Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 04 Feb 2015 17:44:25 +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/2015/Feb/04/t14230719325t79li1ehkw9ng4.htm/, Retrieved Sat, 18 May 2024 07:26:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=276646, Retrieved Sat, 18 May 2024 07:26:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [prijs tabak] [2015-02-04 17:44:25] [87e7ca6f558d0278e2a63754d8e5cb91] [Current]
Feedback Forum

Post a new message
Dataseries X:
73.97
73.97
73.97
73.97
73.97
73.97
73.96
74.44
75.43
75.77
75.82
75.85
75.85
75.85
77.95
82.07
84.82
85.08
85.34
85.65
85.65
85.72
85.73
85.73
85.73
85.73
85.74
86.32
87.59
87.81
87.87
87.94
87.96
88.01
88.01
88.01
88.01
88.01
88.59
89.43
89.63
89.73
89.88
89.89
89.9
89.91
89.86
90.07
90.17
90.17
90.28
90.87
92.05
92.1
92.16
92.22
92.25
92.29
92.29
92.29
92.29
92.29
91.95
91.82
92.16
92.31
92.33
92.4
92.54
92.49
92.54
92.58
92.58
92.39
92.33
93.59
95.51
95.99
96.22
97.2
98.54
99.64
100.23
100.17
100.28
100.44
100.54
100.64
103.27
104.31
104.97
106.42
108.17
108.68
109.15
109.19




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=276646&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=276646&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276646&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
[72,74[7370.0729170.0729170.036458
[74,76[7570.0729170.1458330.036458
[76,78[7710.0104170.156250.005208
[78,80[79000.156250
[80,82[81000.156250
[82,84[8310.0104170.1666670.005208
[84,86[85110.1145830.281250.057292
[86,88[8760.06250.343750.03125
[88,90[89140.1458330.4895830.072917
[90,92[9170.0729170.56250.036458
[92,94[93220.2291670.7916670.114583
[94,96[9520.0208330.81250.010417
[96,98[9720.0208330.8333330.010417
[98,100[9920.0208330.8541670.010417
[100,102[10160.06250.9166670.03125
[102,104[10310.0104170.9270830.005208
[104,106[10520.0208330.9479170.010417
[106,108[10710.0104170.9583330.005208
[108,110]10940.04166710.020833

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[72,74[ & 73 & 7 & 0.072917 & 0.072917 & 0.036458 \tabularnewline
[74,76[ & 75 & 7 & 0.072917 & 0.145833 & 0.036458 \tabularnewline
[76,78[ & 77 & 1 & 0.010417 & 0.15625 & 0.005208 \tabularnewline
[78,80[ & 79 & 0 & 0 & 0.15625 & 0 \tabularnewline
[80,82[ & 81 & 0 & 0 & 0.15625 & 0 \tabularnewline
[82,84[ & 83 & 1 & 0.010417 & 0.166667 & 0.005208 \tabularnewline
[84,86[ & 85 & 11 & 0.114583 & 0.28125 & 0.057292 \tabularnewline
[86,88[ & 87 & 6 & 0.0625 & 0.34375 & 0.03125 \tabularnewline
[88,90[ & 89 & 14 & 0.145833 & 0.489583 & 0.072917 \tabularnewline
[90,92[ & 91 & 7 & 0.072917 & 0.5625 & 0.036458 \tabularnewline
[92,94[ & 93 & 22 & 0.229167 & 0.791667 & 0.114583 \tabularnewline
[94,96[ & 95 & 2 & 0.020833 & 0.8125 & 0.010417 \tabularnewline
[96,98[ & 97 & 2 & 0.020833 & 0.833333 & 0.010417 \tabularnewline
[98,100[ & 99 & 2 & 0.020833 & 0.854167 & 0.010417 \tabularnewline
[100,102[ & 101 & 6 & 0.0625 & 0.916667 & 0.03125 \tabularnewline
[102,104[ & 103 & 1 & 0.010417 & 0.927083 & 0.005208 \tabularnewline
[104,106[ & 105 & 2 & 0.020833 & 0.947917 & 0.010417 \tabularnewline
[106,108[ & 107 & 1 & 0.010417 & 0.958333 & 0.005208 \tabularnewline
[108,110] & 109 & 4 & 0.041667 & 1 & 0.020833 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=276646&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][72,74[[/C][C]73[/C][C]7[/C][C]0.072917[/C][C]0.072917[/C][C]0.036458[/C][/ROW]
[ROW][C][74,76[[/C][C]75[/C][C]7[/C][C]0.072917[/C][C]0.145833[/C][C]0.036458[/C][/ROW]
[ROW][C][76,78[[/C][C]77[/C][C]1[/C][C]0.010417[/C][C]0.15625[/C][C]0.005208[/C][/ROW]
[ROW][C][78,80[[/C][C]79[/C][C]0[/C][C]0[/C][C]0.15625[/C][C]0[/C][/ROW]
[ROW][C][80,82[[/C][C]81[/C][C]0[/C][C]0[/C][C]0.15625[/C][C]0[/C][/ROW]
[ROW][C][82,84[[/C][C]83[/C][C]1[/C][C]0.010417[/C][C]0.166667[/C][C]0.005208[/C][/ROW]
[ROW][C][84,86[[/C][C]85[/C][C]11[/C][C]0.114583[/C][C]0.28125[/C][C]0.057292[/C][/ROW]
[ROW][C][86,88[[/C][C]87[/C][C]6[/C][C]0.0625[/C][C]0.34375[/C][C]0.03125[/C][/ROW]
[ROW][C][88,90[[/C][C]89[/C][C]14[/C][C]0.145833[/C][C]0.489583[/C][C]0.072917[/C][/ROW]
[ROW][C][90,92[[/C][C]91[/C][C]7[/C][C]0.072917[/C][C]0.5625[/C][C]0.036458[/C][/ROW]
[ROW][C][92,94[[/C][C]93[/C][C]22[/C][C]0.229167[/C][C]0.791667[/C][C]0.114583[/C][/ROW]
[ROW][C][94,96[[/C][C]95[/C][C]2[/C][C]0.020833[/C][C]0.8125[/C][C]0.010417[/C][/ROW]
[ROW][C][96,98[[/C][C]97[/C][C]2[/C][C]0.020833[/C][C]0.833333[/C][C]0.010417[/C][/ROW]
[ROW][C][98,100[[/C][C]99[/C][C]2[/C][C]0.020833[/C][C]0.854167[/C][C]0.010417[/C][/ROW]
[ROW][C][100,102[[/C][C]101[/C][C]6[/C][C]0.0625[/C][C]0.916667[/C][C]0.03125[/C][/ROW]
[ROW][C][102,104[[/C][C]103[/C][C]1[/C][C]0.010417[/C][C]0.927083[/C][C]0.005208[/C][/ROW]
[ROW][C][104,106[[/C][C]105[/C][C]2[/C][C]0.020833[/C][C]0.947917[/C][C]0.010417[/C][/ROW]
[ROW][C][106,108[[/C][C]107[/C][C]1[/C][C]0.010417[/C][C]0.958333[/C][C]0.005208[/C][/ROW]
[ROW][C][108,110][/C][C]109[/C][C]4[/C][C]0.041667[/C][C]1[/C][C]0.020833[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=276646&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=276646&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
[72,74[7370.0729170.0729170.036458
[74,76[7570.0729170.1458330.036458
[76,78[7710.0104170.156250.005208
[78,80[79000.156250
[80,82[81000.156250
[82,84[8310.0104170.1666670.005208
[84,86[85110.1145830.281250.057292
[86,88[8760.06250.343750.03125
[88,90[89140.1458330.4895830.072917
[90,92[9170.0729170.56250.036458
[92,94[93220.2291670.7916670.114583
[94,96[9520.0208330.81250.010417
[96,98[9720.0208330.8333330.010417
[98,100[9920.0208330.8541670.010417
[100,102[10160.06250.9166670.03125
[102,104[10310.0104170.9270830.005208
[104,106[10520.0208330.9479170.010417
[106,108[10710.0104170.9583330.005208
[108,110]10940.04166710.020833



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):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '5'
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')
}