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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 10 Nov 2012 05:30:01 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/10/t1352543445cnge4xmkecl6wrp.htm/, Retrieved Sat, 10 Dec 2022 06:24:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187280, Retrieved Sat, 10 Dec 2022 06:24:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-19 12:03:37] [74be16979710d4c4e7c6647856088456]
- RMPD    [Histogram] [Tutorial Assignme...] [2012-11-10 10:30:01] [66a849a05d67389f0588cabd76580e84] [Current]
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Dataseries X:
255
280.2
299.9
339.2
374.2
393.5
389.2
381.7
375.2
369
357.4
352.1
346.5
342.9
340.3
328.3
322.9
314.3
308.9
294
285.6
281.2
280.3
278.8
274.5
270.4
263.4
259.9
258
262.7
284.7
311.3
322.1
327
331.3
333.3
321.4
327
320
314.7
316.7
314.4
321.3
318.2
307.2
301.3
287.5
277.7
274.4
258.8
253.3
251
248.4
249.5
246.1
244.5
243.6
244
240.8
249.8
248
259.4
260.5
260.8
261.3
259.5
256.6
257.9
256.5
254.2
253.3
253.8
255.5
257.1
257.3
253.2
252.8
252
250.7
252.2
250
251
253.4
251.2
255.6
261.1
258.9
259.9
261.2
264.7
267.1
266.4
267.7
268.6
267.5
268.5
268.5
270.5
270.9
270.1
269.3
269.8
270.1
264.9
263.7
264.8
263.7
255.9
276.2
360.1
380.5
373.7
369.8
366.6
359.3
345.8
326.2
324.5
328.1
327.5
324.4
316.5
310.9
301.5
291.7
290.4
287.4
277.7
281.6
288
276
272.9
283
283.3
276.8
284.5
282.7
281.2
287.4
283.1
284
285.5
289.2
292.5
296.4
305.2
303.9
311.5
316.3
316.7
322.5
317.1
309.8
303.8
290.3
293.7
291.7
296.5
289.1
288.5
293.8
297.7
305.4
302.7
302.5
303
294.5
294.1
294.5
297.1
289.4
292.4
287.9
286.6
280.5
272.4
269.2
270.6
267.3
262.5
266.8
268.8
263.1
261.2
266
262.5
265.2
261.3
253.7
249.2
239.1
236.4
235.2
245.2
246.2
247.7
251.4
253.3
254.8
250
249.3
241.5
243.3
248
253
252.9
251.5
251.6
253.5
259.8
334.1
448
445.8
445
448.2
438.2
439.8
423.4
410.8
408.4
406.7
405.9
402.7
405.1
399.6
386.5
381.4
375.2
357.7
359
355
352.7
344.4
343.8
338
339
333.3
334.4
328.3
330.7
330
331.6
351.2
389.4
410.9
442.8
462.8
466.9
461.7
439.2
430.3
416.1
402.5
397.3
403.3
395.9
387.8
378.6
377.1
370.4
362
350.3
348.2
344.6
343.5
342.8
347.6
346.6
349.5
342.1
342
342.8
339.3
348.2
333.7
334.7
354
367.7
363.3
358.4
353.1
343.1
344.6
344.4
333.9
331.7
324.3
321.2
322.4
321.7
320.5
312.8
309.7
315.6
309.7
304.6
302.5
301.5
298.8
291.3
293.6
294.6
285.9
297.6
301.1
293.8
297.7
292.9
292.1
287.2
288.2
283.8
299.9
292.4
293.3
300.8
293.7
293.1
294.4
292.1
291.9
282.5
277.9
287.5
289.2
285.6
293.2
290.8
283.1
275
287.8
287.8
287.4
284
277.8
277.6
304.9
294
300.9
324
332.9
341.6
333.4
348.2
344.7
344.7
329.3
323.5
323.2
317.4
330.1
329.2
334.9
315.8
315.4
319.6
317.3
313.8
315.8
311.3




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' @ yule.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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187280&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187280&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187280&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' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[220,240[23030.0083330.0083330.000417
[240,260[250580.1611110.1694440.008056
[260,280[270520.1444440.3138890.007222
[280,300[290750.2083330.5222220.010417
[300,320[310430.1194440.6416670.005972
[320,340[330450.1250.7666670.00625
[340,360[350360.10.8666670.005
[360,380[370140.0388890.9055560.001944
[380,400[390110.0305560.9361110.001528
[400,420[410100.0277780.9638890.001389
[420,440[43050.0138890.9777780.000694
[440,460[45050.0138890.9916670.000694
[460,480]47030.00833310.000417

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[220,240[ & 230 & 3 & 0.008333 & 0.008333 & 0.000417 \tabularnewline
[240,260[ & 250 & 58 & 0.161111 & 0.169444 & 0.008056 \tabularnewline
[260,280[ & 270 & 52 & 0.144444 & 0.313889 & 0.007222 \tabularnewline
[280,300[ & 290 & 75 & 0.208333 & 0.522222 & 0.010417 \tabularnewline
[300,320[ & 310 & 43 & 0.119444 & 0.641667 & 0.005972 \tabularnewline
[320,340[ & 330 & 45 & 0.125 & 0.766667 & 0.00625 \tabularnewline
[340,360[ & 350 & 36 & 0.1 & 0.866667 & 0.005 \tabularnewline
[360,380[ & 370 & 14 & 0.038889 & 0.905556 & 0.001944 \tabularnewline
[380,400[ & 390 & 11 & 0.030556 & 0.936111 & 0.001528 \tabularnewline
[400,420[ & 410 & 10 & 0.027778 & 0.963889 & 0.001389 \tabularnewline
[420,440[ & 430 & 5 & 0.013889 & 0.977778 & 0.000694 \tabularnewline
[440,460[ & 450 & 5 & 0.013889 & 0.991667 & 0.000694 \tabularnewline
[460,480] & 470 & 3 & 0.008333 & 1 & 0.000417 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187280&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][220,240[[/C][C]230[/C][C]3[/C][C]0.008333[/C][C]0.008333[/C][C]0.000417[/C][/ROW]
[ROW][C][240,260[[/C][C]250[/C][C]58[/C][C]0.161111[/C][C]0.169444[/C][C]0.008056[/C][/ROW]
[ROW][C][260,280[[/C][C]270[/C][C]52[/C][C]0.144444[/C][C]0.313889[/C][C]0.007222[/C][/ROW]
[ROW][C][280,300[[/C][C]290[/C][C]75[/C][C]0.208333[/C][C]0.522222[/C][C]0.010417[/C][/ROW]
[ROW][C][300,320[[/C][C]310[/C][C]43[/C][C]0.119444[/C][C]0.641667[/C][C]0.005972[/C][/ROW]
[ROW][C][320,340[[/C][C]330[/C][C]45[/C][C]0.125[/C][C]0.766667[/C][C]0.00625[/C][/ROW]
[ROW][C][340,360[[/C][C]350[/C][C]36[/C][C]0.1[/C][C]0.866667[/C][C]0.005[/C][/ROW]
[ROW][C][360,380[[/C][C]370[/C][C]14[/C][C]0.038889[/C][C]0.905556[/C][C]0.001944[/C][/ROW]
[ROW][C][380,400[[/C][C]390[/C][C]11[/C][C]0.030556[/C][C]0.936111[/C][C]0.001528[/C][/ROW]
[ROW][C][400,420[[/C][C]410[/C][C]10[/C][C]0.027778[/C][C]0.963889[/C][C]0.001389[/C][/ROW]
[ROW][C][420,440[[/C][C]430[/C][C]5[/C][C]0.013889[/C][C]0.977778[/C][C]0.000694[/C][/ROW]
[ROW][C][440,460[[/C][C]450[/C][C]5[/C][C]0.013889[/C][C]0.991667[/C][C]0.000694[/C][/ROW]
[ROW][C][460,480][/C][C]470[/C][C]3[/C][C]0.008333[/C][C]1[/C][C]0.000417[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187280&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187280&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
[220,240[23030.0083330.0083330.000417
[240,260[250580.1611110.1694440.008056
[260,280[270520.1444440.3138890.007222
[280,300[290750.2083330.5222220.010417
[300,320[310430.1194440.6416670.005972
[320,340[330450.1250.7666670.00625
[340,360[350360.10.8666670.005
[360,380[370140.0388890.9055560.001944
[380,400[390110.0305560.9361110.001528
[400,420[410100.0277780.9638890.001389
[420,440[43050.0138890.9777780.000694
[440,460[45050.0138890.9916670.000694
[460,480]47030.00833310.000417



Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; 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')
}