Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 23 Feb 2016 21:03:42 +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/23/t14562614561fhfcz01s1oqkup.htm/, Retrieved Mon, 06 May 2024 00:20:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292580, Retrieved Mon, 06 May 2024 00:20:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2016-02-17 19:00:39] [d7afde3e7059cd0a0fe09eec4b0008cd]
- RMPD    [Histogram] [] [2016-02-23 21:03:42] [1e8cb0485fd9b8c1cf436607044e417d] [Current]
Feedback Forum

Post a new message
Dataseries X:
92.86
94.06
95.51
96.05
96.71
97.91
97.74
97.64
98.55
98.46
99.19
99.18
99.95
100.66
101.12
101.14
100.73
99.92
100.06
100.64
100.89
100.87
100.72
100.72
100.98
100.15
100.13
100.39
99.87
99.93
99.96
99.61
99.57
99.71
99.78
99.92
100.3
100.83
100.84
97.87
97.99
98.03
97.58
97.45
97.47
98.31
98.29
98.13
98.44
98.05
98.32
97.55
97.74
98.01
97.93
99.23
101.03
100.81
100.57
100.1




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=292580&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=292580&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292580&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
[92.5,93[92.7510.0166670.0166670.033333
[93,93.5[93.25000.0166670
[93.5,94[93.75000.0166670
[94,94.5[94.2510.0166670.0333330.033333
[94.5,95[94.75000.0333330
[95,95.5[95.25000.0333330
[95.5,96[95.7510.0166670.050.033333
[96,96.5[96.2510.0166670.0666670.033333
[96.5,97[96.7510.0166670.0833330.033333
[97,97.5[97.2520.0333330.1166670.066667
[97.5,98[97.7590.150.2666670.3
[98,98.5[98.2590.150.4166670.3
[98.5,99[98.7510.0166670.4333330.033333
[99,99.5[99.2530.050.4833330.1
[99.5,100[99.75100.1666670.650.333333
[100,100.5[100.2560.10.750.2
[100.5,101[100.75120.20.950.4
[101,101.5]101.2530.0510.1

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[92.5,93[ & 92.75 & 1 & 0.016667 & 0.016667 & 0.033333 \tabularnewline
[93,93.5[ & 93.25 & 0 & 0 & 0.016667 & 0 \tabularnewline
[93.5,94[ & 93.75 & 0 & 0 & 0.016667 & 0 \tabularnewline
[94,94.5[ & 94.25 & 1 & 0.016667 & 0.033333 & 0.033333 \tabularnewline
[94.5,95[ & 94.75 & 0 & 0 & 0.033333 & 0 \tabularnewline
[95,95.5[ & 95.25 & 0 & 0 & 0.033333 & 0 \tabularnewline
[95.5,96[ & 95.75 & 1 & 0.016667 & 0.05 & 0.033333 \tabularnewline
[96,96.5[ & 96.25 & 1 & 0.016667 & 0.066667 & 0.033333 \tabularnewline
[96.5,97[ & 96.75 & 1 & 0.016667 & 0.083333 & 0.033333 \tabularnewline
[97,97.5[ & 97.25 & 2 & 0.033333 & 0.116667 & 0.066667 \tabularnewline
[97.5,98[ & 97.75 & 9 & 0.15 & 0.266667 & 0.3 \tabularnewline
[98,98.5[ & 98.25 & 9 & 0.15 & 0.416667 & 0.3 \tabularnewline
[98.5,99[ & 98.75 & 1 & 0.016667 & 0.433333 & 0.033333 \tabularnewline
[99,99.5[ & 99.25 & 3 & 0.05 & 0.483333 & 0.1 \tabularnewline
[99.5,100[ & 99.75 & 10 & 0.166667 & 0.65 & 0.333333 \tabularnewline
[100,100.5[ & 100.25 & 6 & 0.1 & 0.75 & 0.2 \tabularnewline
[100.5,101[ & 100.75 & 12 & 0.2 & 0.95 & 0.4 \tabularnewline
[101,101.5] & 101.25 & 3 & 0.05 & 1 & 0.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292580&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][92.5,93[[/C][C]92.75[/C][C]1[/C][C]0.016667[/C][C]0.016667[/C][C]0.033333[/C][/ROW]
[ROW][C][93,93.5[[/C][C]93.25[/C][C]0[/C][C]0[/C][C]0.016667[/C][C]0[/C][/ROW]
[ROW][C][93.5,94[[/C][C]93.75[/C][C]0[/C][C]0[/C][C]0.016667[/C][C]0[/C][/ROW]
[ROW][C][94,94.5[[/C][C]94.25[/C][C]1[/C][C]0.016667[/C][C]0.033333[/C][C]0.033333[/C][/ROW]
[ROW][C][94.5,95[[/C][C]94.75[/C][C]0[/C][C]0[/C][C]0.033333[/C][C]0[/C][/ROW]
[ROW][C][95,95.5[[/C][C]95.25[/C][C]0[/C][C]0[/C][C]0.033333[/C][C]0[/C][/ROW]
[ROW][C][95.5,96[[/C][C]95.75[/C][C]1[/C][C]0.016667[/C][C]0.05[/C][C]0.033333[/C][/ROW]
[ROW][C][96,96.5[[/C][C]96.25[/C][C]1[/C][C]0.016667[/C][C]0.066667[/C][C]0.033333[/C][/ROW]
[ROW][C][96.5,97[[/C][C]96.75[/C][C]1[/C][C]0.016667[/C][C]0.083333[/C][C]0.033333[/C][/ROW]
[ROW][C][97,97.5[[/C][C]97.25[/C][C]2[/C][C]0.033333[/C][C]0.116667[/C][C]0.066667[/C][/ROW]
[ROW][C][97.5,98[[/C][C]97.75[/C][C]9[/C][C]0.15[/C][C]0.266667[/C][C]0.3[/C][/ROW]
[ROW][C][98,98.5[[/C][C]98.25[/C][C]9[/C][C]0.15[/C][C]0.416667[/C][C]0.3[/C][/ROW]
[ROW][C][98.5,99[[/C][C]98.75[/C][C]1[/C][C]0.016667[/C][C]0.433333[/C][C]0.033333[/C][/ROW]
[ROW][C][99,99.5[[/C][C]99.25[/C][C]3[/C][C]0.05[/C][C]0.483333[/C][C]0.1[/C][/ROW]
[ROW][C][99.5,100[[/C][C]99.75[/C][C]10[/C][C]0.166667[/C][C]0.65[/C][C]0.333333[/C][/ROW]
[ROW][C][100,100.5[[/C][C]100.25[/C][C]6[/C][C]0.1[/C][C]0.75[/C][C]0.2[/C][/ROW]
[ROW][C][100.5,101[[/C][C]100.75[/C][C]12[/C][C]0.2[/C][C]0.95[/C][C]0.4[/C][/ROW]
[ROW][C][101,101.5][/C][C]101.25[/C][C]3[/C][C]0.05[/C][C]1[/C][C]0.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292580&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292580&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
[92.5,93[92.7510.0166670.0166670.033333
[93,93.5[93.25000.0166670
[93.5,94[93.75000.0166670
[94,94.5[94.2510.0166670.0333330.033333
[94.5,95[94.75000.0333330
[95,95.5[95.25000.0333330
[95.5,96[95.7510.0166670.050.033333
[96,96.5[96.2510.0166670.0666670.033333
[96.5,97[96.7510.0166670.0833330.033333
[97,97.5[97.2520.0333330.1166670.066667
[97.5,98[97.7590.150.2666670.3
[98,98.5[98.2590.150.4166670.3
[98.5,99[98.7510.0166670.4333330.033333
[99,99.5[99.2530.050.4833330.1
[99.5,100[99.75100.1666670.650.333333
[100,100.5[100.2560.10.750.2
[100.5,101[100.75120.20.950.4
[101,101.5]101.2530.0510.1



Parameters (Session):
par1 = 6 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 18 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '18'
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')
}