Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 16 Feb 2016 19:10:21 +0000
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/Feb/16/t1455649854m8jprpx2ub2efcs.htm/, Retrieved Mon, 06 May 2024 09:30:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292055, Retrieved Mon, 06 May 2024 09:30:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [] [2016-02-04 09:16:54] [e56dfe8be31eb19d2e02d76fcb74f554]
- R PD  [Histogram] [] [2016-02-16 19:07:33] [e56dfe8be31eb19d2e02d76fcb74f554]
-   P       [Histogram] [] [2016-02-16 19:10:21] [c0f67b4e93ea0adf92c2b9d3976edd70] [Current]
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Dataseries X:
87.5
87.3
87.8
88.1
88.0
87.8
87.0
87.2
87.0
89.4
89.1
87.8
87.8
88.0
86.5
84.1
84.3
84.7
85.7
86.4
86.0
86.9
89.1
90.7
89.8
89.4
88.6
86.8
86.8
89.5
88.5
91.2
92.3
92.0
92.8
92.9
92.7
94.2
94.0
94.3
94.8
94.7
95.1
97.0
97.9
97.3
96.5
98.1
99.3
99.9
99.9
99.9
99.8
99.5
99.9
100.1
100.1
100.2
100.6
100.8
100.8
100.5
101.0
100.5
99.0
97.9
97.6
97.2
96.5
96.3
96.3
96.2
95.6
93.5
93.2
93.6
94.6
96.1
98.4
99.6
99.4
99.7
100.1
99.9




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=292055&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=292055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292055&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
[84,84.5[84.2520.023810.023810.047619
[84.5,85[84.7510.0119050.0357140.02381
[85,85.5[85.25000.0357140
[85.5,86[85.7510.0119050.0476190.02381
[86,86.5[86.2520.023810.0714290.047619
[86.5,87[86.7540.0476190.1190480.095238
[87,87.5[87.2540.0476190.1666670.095238
[87.5,88[87.7550.0595240.226190.119048
[88,88.5[88.2530.0357140.2619050.071429
[88.5,89[88.7520.023810.2857140.047619
[89,89.5[89.2540.0476190.3333330.095238
[89.5,90[89.7520.023810.3571430.047619
[90,90.5[90.25000.3571430
[90.5,91[90.7510.0119050.3690480.02381
[91,91.5[91.2510.0119050.3809520.02381
[91.5,92[91.75000.3809520
[92,92.5[92.2520.023810.4047620.047619
[92.5,93[92.7530.0357140.4404760.071429
[93,93.5[93.2510.0119050.4523810.02381
[93.5,94[93.7520.023810.476190.047619
[94,94.5[94.2530.0357140.5119050.071429
[94.5,95[94.7530.0357140.5476190.071429
[95,95.5[95.2510.0119050.5595240.02381
[95.5,96[95.7510.0119050.5714290.02381
[96,96.5[96.2540.0476190.6190480.095238
[96.5,97[96.7520.023810.6428570.047619
[97,97.5[97.2530.0357140.6785710.071429
[97.5,98[97.7530.0357140.7142860.071429
[98,98.5[98.2520.023810.7380950.047619
[98.5,99[98.75000.7380950
[99,99.5[99.2530.0357140.773810.071429
[99.5,100[99.7590.1071430.8809520.214286
[100,100.5[100.2540.0476190.9285710.095238
[100.5,101]100.7560.07142910.142857

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[84,84.5[ & 84.25 & 2 & 0.02381 & 0.02381 & 0.047619 \tabularnewline
[84.5,85[ & 84.75 & 1 & 0.011905 & 0.035714 & 0.02381 \tabularnewline
[85,85.5[ & 85.25 & 0 & 0 & 0.035714 & 0 \tabularnewline
[85.5,86[ & 85.75 & 1 & 0.011905 & 0.047619 & 0.02381 \tabularnewline
[86,86.5[ & 86.25 & 2 & 0.02381 & 0.071429 & 0.047619 \tabularnewline
[86.5,87[ & 86.75 & 4 & 0.047619 & 0.119048 & 0.095238 \tabularnewline
[87,87.5[ & 87.25 & 4 & 0.047619 & 0.166667 & 0.095238 \tabularnewline
[87.5,88[ & 87.75 & 5 & 0.059524 & 0.22619 & 0.119048 \tabularnewline
[88,88.5[ & 88.25 & 3 & 0.035714 & 0.261905 & 0.071429 \tabularnewline
[88.5,89[ & 88.75 & 2 & 0.02381 & 0.285714 & 0.047619 \tabularnewline
[89,89.5[ & 89.25 & 4 & 0.047619 & 0.333333 & 0.095238 \tabularnewline
[89.5,90[ & 89.75 & 2 & 0.02381 & 0.357143 & 0.047619 \tabularnewline
[90,90.5[ & 90.25 & 0 & 0 & 0.357143 & 0 \tabularnewline
[90.5,91[ & 90.75 & 1 & 0.011905 & 0.369048 & 0.02381 \tabularnewline
[91,91.5[ & 91.25 & 1 & 0.011905 & 0.380952 & 0.02381 \tabularnewline
[91.5,92[ & 91.75 & 0 & 0 & 0.380952 & 0 \tabularnewline
[92,92.5[ & 92.25 & 2 & 0.02381 & 0.404762 & 0.047619 \tabularnewline
[92.5,93[ & 92.75 & 3 & 0.035714 & 0.440476 & 0.071429 \tabularnewline
[93,93.5[ & 93.25 & 1 & 0.011905 & 0.452381 & 0.02381 \tabularnewline
[93.5,94[ & 93.75 & 2 & 0.02381 & 0.47619 & 0.047619 \tabularnewline
[94,94.5[ & 94.25 & 3 & 0.035714 & 0.511905 & 0.071429 \tabularnewline
[94.5,95[ & 94.75 & 3 & 0.035714 & 0.547619 & 0.071429 \tabularnewline
[95,95.5[ & 95.25 & 1 & 0.011905 & 0.559524 & 0.02381 \tabularnewline
[95.5,96[ & 95.75 & 1 & 0.011905 & 0.571429 & 0.02381 \tabularnewline
[96,96.5[ & 96.25 & 4 & 0.047619 & 0.619048 & 0.095238 \tabularnewline
[96.5,97[ & 96.75 & 2 & 0.02381 & 0.642857 & 0.047619 \tabularnewline
[97,97.5[ & 97.25 & 3 & 0.035714 & 0.678571 & 0.071429 \tabularnewline
[97.5,98[ & 97.75 & 3 & 0.035714 & 0.714286 & 0.071429 \tabularnewline
[98,98.5[ & 98.25 & 2 & 0.02381 & 0.738095 & 0.047619 \tabularnewline
[98.5,99[ & 98.75 & 0 & 0 & 0.738095 & 0 \tabularnewline
[99,99.5[ & 99.25 & 3 & 0.035714 & 0.77381 & 0.071429 \tabularnewline
[99.5,100[ & 99.75 & 9 & 0.107143 & 0.880952 & 0.214286 \tabularnewline
[100,100.5[ & 100.25 & 4 & 0.047619 & 0.928571 & 0.095238 \tabularnewline
[100.5,101] & 100.75 & 6 & 0.071429 & 1 & 0.142857 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292055&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][84,84.5[[/C][C]84.25[/C][C]2[/C][C]0.02381[/C][C]0.02381[/C][C]0.047619[/C][/ROW]
[ROW][C][84.5,85[[/C][C]84.75[/C][C]1[/C][C]0.011905[/C][C]0.035714[/C][C]0.02381[/C][/ROW]
[ROW][C][85,85.5[[/C][C]85.25[/C][C]0[/C][C]0[/C][C]0.035714[/C][C]0[/C][/ROW]
[ROW][C][85.5,86[[/C][C]85.75[/C][C]1[/C][C]0.011905[/C][C]0.047619[/C][C]0.02381[/C][/ROW]
[ROW][C][86,86.5[[/C][C]86.25[/C][C]2[/C][C]0.02381[/C][C]0.071429[/C][C]0.047619[/C][/ROW]
[ROW][C][86.5,87[[/C][C]86.75[/C][C]4[/C][C]0.047619[/C][C]0.119048[/C][C]0.095238[/C][/ROW]
[ROW][C][87,87.5[[/C][C]87.25[/C][C]4[/C][C]0.047619[/C][C]0.166667[/C][C]0.095238[/C][/ROW]
[ROW][C][87.5,88[[/C][C]87.75[/C][C]5[/C][C]0.059524[/C][C]0.22619[/C][C]0.119048[/C][/ROW]
[ROW][C][88,88.5[[/C][C]88.25[/C][C]3[/C][C]0.035714[/C][C]0.261905[/C][C]0.071429[/C][/ROW]
[ROW][C][88.5,89[[/C][C]88.75[/C][C]2[/C][C]0.02381[/C][C]0.285714[/C][C]0.047619[/C][/ROW]
[ROW][C][89,89.5[[/C][C]89.25[/C][C]4[/C][C]0.047619[/C][C]0.333333[/C][C]0.095238[/C][/ROW]
[ROW][C][89.5,90[[/C][C]89.75[/C][C]2[/C][C]0.02381[/C][C]0.357143[/C][C]0.047619[/C][/ROW]
[ROW][C][90,90.5[[/C][C]90.25[/C][C]0[/C][C]0[/C][C]0.357143[/C][C]0[/C][/ROW]
[ROW][C][90.5,91[[/C][C]90.75[/C][C]1[/C][C]0.011905[/C][C]0.369048[/C][C]0.02381[/C][/ROW]
[ROW][C][91,91.5[[/C][C]91.25[/C][C]1[/C][C]0.011905[/C][C]0.380952[/C][C]0.02381[/C][/ROW]
[ROW][C][91.5,92[[/C][C]91.75[/C][C]0[/C][C]0[/C][C]0.380952[/C][C]0[/C][/ROW]
[ROW][C][92,92.5[[/C][C]92.25[/C][C]2[/C][C]0.02381[/C][C]0.404762[/C][C]0.047619[/C][/ROW]
[ROW][C][92.5,93[[/C][C]92.75[/C][C]3[/C][C]0.035714[/C][C]0.440476[/C][C]0.071429[/C][/ROW]
[ROW][C][93,93.5[[/C][C]93.25[/C][C]1[/C][C]0.011905[/C][C]0.452381[/C][C]0.02381[/C][/ROW]
[ROW][C][93.5,94[[/C][C]93.75[/C][C]2[/C][C]0.02381[/C][C]0.47619[/C][C]0.047619[/C][/ROW]
[ROW][C][94,94.5[[/C][C]94.25[/C][C]3[/C][C]0.035714[/C][C]0.511905[/C][C]0.071429[/C][/ROW]
[ROW][C][94.5,95[[/C][C]94.75[/C][C]3[/C][C]0.035714[/C][C]0.547619[/C][C]0.071429[/C][/ROW]
[ROW][C][95,95.5[[/C][C]95.25[/C][C]1[/C][C]0.011905[/C][C]0.559524[/C][C]0.02381[/C][/ROW]
[ROW][C][95.5,96[[/C][C]95.75[/C][C]1[/C][C]0.011905[/C][C]0.571429[/C][C]0.02381[/C][/ROW]
[ROW][C][96,96.5[[/C][C]96.25[/C][C]4[/C][C]0.047619[/C][C]0.619048[/C][C]0.095238[/C][/ROW]
[ROW][C][96.5,97[[/C][C]96.75[/C][C]2[/C][C]0.02381[/C][C]0.642857[/C][C]0.047619[/C][/ROW]
[ROW][C][97,97.5[[/C][C]97.25[/C][C]3[/C][C]0.035714[/C][C]0.678571[/C][C]0.071429[/C][/ROW]
[ROW][C][97.5,98[[/C][C]97.75[/C][C]3[/C][C]0.035714[/C][C]0.714286[/C][C]0.071429[/C][/ROW]
[ROW][C][98,98.5[[/C][C]98.25[/C][C]2[/C][C]0.02381[/C][C]0.738095[/C][C]0.047619[/C][/ROW]
[ROW][C][98.5,99[[/C][C]98.75[/C][C]0[/C][C]0[/C][C]0.738095[/C][C]0[/C][/ROW]
[ROW][C][99,99.5[[/C][C]99.25[/C][C]3[/C][C]0.035714[/C][C]0.77381[/C][C]0.071429[/C][/ROW]
[ROW][C][99.5,100[[/C][C]99.75[/C][C]9[/C][C]0.107143[/C][C]0.880952[/C][C]0.214286[/C][/ROW]
[ROW][C][100,100.5[[/C][C]100.25[/C][C]4[/C][C]0.047619[/C][C]0.928571[/C][C]0.095238[/C][/ROW]
[ROW][C][100.5,101][/C][C]100.75[/C][C]6[/C][C]0.071429[/C][C]1[/C][C]0.142857[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292055&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
[84,84.5[84.2520.023810.023810.047619
[84.5,85[84.7510.0119050.0357140.02381
[85,85.5[85.25000.0357140
[85.5,86[85.7510.0119050.0476190.02381
[86,86.5[86.2520.023810.0714290.047619
[86.5,87[86.7540.0476190.1190480.095238
[87,87.5[87.2540.0476190.1666670.095238
[87.5,88[87.7550.0595240.226190.119048
[88,88.5[88.2530.0357140.2619050.071429
[88.5,89[88.7520.023810.2857140.047619
[89,89.5[89.2540.0476190.3333330.095238
[89.5,90[89.7520.023810.3571430.047619
[90,90.5[90.25000.3571430
[90.5,91[90.7510.0119050.3690480.02381
[91,91.5[91.2510.0119050.3809520.02381
[91.5,92[91.75000.3809520
[92,92.5[92.2520.023810.4047620.047619
[92.5,93[92.7530.0357140.4404760.071429
[93,93.5[93.2510.0119050.4523810.02381
[93.5,94[93.7520.023810.476190.047619
[94,94.5[94.2530.0357140.5119050.071429
[94.5,95[94.7530.0357140.5476190.071429
[95,95.5[95.2510.0119050.5595240.02381
[95.5,96[95.7510.0119050.5714290.02381
[96,96.5[96.2540.0476190.6190480.095238
[96.5,97[96.7520.023810.6428570.047619
[97,97.5[97.2530.0357140.6785710.071429
[97.5,98[97.7530.0357140.7142860.071429
[98,98.5[98.2520.023810.7380950.047619
[98.5,99[98.75000.7380950
[99,99.5[99.2530.0357140.773810.071429
[99.5,100[99.7590.1071430.8809520.214286
[100,100.5[100.2540.0476190.9285710.095238
[100.5,101]100.7560.07142910.142857



Parameters (Session):
par1 = 30 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 30 ; 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')
}