Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 23 Feb 2016 23:53:20 +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/2016/Feb/23/t14562716121j9hamv3now9weu.htm/, Retrieved Sun, 05 May 2024 23:13:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292603, Retrieved Sun, 05 May 2024 23:13:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2016-02-23 23:53:20] [e2ca982fef5d38be90899c2ec1ea6fcf] [Current]
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Dataseries X:
250785	
250140	
255755	
254671	
253919	
253741	
252729	
253810	
256653	
255231	
258405	
251061	
254811	
254895	
258325
257608	
258759	
258621	
257852	
260560	
262358	
260812	
261165	
257164	
260720	
259581	
264743	
261845	
262262	
261631	
258953	
259966	
262850	
262204	
263418	
262752	
266433	
267722	
266003	
262971	
265521	
264676	
270223	
269508	
268457	
265814	
266680	
263018	
269285	
269829	
270911	
266844	
271244	
269907	
271296	
270157	
271322	
267179	
264101	
265518	
269419	
268714	
272482	
268351	
268175	
270674	
272764	
272599	
270333	
270846	
270491	
269160	
274027	
273784	
276663	
274525	
271344	
271115	
270798	
273911	
273985	
271917	
273338	
270601	
273547	
275363	
281229	
277793	
279913	
282500	
280041	
282166	
290304	
283519	
287816	
285226	
287595	
289741	
289148	
288301	
290155	
289648	
288225	
289351	
294735	
305333	
309030	
310215	
321935	
325734	
320846	
323023	
319753	
321753	
320757	
324479	
324641	
322767	
324181	
321389	
327897	
334287	
332653	
334819	
335264	
339622	
342440	
346585	
335378	
337010	
339130	
341193	
343507	
348915	
346431	
348322	
348288	
346597	
351076	
355215	
350562	
355266	
361565	
363462	
366183	
365423	
369208	
366713	
369354	
371970	
371824	
373187	
367270	
368140	
373742	
364815	
368558	
371503	
372611	
370197	
375441	
375888	
375132	
381142	
372024	
376070	
376864	
371401	
375687	
384304	
380738	
379908	
384007	
384499	
385106	
387935	
380435	
379281	
384153	
380599




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292603&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292603&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292603&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[250000,260000[255000230.1277780.1277781.3e-05
[260000,270000[265000360.20.3277782e-05
[270000,280000[275000290.1611110.4888891.6e-05
[280000,290000[285000140.0777780.5666678e-06
[290000,3e+05[29500030.0166670.5833332e-06
[3e+05,310000[30500020.0111110.5944441e-06
[310000,320000[31500020.0111110.6055561e-06
[320000,330000[325000120.0666670.6722227e-06
[330000,340000[33500080.0444440.7166674e-06
[340000,350000[34500090.050.7666675e-06
[350000,360000[35500040.0222220.7888892e-06
[360000,370000[365000110.0611110.856e-06
[370000,380000[375000170.0944440.9444449e-06
[380000,390000]385000100.05555616e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[250000,260000[ & 255000 & 23 & 0.127778 & 0.127778 & 1.3e-05 \tabularnewline
[260000,270000[ & 265000 & 36 & 0.2 & 0.327778 & 2e-05 \tabularnewline
[270000,280000[ & 275000 & 29 & 0.161111 & 0.488889 & 1.6e-05 \tabularnewline
[280000,290000[ & 285000 & 14 & 0.077778 & 0.566667 & 8e-06 \tabularnewline
[290000,3e+05[ & 295000 & 3 & 0.016667 & 0.583333 & 2e-06 \tabularnewline
[3e+05,310000[ & 305000 & 2 & 0.011111 & 0.594444 & 1e-06 \tabularnewline
[310000,320000[ & 315000 & 2 & 0.011111 & 0.605556 & 1e-06 \tabularnewline
[320000,330000[ & 325000 & 12 & 0.066667 & 0.672222 & 7e-06 \tabularnewline
[330000,340000[ & 335000 & 8 & 0.044444 & 0.716667 & 4e-06 \tabularnewline
[340000,350000[ & 345000 & 9 & 0.05 & 0.766667 & 5e-06 \tabularnewline
[350000,360000[ & 355000 & 4 & 0.022222 & 0.788889 & 2e-06 \tabularnewline
[360000,370000[ & 365000 & 11 & 0.061111 & 0.85 & 6e-06 \tabularnewline
[370000,380000[ & 375000 & 17 & 0.094444 & 0.944444 & 9e-06 \tabularnewline
[380000,390000] & 385000 & 10 & 0.055556 & 1 & 6e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292603&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][250000,260000[[/C][C]255000[/C][C]23[/C][C]0.127778[/C][C]0.127778[/C][C]1.3e-05[/C][/ROW]
[ROW][C][260000,270000[[/C][C]265000[/C][C]36[/C][C]0.2[/C][C]0.327778[/C][C]2e-05[/C][/ROW]
[ROW][C][270000,280000[[/C][C]275000[/C][C]29[/C][C]0.161111[/C][C]0.488889[/C][C]1.6e-05[/C][/ROW]
[ROW][C][280000,290000[[/C][C]285000[/C][C]14[/C][C]0.077778[/C][C]0.566667[/C][C]8e-06[/C][/ROW]
[ROW][C][290000,3e+05[[/C][C]295000[/C][C]3[/C][C]0.016667[/C][C]0.583333[/C][C]2e-06[/C][/ROW]
[ROW][C][3e+05,310000[[/C][C]305000[/C][C]2[/C][C]0.011111[/C][C]0.594444[/C][C]1e-06[/C][/ROW]
[ROW][C][310000,320000[[/C][C]315000[/C][C]2[/C][C]0.011111[/C][C]0.605556[/C][C]1e-06[/C][/ROW]
[ROW][C][320000,330000[[/C][C]325000[/C][C]12[/C][C]0.066667[/C][C]0.672222[/C][C]7e-06[/C][/ROW]
[ROW][C][330000,340000[[/C][C]335000[/C][C]8[/C][C]0.044444[/C][C]0.716667[/C][C]4e-06[/C][/ROW]
[ROW][C][340000,350000[[/C][C]345000[/C][C]9[/C][C]0.05[/C][C]0.766667[/C][C]5e-06[/C][/ROW]
[ROW][C][350000,360000[[/C][C]355000[/C][C]4[/C][C]0.022222[/C][C]0.788889[/C][C]2e-06[/C][/ROW]
[ROW][C][360000,370000[[/C][C]365000[/C][C]11[/C][C]0.061111[/C][C]0.85[/C][C]6e-06[/C][/ROW]
[ROW][C][370000,380000[[/C][C]375000[/C][C]17[/C][C]0.094444[/C][C]0.944444[/C][C]9e-06[/C][/ROW]
[ROW][C][380000,390000][/C][C]385000[/C][C]10[/C][C]0.055556[/C][C]1[/C][C]6e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292603&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292603&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
[250000,260000[255000230.1277780.1277781.3e-05
[260000,270000[265000360.20.3277782e-05
[270000,280000[275000290.1611110.4888891.6e-05
[280000,290000[285000140.0777780.5666678e-06
[290000,3e+05[29500030.0166670.5833332e-06
[3e+05,310000[30500020.0111110.5944441e-06
[310000,320000[31500020.0111110.6055561e-06
[320000,330000[325000120.0666670.6722227e-06
[330000,340000[33500080.0444440.7166674e-06
[340000,350000[34500090.050.7666675e-06
[350000,360000[35500040.0222220.7888892e-06
[360000,370000[365000110.0611110.856e-06
[370000,380000[375000170.0944440.9444449e-06
[380000,390000]385000100.05555616e-06



Parameters (Session):
par1 = 15 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 15 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '4'
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 {
barplot(mytab <- sort(table(x),T),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')
}