Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 23 Jul 2017 16:10:48 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jul/23/t1500819106o2i17b6h34bbyr2.htm/, Retrieved Tue, 14 May 2024 12:44:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306737, Retrieved Tue, 14 May 2024 12:44:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2017-07-23 14:10:48] [1a8cec710a8245ea2c14b5d40c333c7c] [Current]
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Dataseries X:
247832.00
246909.00
245973.00
244036.00
263198.00
262184.00
247832.00
238290.00
239213.00
239213.00
240240.00
242086.00
244959.00
244959.00
243113.00
238290.00
263198.00
266994.00
261261.00
247832.00
253578.00
244959.00
248846.00
250705.00
252642.00
247832.00
248846.00
242086.00
263198.00
269867.00
264134.00
253578.00
265057.00
252642.00
264134.00
263198.00
266071.00
255515.00
266994.00
266071.00
283296.00
279409.00
264134.00
256438.00
266994.00
252642.00
263198.00
265057.00
268944.00
260338.00
265057.00
267930.00
278486.00
269867.00
258388.00
245973.00
257465.00
225875.00
241163.00
249769.00
258388.00
245973.00
245973.00
245973.00
252642.00
243113.00
230607.00
220142.00
227734.00
198094.00
216255.00
226811.00
228748.00
218192.00
219115.00
216255.00
225875.00
219115.00
205790.00
196157.00
212446.00
177073.00
200044.00
210509.00
210509.00
198094.00
186615.00
185692.00
196157.00
186615.00
168467.00
155961.00
169390.00
137813.00
166517.00
181792.00
186615.00
176059.00
162721.00
172263.00
176059.00
173186.00
144469.00
131144.00
140673.00
111969.00
141609.00
152165.00
160771.00
146419.00
132990.00
140673.00
144469.00
136877.00
108173.00
95667.00
107146.00
75569.00
110019.00
131144.00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306737&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306737&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306737&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 Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[70000,80000[7500010.0083330.0083331e-06
[80000,90000[85000000.0083330
[90000,100000[9500010.0083330.0166671e-06
[100000,110000[10500020.0166670.0333332e-06
[110000,120000[11500020.0166670.052e-06
[120000,130000[125000000.050
[130000,140000[13500050.0416670.0916674e-06
[140000,150000[14500060.050.1416675e-06
[150000,160000[15500020.0166670.1583332e-06
[160000,170000[16500050.0416670.24e-06
[170000,180000[17500050.0416670.2416674e-06
[180000,190000[18500050.0416670.2833334e-06
[190000,200000[19500040.0333330.3166673e-06
[200000,210000[20500020.0166670.3333332e-06
[210000,220000[21500080.0666670.47e-06
[220000,230000[22500060.050.455e-06
[230000,240000[23500050.0416670.4916674e-06
[240000,250000[245000230.1916670.6833331.9e-05
[250000,260000[255000120.10.7833331e-05
[260000,270000[265000230.1916670.9751.9e-05
[270000,280000[27500020.0166670.9916672e-06
[280000,290000]28500010.00833311e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[70000,80000[ & 75000 & 1 & 0.008333 & 0.008333 & 1e-06 \tabularnewline
[80000,90000[ & 85000 & 0 & 0 & 0.008333 & 0 \tabularnewline
[90000,100000[ & 95000 & 1 & 0.008333 & 0.016667 & 1e-06 \tabularnewline
[100000,110000[ & 105000 & 2 & 0.016667 & 0.033333 & 2e-06 \tabularnewline
[110000,120000[ & 115000 & 2 & 0.016667 & 0.05 & 2e-06 \tabularnewline
[120000,130000[ & 125000 & 0 & 0 & 0.05 & 0 \tabularnewline
[130000,140000[ & 135000 & 5 & 0.041667 & 0.091667 & 4e-06 \tabularnewline
[140000,150000[ & 145000 & 6 & 0.05 & 0.141667 & 5e-06 \tabularnewline
[150000,160000[ & 155000 & 2 & 0.016667 & 0.158333 & 2e-06 \tabularnewline
[160000,170000[ & 165000 & 5 & 0.041667 & 0.2 & 4e-06 \tabularnewline
[170000,180000[ & 175000 & 5 & 0.041667 & 0.241667 & 4e-06 \tabularnewline
[180000,190000[ & 185000 & 5 & 0.041667 & 0.283333 & 4e-06 \tabularnewline
[190000,200000[ & 195000 & 4 & 0.033333 & 0.316667 & 3e-06 \tabularnewline
[200000,210000[ & 205000 & 2 & 0.016667 & 0.333333 & 2e-06 \tabularnewline
[210000,220000[ & 215000 & 8 & 0.066667 & 0.4 & 7e-06 \tabularnewline
[220000,230000[ & 225000 & 6 & 0.05 & 0.45 & 5e-06 \tabularnewline
[230000,240000[ & 235000 & 5 & 0.041667 & 0.491667 & 4e-06 \tabularnewline
[240000,250000[ & 245000 & 23 & 0.191667 & 0.683333 & 1.9e-05 \tabularnewline
[250000,260000[ & 255000 & 12 & 0.1 & 0.783333 & 1e-05 \tabularnewline
[260000,270000[ & 265000 & 23 & 0.191667 & 0.975 & 1.9e-05 \tabularnewline
[270000,280000[ & 275000 & 2 & 0.016667 & 0.991667 & 2e-06 \tabularnewline
[280000,290000] & 285000 & 1 & 0.008333 & 1 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306737&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][70000,80000[[/C][C]75000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]1e-06[/C][/ROW]
[ROW][C][80000,90000[[/C][C]85000[/C][C]0[/C][C]0[/C][C]0.008333[/C][C]0[/C][/ROW]
[ROW][C][90000,100000[[/C][C]95000[/C][C]1[/C][C]0.008333[/C][C]0.016667[/C][C]1e-06[/C][/ROW]
[ROW][C][100000,110000[[/C][C]105000[/C][C]2[/C][C]0.016667[/C][C]0.033333[/C][C]2e-06[/C][/ROW]
[ROW][C][110000,120000[[/C][C]115000[/C][C]2[/C][C]0.016667[/C][C]0.05[/C][C]2e-06[/C][/ROW]
[ROW][C][120000,130000[[/C][C]125000[/C][C]0[/C][C]0[/C][C]0.05[/C][C]0[/C][/ROW]
[ROW][C][130000,140000[[/C][C]135000[/C][C]5[/C][C]0.041667[/C][C]0.091667[/C][C]4e-06[/C][/ROW]
[ROW][C][140000,150000[[/C][C]145000[/C][C]6[/C][C]0.05[/C][C]0.141667[/C][C]5e-06[/C][/ROW]
[ROW][C][150000,160000[[/C][C]155000[/C][C]2[/C][C]0.016667[/C][C]0.158333[/C][C]2e-06[/C][/ROW]
[ROW][C][160000,170000[[/C][C]165000[/C][C]5[/C][C]0.041667[/C][C]0.2[/C][C]4e-06[/C][/ROW]
[ROW][C][170000,180000[[/C][C]175000[/C][C]5[/C][C]0.041667[/C][C]0.241667[/C][C]4e-06[/C][/ROW]
[ROW][C][180000,190000[[/C][C]185000[/C][C]5[/C][C]0.041667[/C][C]0.283333[/C][C]4e-06[/C][/ROW]
[ROW][C][190000,200000[[/C][C]195000[/C][C]4[/C][C]0.033333[/C][C]0.316667[/C][C]3e-06[/C][/ROW]
[ROW][C][200000,210000[[/C][C]205000[/C][C]2[/C][C]0.016667[/C][C]0.333333[/C][C]2e-06[/C][/ROW]
[ROW][C][210000,220000[[/C][C]215000[/C][C]8[/C][C]0.066667[/C][C]0.4[/C][C]7e-06[/C][/ROW]
[ROW][C][220000,230000[[/C][C]225000[/C][C]6[/C][C]0.05[/C][C]0.45[/C][C]5e-06[/C][/ROW]
[ROW][C][230000,240000[[/C][C]235000[/C][C]5[/C][C]0.041667[/C][C]0.491667[/C][C]4e-06[/C][/ROW]
[ROW][C][240000,250000[[/C][C]245000[/C][C]23[/C][C]0.191667[/C][C]0.683333[/C][C]1.9e-05[/C][/ROW]
[ROW][C][250000,260000[[/C][C]255000[/C][C]12[/C][C]0.1[/C][C]0.783333[/C][C]1e-05[/C][/ROW]
[ROW][C][260000,270000[[/C][C]265000[/C][C]23[/C][C]0.191667[/C][C]0.975[/C][C]1.9e-05[/C][/ROW]
[ROW][C][270000,280000[[/C][C]275000[/C][C]2[/C][C]0.016667[/C][C]0.991667[/C][C]2e-06[/C][/ROW]
[ROW][C][280000,290000][/C][C]285000[/C][C]1[/C][C]0.008333[/C][C]1[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306737&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306737&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
[70000,80000[7500010.0083330.0083331e-06
[80000,90000[85000000.0083330
[90000,100000[9500010.0083330.0166671e-06
[100000,110000[10500020.0166670.0333332e-06
[110000,120000[11500020.0166670.052e-06
[120000,130000[125000000.050
[130000,140000[13500050.0416670.0916674e-06
[140000,150000[14500060.050.1416675e-06
[150000,160000[15500020.0166670.1583332e-06
[160000,170000[16500050.0416670.24e-06
[170000,180000[17500050.0416670.2416674e-06
[180000,190000[18500050.0416670.2833334e-06
[190000,200000[19500040.0333330.3166673e-06
[200000,210000[20500020.0166670.3333332e-06
[210000,220000[21500080.0666670.47e-06
[220000,230000[22500060.050.455e-06
[230000,240000[23500050.0416670.4916674e-06
[240000,250000[245000230.1916670.6833331.9e-05
[250000,260000[255000120.10.7833331e-05
[260000,270000[265000230.1916670.9751.9e-05
[270000,280000[27500020.0166670.9916672e-06
[280000,290000]28500010.00833311e-06



Parameters (Session):
Parameters (R input):
par1 = 24 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '8'
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,'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')
}