Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 09 Aug 2016 08:50:46 +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/2016/Aug/09/t1470729060jest4g8m7x089z4.htm/, Retrieved Sat, 18 May 2024 05:44:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296128, Retrieved Sat, 18 May 2024 05:44:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2016-08-09 07:18:36] [ba9845715efdcdf5bf90594b26d5ea9c]
-   PD  [Univariate Data Series] [] [2016-08-09 07:23:22] [ba9845715efdcdf5bf90594b26d5ea9c]
- RMPD      [Histogram] [] [2016-08-09 07:50:46] [eed3b94f44ab74d862a61d666a631b56] [Current]
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Dataseries X:
7263.63
7135.88
7008.00
6752.38
9339.00
9211.13
7263.63
5970.38
6098.13
6098.13
6226.00
6495.50
5714.75
4932.75
4292.38
4292.38
6752.38
7008.00
5060.50
2857.38
4022.88
4022.88
4932.75
5457.88
5330.00
4022.88
4677.13
4420.25
6623.38
6098.13
4022.88
2472.75
3895.00
4292.38
4677.13
5188.38
4150.63
3254.75
3639.50
3767.25
7135.88
7135.88
5188.38
4932.75
5714.75
5330.00
6367.75
7661.00
7917.88
6098.13
5585.63
5060.50
8570.88
8827.75
8173.50
8827.75
8698.63
7661.00
8827.75
10121.00
10646.13
9083.38
8045.63
8827.75
12196.25
13234.00
12978.38
13489.50
13361.75
12068.50
14271.63
14796.75
15564.88
13234.00
12324.13
13361.75
15834.38
18037.50
17512.38
17512.38
17769.25
16872.00
19204.25
19204.25
18806.88
16602.50
16999.88
17256.75
18947.38
21150.50
19587.63
20369.75
19715.50
19332.00
22317.25
21663.00
20753.13
19459.88
20753.13
21407.38
22188.13
23225.75
22188.13
22828.50
22047.63
21919.88
25160.63
25430.13
24392.50
22572.88
24123.00
24776.00
25558.00
26723.50
25558.00
26467.88
26070.50
24648.13
27633.25
27633.25




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296128&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296128&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296128&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'George Udny Yule' @ yule.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[2000,4000[300060.050.052.5e-05
[4000,6000[5000250.2083330.2583330.000104
[6000,8000[7000200.1666670.4258.3e-05
[8000,10000[9000110.0916670.5166674.6e-05
[10000,12000[1100020.0166670.5333338e-06
[12000,14000[1300090.0750.6083333.8e-05
[14000,16000[1500040.0333330.6416671.7e-05
[16000,18000[1700070.0583330.72.9e-05
[18000,20000[1900090.0750.7753.8e-05
[20000,22000[2100070.0583330.8333332.9e-05
[22000,24000[2300070.0583330.8916672.9e-05
[24000,26000[2500080.0666670.9583333.3e-05
[26000,28000]2700050.04166712.1e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[2000,4000[ & 3000 & 6 & 0.05 & 0.05 & 2.5e-05 \tabularnewline
[4000,6000[ & 5000 & 25 & 0.208333 & 0.258333 & 0.000104 \tabularnewline
[6000,8000[ & 7000 & 20 & 0.166667 & 0.425 & 8.3e-05 \tabularnewline
[8000,10000[ & 9000 & 11 & 0.091667 & 0.516667 & 4.6e-05 \tabularnewline
[10000,12000[ & 11000 & 2 & 0.016667 & 0.533333 & 8e-06 \tabularnewline
[12000,14000[ & 13000 & 9 & 0.075 & 0.608333 & 3.8e-05 \tabularnewline
[14000,16000[ & 15000 & 4 & 0.033333 & 0.641667 & 1.7e-05 \tabularnewline
[16000,18000[ & 17000 & 7 & 0.058333 & 0.7 & 2.9e-05 \tabularnewline
[18000,20000[ & 19000 & 9 & 0.075 & 0.775 & 3.8e-05 \tabularnewline
[20000,22000[ & 21000 & 7 & 0.058333 & 0.833333 & 2.9e-05 \tabularnewline
[22000,24000[ & 23000 & 7 & 0.058333 & 0.891667 & 2.9e-05 \tabularnewline
[24000,26000[ & 25000 & 8 & 0.066667 & 0.958333 & 3.3e-05 \tabularnewline
[26000,28000] & 27000 & 5 & 0.041667 & 1 & 2.1e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296128&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][2000,4000[[/C][C]3000[/C][C]6[/C][C]0.05[/C][C]0.05[/C][C]2.5e-05[/C][/ROW]
[ROW][C][4000,6000[[/C][C]5000[/C][C]25[/C][C]0.208333[/C][C]0.258333[/C][C]0.000104[/C][/ROW]
[ROW][C][6000,8000[[/C][C]7000[/C][C]20[/C][C]0.166667[/C][C]0.425[/C][C]8.3e-05[/C][/ROW]
[ROW][C][8000,10000[[/C][C]9000[/C][C]11[/C][C]0.091667[/C][C]0.516667[/C][C]4.6e-05[/C][/ROW]
[ROW][C][10000,12000[[/C][C]11000[/C][C]2[/C][C]0.016667[/C][C]0.533333[/C][C]8e-06[/C][/ROW]
[ROW][C][12000,14000[[/C][C]13000[/C][C]9[/C][C]0.075[/C][C]0.608333[/C][C]3.8e-05[/C][/ROW]
[ROW][C][14000,16000[[/C][C]15000[/C][C]4[/C][C]0.033333[/C][C]0.641667[/C][C]1.7e-05[/C][/ROW]
[ROW][C][16000,18000[[/C][C]17000[/C][C]7[/C][C]0.058333[/C][C]0.7[/C][C]2.9e-05[/C][/ROW]
[ROW][C][18000,20000[[/C][C]19000[/C][C]9[/C][C]0.075[/C][C]0.775[/C][C]3.8e-05[/C][/ROW]
[ROW][C][20000,22000[[/C][C]21000[/C][C]7[/C][C]0.058333[/C][C]0.833333[/C][C]2.9e-05[/C][/ROW]
[ROW][C][22000,24000[[/C][C]23000[/C][C]7[/C][C]0.058333[/C][C]0.891667[/C][C]2.9e-05[/C][/ROW]
[ROW][C][24000,26000[[/C][C]25000[/C][C]8[/C][C]0.066667[/C][C]0.958333[/C][C]3.3e-05[/C][/ROW]
[ROW][C][26000,28000][/C][C]27000[/C][C]5[/C][C]0.041667[/C][C]1[/C][C]2.1e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296128&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296128&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
[2000,4000[300060.050.052.5e-05
[4000,6000[5000250.2083330.2583330.000104
[6000,8000[7000200.1666670.4258.3e-05
[8000,10000[9000110.0916670.5166674.6e-05
[10000,12000[1100020.0166670.5333338e-06
[12000,14000[1300090.0750.6083333.8e-05
[14000,16000[1500040.0333330.6416671.7e-05
[16000,18000[1700070.0583330.72.9e-05
[18000,20000[1900090.0750.7753.8e-05
[20000,22000[2100070.0583330.8333332.9e-05
[22000,24000[2300070.0583330.8916672.9e-05
[24000,26000[2500080.0666670.9583333.3e-05
[26000,28000]2700050.04166712.1e-05



Parameters (Session):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '20'
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')
}