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Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 18 Jul 2015 14:37:01 +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/Jul/18/t1437226645glhiybjz9jsa2bn.htm/, Retrieved Fri, 17 May 2024 05:33:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279585, Retrieved Fri, 17 May 2024 05:33:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [opgave 2 a] [2015-07-18 13:37:01] [b43493158838656c32486372ca9c54cf] [Current]
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Dataseries X:
228768.00
227916.00
227052.00
225264.00
242952.00
242016.00
228768.00
219960.00
220812.00
220812.00
221760.00
223464.00
226116.00
226116.00
224412.00
219960.00
242952.00
246456.00
241164.00
228768.00
234072.00
226116.00
229704.00
231420.00
233208.00
228768.00
229704.00
223464.00
242952.00
249108.00
243816.00
234072.00
244668.00
233208.00
243816.00
242952.00
245604.00
235860.00
246456.00
245604.00
261504.00
257916.00
243816.00
236712.00
246456.00
233208.00
242952.00
244668.00
248256.00
240312.00
244668.00
247320.00
257064.00
249108.00
238512.00
227052.00
237660.00
208500.00
222612.00
230556.00
238512.00
227052.00
227052.00
227052.00
233208.00
224412.00
212868.00
203208.00
210216.00
182856.00
199620.00
209364.00
211152.00
201408.00
202260.00
199620.00
208500.00
202260.00
189960.00
181068.00
196104.00
163452.00
184656.00
194316.00
194316.00
182856.00
172260.00
171408.00
181068.00
172260.00
155508.00
143964.00
156360.00
127212.00
153708.00
167808.00
172260.00
162516.00
150204.00
159012.00
162516.00
159864.00
133356.00
121056.00
129852.00
103356.00
130716.00
140460.00
148404.00
135156.00
122760.00
129852.00
133356.00
126348.00
99852.00
88308.00
98904.00
69756.00
101556.00
121056.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279585&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279585&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279585&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'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[60000,70000[6500010.0083330.0083331e-06
[70000,80000[75000000.0083330
[80000,90000[8500010.0083330.0166671e-06
[90000,1e+05[9500020.0166670.0333332e-06
[1e+05,110000[10500020.0166670.052e-06
[110000,120000[115000000.050
[120000,130000[12500070.0583330.1083336e-06
[130000,140000[13500040.0333330.1416673e-06
[140000,150000[14500030.0250.1666672e-06
[150000,160000[15500060.050.2166675e-06
[160000,170000[16500040.0333330.253e-06
[170000,180000[17500040.0333330.2833333e-06
[180000,190000[18500060.050.3333335e-06
[190000,2e+05[19500050.0416670.3754e-06
[2e+05,210000[20500070.0583330.4333336e-06
[210000,220000[21500050.0416670.4754e-06
[220000,230000[225000240.20.6752e-05
[230000,240000[235000130.1083330.7833331.1e-05
[240000,250000[245000230.1916670.9751.9e-05
[250000,260000[25500020.0166670.9916672e-06
[260000,270000]26500010.00833311e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[60000,70000[ & 65000 & 1 & 0.008333 & 0.008333 & 1e-06 \tabularnewline
[70000,80000[ & 75000 & 0 & 0 & 0.008333 & 0 \tabularnewline
[80000,90000[ & 85000 & 1 & 0.008333 & 0.016667 & 1e-06 \tabularnewline
[90000,1e+05[ & 95000 & 2 & 0.016667 & 0.033333 & 2e-06 \tabularnewline
[1e+05,110000[ & 105000 & 2 & 0.016667 & 0.05 & 2e-06 \tabularnewline
[110000,120000[ & 115000 & 0 & 0 & 0.05 & 0 \tabularnewline
[120000,130000[ & 125000 & 7 & 0.058333 & 0.108333 & 6e-06 \tabularnewline
[130000,140000[ & 135000 & 4 & 0.033333 & 0.141667 & 3e-06 \tabularnewline
[140000,150000[ & 145000 & 3 & 0.025 & 0.166667 & 2e-06 \tabularnewline
[150000,160000[ & 155000 & 6 & 0.05 & 0.216667 & 5e-06 \tabularnewline
[160000,170000[ & 165000 & 4 & 0.033333 & 0.25 & 3e-06 \tabularnewline
[170000,180000[ & 175000 & 4 & 0.033333 & 0.283333 & 3e-06 \tabularnewline
[180000,190000[ & 185000 & 6 & 0.05 & 0.333333 & 5e-06 \tabularnewline
[190000,2e+05[ & 195000 & 5 & 0.041667 & 0.375 & 4e-06 \tabularnewline
[2e+05,210000[ & 205000 & 7 & 0.058333 & 0.433333 & 6e-06 \tabularnewline
[210000,220000[ & 215000 & 5 & 0.041667 & 0.475 & 4e-06 \tabularnewline
[220000,230000[ & 225000 & 24 & 0.2 & 0.675 & 2e-05 \tabularnewline
[230000,240000[ & 235000 & 13 & 0.108333 & 0.783333 & 1.1e-05 \tabularnewline
[240000,250000[ & 245000 & 23 & 0.191667 & 0.975 & 1.9e-05 \tabularnewline
[250000,260000[ & 255000 & 2 & 0.016667 & 0.991667 & 2e-06 \tabularnewline
[260000,270000] & 265000 & 1 & 0.008333 & 1 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279585&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][60000,70000[[/C][C]65000[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]1e-06[/C][/ROW]
[ROW][C][70000,80000[[/C][C]75000[/C][C]0[/C][C]0[/C][C]0.008333[/C][C]0[/C][/ROW]
[ROW][C][80000,90000[[/C][C]85000[/C][C]1[/C][C]0.008333[/C][C]0.016667[/C][C]1e-06[/C][/ROW]
[ROW][C][90000,1e+05[[/C][C]95000[/C][C]2[/C][C]0.016667[/C][C]0.033333[/C][C]2e-06[/C][/ROW]
[ROW][C][1e+05,110000[[/C][C]105000[/C][C]2[/C][C]0.016667[/C][C]0.05[/C][C]2e-06[/C][/ROW]
[ROW][C][110000,120000[[/C][C]115000[/C][C]0[/C][C]0[/C][C]0.05[/C][C]0[/C][/ROW]
[ROW][C][120000,130000[[/C][C]125000[/C][C]7[/C][C]0.058333[/C][C]0.108333[/C][C]6e-06[/C][/ROW]
[ROW][C][130000,140000[[/C][C]135000[/C][C]4[/C][C]0.033333[/C][C]0.141667[/C][C]3e-06[/C][/ROW]
[ROW][C][140000,150000[[/C][C]145000[/C][C]3[/C][C]0.025[/C][C]0.166667[/C][C]2e-06[/C][/ROW]
[ROW][C][150000,160000[[/C][C]155000[/C][C]6[/C][C]0.05[/C][C]0.216667[/C][C]5e-06[/C][/ROW]
[ROW][C][160000,170000[[/C][C]165000[/C][C]4[/C][C]0.033333[/C][C]0.25[/C][C]3e-06[/C][/ROW]
[ROW][C][170000,180000[[/C][C]175000[/C][C]4[/C][C]0.033333[/C][C]0.283333[/C][C]3e-06[/C][/ROW]
[ROW][C][180000,190000[[/C][C]185000[/C][C]6[/C][C]0.05[/C][C]0.333333[/C][C]5e-06[/C][/ROW]
[ROW][C][190000,2e+05[[/C][C]195000[/C][C]5[/C][C]0.041667[/C][C]0.375[/C][C]4e-06[/C][/ROW]
[ROW][C][2e+05,210000[[/C][C]205000[/C][C]7[/C][C]0.058333[/C][C]0.433333[/C][C]6e-06[/C][/ROW]
[ROW][C][210000,220000[[/C][C]215000[/C][C]5[/C][C]0.041667[/C][C]0.475[/C][C]4e-06[/C][/ROW]
[ROW][C][220000,230000[[/C][C]225000[/C][C]24[/C][C]0.2[/C][C]0.675[/C][C]2e-05[/C][/ROW]
[ROW][C][230000,240000[[/C][C]235000[/C][C]13[/C][C]0.108333[/C][C]0.783333[/C][C]1.1e-05[/C][/ROW]
[ROW][C][240000,250000[[/C][C]245000[/C][C]23[/C][C]0.191667[/C][C]0.975[/C][C]1.9e-05[/C][/ROW]
[ROW][C][250000,260000[[/C][C]255000[/C][C]2[/C][C]0.016667[/C][C]0.991667[/C][C]2e-06[/C][/ROW]
[ROW][C][260000,270000][/C][C]265000[/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=279585&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279585&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
[60000,70000[6500010.0083330.0083331e-06
[70000,80000[75000000.0083330
[80000,90000[8500010.0083330.0166671e-06
[90000,1e+05[9500020.0166670.0333332e-06
[1e+05,110000[10500020.0166670.052e-06
[110000,120000[115000000.050
[120000,130000[12500070.0583330.1083336e-06
[130000,140000[13500040.0333330.1416673e-06
[140000,150000[14500030.0250.1666672e-06
[150000,160000[15500060.050.2166675e-06
[160000,170000[16500040.0333330.253e-06
[170000,180000[17500040.0333330.2833333e-06
[180000,190000[18500060.050.3333335e-06
[190000,2e+05[19500050.0416670.3754e-06
[2e+05,210000[20500070.0583330.4333336e-06
[210000,220000[21500050.0416670.4754e-06
[220000,230000[225000240.20.6752e-05
[230000,240000[235000130.1083330.7833331.1e-05
[240000,250000[245000230.1916670.9751.9e-05
[250000,260000[25500020.0166670.9916672e-06
[260000,270000]26500010.00833311e-06



Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '6'
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')
}