021898	0.036496	0.001095
[40,60[	50	2	0.014599	0.051095	0.00073
[60,80[	70	4	0.029197	0.080292	0.00146
[80,100[	90	2	0.014599	0.094891	0.00073
[100,120[	110	2	0.014599	0.109489	0.00073
[120,140[	130	4	0.029197	0.138686	0.00146
[140,160[	150	4	0.029197	0.167883	0.00146
[160,180[	170	3	0.021898	0.189781	0.001095
[180,200[	190	14	0.10219	0.291971	0.005109
[200,220[	210	16	0.116788	0.408759	0.005839
[220,240[	230	12	0.087591	0.49635	0.00438
[240,260[	250	12	0.087591	0.583942	0.00438
[260,280[	270	10	0.072993	0.656934	0.00365
[280,300[	290	4	0.029197	0.686131	0.00146
[300,320[	310	5	0.036496	0.722628	0.001825
[320,340[	330	2	0.014599	0.737226	0.00073
[340,360[	350	3	0.021898	0.759124	0.001095
[360,380[	370	1	0.007299	0.766423	0.000365
[380,400[	390	6	0.043796	0.810219	0.00219
[400,420[	410	5	0.036496	0.846715	0.001825
[420,440[	430	4	0.029197	0.875912	0.00146
[440,460[	450	3	0.021898	0.89781	0.001095
[460,480[	470	1	0.007299	0.905109	0.000365
[480,500[	490	0	0	0.905109	0
[500,520[	510	1	0.007299	0.912409	0.000365
[520,540[	530	0	0	0.912409	0
[540,560[	550	1	0.007299	0.919708	0.000365
[560,580[	570	0	0	0.919708	0
[580,600[	590	0	0	0.919708	0
[600,620[	610	2	0.014599	0.934307	0.00073
[620,640[	630	0	0	0.934307	0
[640,660[	650	2	0.014599	0.948905	0.00073
[660,680[	670	1	0.007299	0.956204	0.000365
[680,700[	690	2	0.014599	0.970803	0.00073
[700,720[	710	0	0	0.970803	0
[720,740[	730	0	0	0.970803	0
[740,760[	750	1	0.007299	0.978102	0.000365
[760,780[	770	0	0	0.978102	0
[780,800[	790	0	0	0.978102	0
[800,820[	810	0	0	0.978102	0
[820,840[	830	0	0	0.978102	0
[840,860[	850	0	0	0.978102	0
[860,880[	870	0	0	0.978102	0
[880,900[	890	0	0	0.978102	0
[900,920[	910	0	0	0.978102	0
[920,940[	930	0	0	0.978102	0
[940,960[	950	1	0.007299	0.985401	0.000365
[960,980[	970	0	0	0.985401	0
[980,1000[	990	0	0	0.985401	0
[1000,1020[	1010	0	0	0.985401	0
[1020,1040[	1030	1	0.007299	0.992701	0.000365
[1040,1060[	1050	0	0	0.992701	0
[1060,1080[	1070	0	0	0.992701	0
[1080,1100[	1090	0	0	0.992701	0
[1100,1120[	1110	0	0	0.992701	0
[1120,1140[	1130	0	0	0.992701	0
[1140,1160[	1150	0	0	0.992701	0
[1160,1180[	1170	0	0	0.992701	0
[1180,1200[	1190	0	0	0.992701	0
[1200,1220[	1210	0	0	0.992701	0
[1220,1240[	1230	0	0	0.992701	0
[1240,1260[	1250	0	0	0.992701	0
[1260,1280[	1270	0	0	0.992701	0
[1280,1300[	1290	0	0	0.992701	0
[1300,1320]	1310	1	0.007299	1	0.000365

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par2 = blue ; par3 = FALSE ; par4 = Unknown ;

Parameters (R input):

par1 = 1000 ; 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code