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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationFri, 07 Aug 2015 16:02:27 +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/07/t1438959862sdc163vpplirbh6.htm/, Retrieved Thu, 31 Oct 2024 23:59:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279906, Retrieved Thu, 31 Oct 2024 23:59:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-08-07 15:02:27] [70e23d918d09c907c02097a361cd6415] [Current]
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Dataseries X:
209704.00
208923.00
208131.00
206492.00
222706.00
221848.00
209704.00
201630.00
202411.00
202411.00
203280.00
204842.00
207273.00
207273.00
205711.00
201630.00
222706.00
225918.00
221067.00
209704.00
214566.00
207273.00
210562.00
212135.00
213774.00
209704.00
210562.00
204842.00
222706.00
228349.00
223498.00
214566.00
224279.00
213774.00
223498.00
222706.00
225137.00
216205.00
225918.00
225137.00
239712.00
236423.00
223498.00
216986.00
225918.00
213774.00
222706.00
224279.00
227568.00
220286.00
224279.00
226710.00
235642.00
228349.00
218636.00
208131.00
217855.00
191125.00
204061.00
211343.00
218636.00
208131.00
208131.00
208131.00
213774.00
205711.00
195129.00
186274.00
192698.00
167618.00
182985.00
191917.00
193556.00
184624.00
185405.00
182985.00
191125.00
185405.00
174130.00
165979.00
179762.00
149831.00
169268.00
178123.00
178123.00
167618.00
157905.00
157124.00
165979.00
157905.00
142549.00
131967.00
143330.00
116611.00
140899.00
153824.00
157905.00
148973.00
137687.00
145761.00
148973.00
146542.00
122243.00
110968.00
119031.00
94743.00
119823.00
128755.00
136037.00
123893.00
112530.00
119031.00
122243.00
115819.00
91531.00
80949.00
90662.00
63943.00
93093.00
110968.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279906&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279906&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279906&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'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[60000,80000[7000010.0083330.0083330
[80000,1e+05[9000050.0416670.052e-06
[1e+05,120000[11000080.0666670.1166673e-06
[120000,140000[13000070.0583330.1753e-06
[140000,160000[150000130.1083330.2833335e-06
[160000,180000[17000090.0750.3583334e-06
[180000,2e+05[190000120.10.4583335e-06
[2e+05,220000[210000390.3250.7833331.6e-05
[220000,240000]230000260.21666711.1e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[60000,80000[ & 70000 & 1 & 0.008333 & 0.008333 & 0 \tabularnewline
[80000,1e+05[ & 90000 & 5 & 0.041667 & 0.05 & 2e-06 \tabularnewline
[1e+05,120000[ & 110000 & 8 & 0.066667 & 0.116667 & 3e-06 \tabularnewline
[120000,140000[ & 130000 & 7 & 0.058333 & 0.175 & 3e-06 \tabularnewline
[140000,160000[ & 150000 & 13 & 0.108333 & 0.283333 & 5e-06 \tabularnewline
[160000,180000[ & 170000 & 9 & 0.075 & 0.358333 & 4e-06 \tabularnewline
[180000,2e+05[ & 190000 & 12 & 0.1 & 0.458333 & 5e-06 \tabularnewline
[2e+05,220000[ & 210000 & 39 & 0.325 & 0.783333 & 1.6e-05 \tabularnewline
[220000,240000] & 230000 & 26 & 0.216667 & 1 & 1.1e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279906&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][60000,80000[[/C][C]70000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]0[/C][/ROW]
[ROW][C][80000,1e+05[[/C][C]90000[/C][C]5[/C][C]0.041667[/C][C]0.05[/C][C]2e-06[/C][/ROW]
[ROW][C][1e+05,120000[[/C][C]110000[/C][C]8[/C][C]0.066667[/C][C]0.116667[/C][C]3e-06[/C][/ROW]
[ROW][C][120000,140000[[/C][C]130000[/C][C]7[/C][C]0.058333[/C][C]0.175[/C][C]3e-06[/C][/ROW]
[ROW][C][140000,160000[[/C][C]150000[/C][C]13[/C][C]0.108333[/C][C]0.283333[/C][C]5e-06[/C][/ROW]
[ROW][C][160000,180000[[/C][C]170000[/C][C]9[/C][C]0.075[/C][C]0.358333[/C][C]4e-06[/C][/ROW]
[ROW][C][180000,2e+05[[/C][C]190000[/C][C]12[/C][C]0.1[/C][C]0.458333[/C][C]5e-06[/C][/ROW]
[ROW][C][2e+05,220000[[/C][C]210000[/C][C]39[/C][C]0.325[/C][C]0.783333[/C][C]1.6e-05[/C][/ROW]
[ROW][C][220000,240000][/C][C]230000[/C][C]26[/C][C]0.216667[/C][C]1[/C][C]1.1e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279906&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279906&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
[60000,80000[7000010.0083330.0083330
[80000,1e+05[9000050.0416670.052e-06
[1e+05,120000[11000080.0666670.1166673e-06
[120000,140000[13000070.0583330.1753e-06
[140000,160000[150000130.1083330.2833335e-06
[160000,180000[17000090.0750.3583334e-06
[180000,2e+05[190000120.10.4583335e-06
[2e+05,220000[210000390.3250.7833331.6e-05
[220000,240000]230000260.21666711.1e-05



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')
}