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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 15 Aug 2015 13:25:55 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/15/t1439641606rri8o35gupwni45.htm/, Retrieved Wed, 15 May 2024 01:14:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280085, Retrieved Wed, 15 May 2024 01:14:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram omzet n...] [2015-08-15 12:25:55] [0d8529ada52922935dd1fcf0fb375c74] [Current]
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Dataseries X:
133448,00
132951,00
132447,00
131404,00
141722,00
141176,00
133448,00
128310,00
128807,00
128807,00
129360,00
130354,00
131901,00
131901,00
130907,00
128310,00
141722,00
143766,00
140679,00
133448,00
136542,00
131901,00
133994,00
134995,00
136038,00
133448,00
133994,00
130354,00
141722,00
145313,00
142226,00
136542,00
142723,00
136038,00
142226,00
141722,00
143269,00
137585,00
143766,00
143269,00
152544,00
150451,00
142226,00
138082,00
143766,00
136038,00
141722,00
142723,00
144816,00
140182,00
142723,00
144270,00
149954,00
145313,00
139132,00
132447,00
138635,00
121625,00
129857,00
134491,00
139132,00
132447,00
132447,00
132447,00
136038,00
130907,00
124173,00
118538,00
122626,00
106666,00
116445,00
122129,00
123172,00
117488,00
117985,00
116445,00
121625,00
117985,00
110810,00
105623,00
114394,00
95347,00
107716,00
113351,00
113351,00
106666,00
100485,00
99988,00
105623,00
100485,00
90713,00
83979,00
91210,00
74207,00
89663,00
97888,00
100485,00
94801,00
87619,00
92757,00
94801,00
93254,00
77791,00
70616,00
75747,00
60291,00
76251,00
81935,00
86569,00
78841,00
71610,00
75747,00
77791,00
73703,00
58247,00
51513,00
57694,00
40691,00
59241,00
70616,00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280085&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280085&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280085&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'Sir Maurice George Kendall' @ kendall.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[40000,50000[4500010.0083330.0083331e-06
[50000,60000[5500040.0333330.0416673e-06
[60000,70000[6500010.0083330.051e-06
[70000,80000[75000110.0916670.1416679e-06
[80000,90000[8500050.0416670.1833334e-06
[90000,1e+05[9500090.0750.2583338e-06
[1e+05,110000[10500080.0666670.3257e-06
[110000,120000[115000100.0833330.4083338e-06
[120000,130000[125000120.10.5083331e-05
[130000,140000[135000330.2750.7833332.8e-05
[140000,150000[145000240.20.9833332e-05
[150000,160000]15500020.01666712e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[40000,50000[ & 45000 & 1 & 0.008333 & 0.008333 & 1e-06 \tabularnewline
[50000,60000[ & 55000 & 4 & 0.033333 & 0.041667 & 3e-06 \tabularnewline
[60000,70000[ & 65000 & 1 & 0.008333 & 0.05 & 1e-06 \tabularnewline
[70000,80000[ & 75000 & 11 & 0.091667 & 0.141667 & 9e-06 \tabularnewline
[80000,90000[ & 85000 & 5 & 0.041667 & 0.183333 & 4e-06 \tabularnewline
[90000,1e+05[ & 95000 & 9 & 0.075 & 0.258333 & 8e-06 \tabularnewline
[1e+05,110000[ & 105000 & 8 & 0.066667 & 0.325 & 7e-06 \tabularnewline
[110000,120000[ & 115000 & 10 & 0.083333 & 0.408333 & 8e-06 \tabularnewline
[120000,130000[ & 125000 & 12 & 0.1 & 0.508333 & 1e-05 \tabularnewline
[130000,140000[ & 135000 & 33 & 0.275 & 0.783333 & 2.8e-05 \tabularnewline
[140000,150000[ & 145000 & 24 & 0.2 & 0.983333 & 2e-05 \tabularnewline
[150000,160000] & 155000 & 2 & 0.016667 & 1 & 2e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280085&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][40000,50000[[/C][C]45000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]1e-06[/C][/ROW]
[ROW][C][50000,60000[[/C][C]55000[/C][C]4[/C][C]0.033333[/C][C]0.041667[/C][C]3e-06[/C][/ROW]
[ROW][C][60000,70000[[/C][C]65000[/C][C]1[/C][C]0.008333[/C][C]0.05[/C][C]1e-06[/C][/ROW]
[ROW][C][70000,80000[[/C][C]75000[/C][C]11[/C][C]0.091667[/C][C]0.141667[/C][C]9e-06[/C][/ROW]
[ROW][C][80000,90000[[/C][C]85000[/C][C]5[/C][C]0.041667[/C][C]0.183333[/C][C]4e-06[/C][/ROW]
[ROW][C][90000,1e+05[[/C][C]95000[/C][C]9[/C][C]0.075[/C][C]0.258333[/C][C]8e-06[/C][/ROW]
[ROW][C][1e+05,110000[[/C][C]105000[/C][C]8[/C][C]0.066667[/C][C]0.325[/C][C]7e-06[/C][/ROW]
[ROW][C][110000,120000[[/C][C]115000[/C][C]10[/C][C]0.083333[/C][C]0.408333[/C][C]8e-06[/C][/ROW]
[ROW][C][120000,130000[[/C][C]125000[/C][C]12[/C][C]0.1[/C][C]0.508333[/C][C]1e-05[/C][/ROW]
[ROW][C][130000,140000[[/C][C]135000[/C][C]33[/C][C]0.275[/C][C]0.783333[/C][C]2.8e-05[/C][/ROW]
[ROW][C][140000,150000[[/C][C]145000[/C][C]24[/C][C]0.2[/C][C]0.983333[/C][C]2e-05[/C][/ROW]
[ROW][C][150000,160000][/C][C]155000[/C][C]2[/C][C]0.016667[/C][C]1[/C][C]2e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280085&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280085&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
[40000,50000[4500010.0083330.0083331e-06
[50000,60000[5500040.0333330.0416673e-06
[60000,70000[6500010.0083330.051e-06
[70000,80000[75000110.0916670.1416679e-06
[80000,90000[8500050.0416670.1833334e-06
[90000,1e+05[9500090.0750.2583338e-06
[1e+05,110000[10500080.0666670.3257e-06
[110000,120000[115000100.0833330.4083338e-06
[120000,130000[125000120.10.5083331e-05
[130000,140000[135000330.2750.7833332.8e-05
[140000,150000[145000240.20.9833332e-05
[150000,160000]15500020.01666712e-06



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')
}