Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 15 Aug 2016 14:19:44 +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/15/t14712673059b53a054e1z2uwg.htm/, Retrieved Sun, 28 Apr 2024 11:00:37 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 28 Apr 2024 11:00:37 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
21571.00
21493.00
21422.00
21272.00
22747.00
22676.00
21571.00
20831.00
20909.00
20909.00
20980.00
21130.00
21051.00
21643.00
21864.00
21643.00
22455.00
21935.00
20759.00
20467.00
20467.00
20610.00
20026.00
20467.00
20097.00
20467.00
21051.00
21272.00
21792.00
21571.00
20246.00
19726.00
19506.00
19726.00
19363.00
19506.00
19064.00
19805.00
20168.00
20246.00
21643.00
21643.00
19805.00
19363.00
19363.00
19584.00
18622.00
18180.00
17668.00
17817.00
18480.00
17960.00
19363.00
19584.00
18180.00
17668.00
17375.00
17668.00
16855.00
16563.00
15388.00
15680.00
15751.00
15830.00
17226.00
17076.00
15388.00
14647.00
14355.00
14725.00
13322.00
12367.00
10601.00
10750.00
10750.00
10601.00
11854.00
11926.00
10451.00
10159.00
9568.00
10380.00
8905.00
8022.00
6333.00
6697.00
6255.00
6404.00
7509.00
7730.00
6996.00
6917.00
6917.00
7879.00
6184.00
5079.00
3163.00
4709.00
4488.00
4566.00
6333.00
6112.00
5300.00
5671.00
5671.00
6996.00
5450.00
4566.00
3163.00
5008.00
4859.00
4930.00
6476.00
6333.00
5813.00
5892.00
6255.00
7067.00
5813.00
4787.00






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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[3000,4000[350020.0166670.0166671.7e-05
[4000,5000[450070.0583330.0755.8e-05
[5000,6000[550090.0750.157.5e-05
[6000,7000[6500140.1166670.2666670.000117
[7000,8000[750040.0333330.33.3e-05
[8000,9000[850020.0166670.3166671.7e-05
[9000,10000[950010.0083330.3258e-06
[10000,11000[1050070.0583330.3833335.8e-05
[11000,12000[1150020.0166670.41.7e-05
[12000,13000[1250010.0083330.4083338e-06
[13000,14000[1350010.0083330.4166678e-06
[14000,15000[1450030.0250.4416672.5e-05
[15000,16000[1550050.0416670.4833334.2e-05
[16000,17000[1650020.0166670.51.7e-05
[17000,18000[1750080.0666670.5666676.7e-05
[18000,19000[1850040.0333330.63.3e-05
[19000,20000[19500130.1083330.7083330.000108
[20000,21000[20500150.1250.8333330.000125
[21000,22000[21500170.1416670.9750.000142
[22000,23000]2250030.02512.5e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[3000,4000[ & 3500 & 2 & 0.016667 & 0.016667 & 1.7e-05 \tabularnewline
[4000,5000[ & 4500 & 7 & 0.058333 & 0.075 & 5.8e-05 \tabularnewline
[5000,6000[ & 5500 & 9 & 0.075 & 0.15 & 7.5e-05 \tabularnewline
[6000,7000[ & 6500 & 14 & 0.116667 & 0.266667 & 0.000117 \tabularnewline
[7000,8000[ & 7500 & 4 & 0.033333 & 0.3 & 3.3e-05 \tabularnewline
[8000,9000[ & 8500 & 2 & 0.016667 & 0.316667 & 1.7e-05 \tabularnewline
[9000,10000[ & 9500 & 1 & 0.008333 & 0.325 & 8e-06 \tabularnewline
[10000,11000[ & 10500 & 7 & 0.058333 & 0.383333 & 5.8e-05 \tabularnewline
[11000,12000[ & 11500 & 2 & 0.016667 & 0.4 & 1.7e-05 \tabularnewline
[12000,13000[ & 12500 & 1 & 0.008333 & 0.408333 & 8e-06 \tabularnewline
[13000,14000[ & 13500 & 1 & 0.008333 & 0.416667 & 8e-06 \tabularnewline
[14000,15000[ & 14500 & 3 & 0.025 & 0.441667 & 2.5e-05 \tabularnewline
[15000,16000[ & 15500 & 5 & 0.041667 & 0.483333 & 4.2e-05 \tabularnewline
[16000,17000[ & 16500 & 2 & 0.016667 & 0.5 & 1.7e-05 \tabularnewline
[17000,18000[ & 17500 & 8 & 0.066667 & 0.566667 & 6.7e-05 \tabularnewline
[18000,19000[ & 18500 & 4 & 0.033333 & 0.6 & 3.3e-05 \tabularnewline
[19000,20000[ & 19500 & 13 & 0.108333 & 0.708333 & 0.000108 \tabularnewline
[20000,21000[ & 20500 & 15 & 0.125 & 0.833333 & 0.000125 \tabularnewline
[21000,22000[ & 21500 & 17 & 0.141667 & 0.975 & 0.000142 \tabularnewline
[22000,23000] & 22500 & 3 & 0.025 & 1 & 2.5e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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][3000,4000[[/C][C]3500[/C][C]2[/C][C]0.016667[/C][C]0.016667[/C][C]1.7e-05[/C][/ROW]
[ROW][C][4000,5000[[/C][C]4500[/C][C]7[/C][C]0.058333[/C][C]0.075[/C][C]5.8e-05[/C][/ROW]
[ROW][C][5000,6000[[/C][C]5500[/C][C]9[/C][C]0.075[/C][C]0.15[/C][C]7.5e-05[/C][/ROW]
[ROW][C][6000,7000[[/C][C]6500[/C][C]14[/C][C]0.116667[/C][C]0.266667[/C][C]0.000117[/C][/ROW]
[ROW][C][7000,8000[[/C][C]7500[/C][C]4[/C][C]0.033333[/C][C]0.3[/C][C]3.3e-05[/C][/ROW]
[ROW][C][8000,9000[[/C][C]8500[/C][C]2[/C][C]0.016667[/C][C]0.316667[/C][C]1.7e-05[/C][/ROW]
[ROW][C][9000,10000[[/C][C]9500[/C][C]1[/C][C]0.008333[/C][C]0.325[/C][C]8e-06[/C][/ROW]
[ROW][C][10000,11000[[/C][C]10500[/C][C]7[/C][C]0.058333[/C][C]0.383333[/C][C]5.8e-05[/C][/ROW]
[ROW][C][11000,12000[[/C][C]11500[/C][C]2[/C][C]0.016667[/C][C]0.4[/C][C]1.7e-05[/C][/ROW]
[ROW][C][12000,13000[[/C][C]12500[/C][C]1[/C][C]0.008333[/C][C]0.408333[/C][C]8e-06[/C][/ROW]
[ROW][C][13000,14000[[/C][C]13500[/C][C]1[/C][C]0.008333[/C][C]0.416667[/C][C]8e-06[/C][/ROW]
[ROW][C][14000,15000[[/C][C]14500[/C][C]3[/C][C]0.025[/C][C]0.441667[/C][C]2.5e-05[/C][/ROW]
[ROW][C][15000,16000[[/C][C]15500[/C][C]5[/C][C]0.041667[/C][C]0.483333[/C][C]4.2e-05[/C][/ROW]
[ROW][C][16000,17000[[/C][C]16500[/C][C]2[/C][C]0.016667[/C][C]0.5[/C][C]1.7e-05[/C][/ROW]
[ROW][C][17000,18000[[/C][C]17500[/C][C]8[/C][C]0.066667[/C][C]0.566667[/C][C]6.7e-05[/C][/ROW]
[ROW][C][18000,19000[[/C][C]18500[/C][C]4[/C][C]0.033333[/C][C]0.6[/C][C]3.3e-05[/C][/ROW]
[ROW][C][19000,20000[[/C][C]19500[/C][C]13[/C][C]0.108333[/C][C]0.708333[/C][C]0.000108[/C][/ROW]
[ROW][C][20000,21000[[/C][C]20500[/C][C]15[/C][C]0.125[/C][C]0.833333[/C][C]0.000125[/C][/ROW]
[ROW][C][21000,22000[[/C][C]21500[/C][C]17[/C][C]0.141667[/C][C]0.975[/C][C]0.000142[/C][/ROW]
[ROW][C][22000,23000][/C][C]22500[/C][C]3[/C][C]0.025[/C][C]1[/C][C]2.5e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
[3000,4000[350020.0166670.0166671.7e-05
[4000,5000[450070.0583330.0755.8e-05
[5000,6000[550090.0750.157.5e-05
[6000,7000[6500140.1166670.2666670.000117
[7000,8000[750040.0333330.33.3e-05
[8000,9000[850020.0166670.3166671.7e-05
[9000,10000[950010.0083330.3258e-06
[10000,11000[1050070.0583330.3833335.8e-05
[11000,12000[1150020.0166670.41.7e-05
[12000,13000[1250010.0083330.4083338e-06
[13000,14000[1350010.0083330.4166678e-06
[14000,15000[1450030.0250.4416672.5e-05
[15000,16000[1550050.0416670.4833334.2e-05
[16000,17000[1650020.0166670.51.7e-05
[17000,18000[1750080.0666670.5666676.7e-05
[18000,19000[1850040.0333330.63.3e-05
[19000,20000[19500130.1083330.7083330.000108
[20000,21000[20500150.1250.8333330.000125
[21000,22000[21500170.1416670.9750.000142
[22000,23000]2250030.02512.5e-05



Parameters (Session):
par1 = 15 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 15 ; 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 {
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')
}