Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 25 Sep 2013 17:00:32 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Sep/25/t1380142843cvtjl7tew8ryd7f.htm/, Retrieved Fri, 03 May 2024 10:34:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=212008, Retrieved Fri, 03 May 2024 10:34:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2013-09-25 20:22:51] [b18144ee792179a5b494368f415f5e94]
- RMP     [Histogram] [] [2013-09-25 21:00:32] [5084d5e36b1f8e83675c5d3d354927b3] [Current]
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Dataseries X:
1.94
1.82
1.8
1.79
1.79
1.78
1.81
1.84
1.87
1.87
1.87
1.84
1.82
1.83
1.83
1.82
1.83
1.87
1.88
1.9
1.98
2.03
2.14
2.42
2.73
2.84
2.85
2.94
3.06
3.24
3.18
3.01
2.87
2.73
2.63
2.39
2.26
2.11
2.01
1.99
1.96
1.93
1.98
2.07
2.24
2.31
2.23
2.26
2.28
2.3
2.33
2.26
2.24
2.47
2.55
2.89
3.21
3.21
2.92
2.68
2.4
2.28
2.24
2.2
2.18
2.23
2.24
2.25
2.23
2.25
2.23
2.21
2.17
2.17
2.13
2.12
2.13
2.17
2.33
2.5
2.57
2.59
2.58
2.31




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212008&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]3 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=212008&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212008&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1.7,1.8[1.7530.0357140.0357140.357143
[1.8,1.9[1.85150.1785710.2142861.785714
[1.9,2[1.9570.0833330.2976190.833333
[2,2.1[2.0530.0357140.3333330.357143
[2.1,2.2[2.1590.1071430.4404761.071429
[2.2,2.3[2.25170.2023810.6428572.02381
[2.3,2.4[2.3560.0714290.7142860.714286
[2.4,2.5[2.4530.0357140.750.357143
[2.5,2.6[2.5550.0595240.8095240.595238
[2.6,2.7[2.6520.023810.8333330.238095
[2.7,2.8[2.7520.023810.8571430.238095
[2.8,2.9[2.8540.0476190.9047620.47619
[2.9,3[2.9520.023810.9285710.238095
[3,3.1[3.0520.023810.9523810.238095
[3.1,3.2[3.1510.0119050.9642860.119048
[3.2,3.3]3.2530.03571410.357143

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1.7,1.8[ & 1.75 & 3 & 0.035714 & 0.035714 & 0.357143 \tabularnewline
[1.8,1.9[ & 1.85 & 15 & 0.178571 & 0.214286 & 1.785714 \tabularnewline
[1.9,2[ & 1.95 & 7 & 0.083333 & 0.297619 & 0.833333 \tabularnewline
[2,2.1[ & 2.05 & 3 & 0.035714 & 0.333333 & 0.357143 \tabularnewline
[2.1,2.2[ & 2.15 & 9 & 0.107143 & 0.440476 & 1.071429 \tabularnewline
[2.2,2.3[ & 2.25 & 17 & 0.202381 & 0.642857 & 2.02381 \tabularnewline
[2.3,2.4[ & 2.35 & 6 & 0.071429 & 0.714286 & 0.714286 \tabularnewline
[2.4,2.5[ & 2.45 & 3 & 0.035714 & 0.75 & 0.357143 \tabularnewline
[2.5,2.6[ & 2.55 & 5 & 0.059524 & 0.809524 & 0.595238 \tabularnewline
[2.6,2.7[ & 2.65 & 2 & 0.02381 & 0.833333 & 0.238095 \tabularnewline
[2.7,2.8[ & 2.75 & 2 & 0.02381 & 0.857143 & 0.238095 \tabularnewline
[2.8,2.9[ & 2.85 & 4 & 0.047619 & 0.904762 & 0.47619 \tabularnewline
[2.9,3[ & 2.95 & 2 & 0.02381 & 0.928571 & 0.238095 \tabularnewline
[3,3.1[ & 3.05 & 2 & 0.02381 & 0.952381 & 0.238095 \tabularnewline
[3.1,3.2[ & 3.15 & 1 & 0.011905 & 0.964286 & 0.119048 \tabularnewline
[3.2,3.3] & 3.25 & 3 & 0.035714 & 1 & 0.357143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=212008&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][1.7,1.8[[/C][C]1.75[/C][C]3[/C][C]0.035714[/C][C]0.035714[/C][C]0.357143[/C][/ROW]
[ROW][C][1.8,1.9[[/C][C]1.85[/C][C]15[/C][C]0.178571[/C][C]0.214286[/C][C]1.785714[/C][/ROW]
[ROW][C][1.9,2[[/C][C]1.95[/C][C]7[/C][C]0.083333[/C][C]0.297619[/C][C]0.833333[/C][/ROW]
[ROW][C][2,2.1[[/C][C]2.05[/C][C]3[/C][C]0.035714[/C][C]0.333333[/C][C]0.357143[/C][/ROW]
[ROW][C][2.1,2.2[[/C][C]2.15[/C][C]9[/C][C]0.107143[/C][C]0.440476[/C][C]1.071429[/C][/ROW]
[ROW][C][2.2,2.3[[/C][C]2.25[/C][C]17[/C][C]0.202381[/C][C]0.642857[/C][C]2.02381[/C][/ROW]
[ROW][C][2.3,2.4[[/C][C]2.35[/C][C]6[/C][C]0.071429[/C][C]0.714286[/C][C]0.714286[/C][/ROW]
[ROW][C][2.4,2.5[[/C][C]2.45[/C][C]3[/C][C]0.035714[/C][C]0.75[/C][C]0.357143[/C][/ROW]
[ROW][C][2.5,2.6[[/C][C]2.55[/C][C]5[/C][C]0.059524[/C][C]0.809524[/C][C]0.595238[/C][/ROW]
[ROW][C][2.6,2.7[[/C][C]2.65[/C][C]2[/C][C]0.02381[/C][C]0.833333[/C][C]0.238095[/C][/ROW]
[ROW][C][2.7,2.8[[/C][C]2.75[/C][C]2[/C][C]0.02381[/C][C]0.857143[/C][C]0.238095[/C][/ROW]
[ROW][C][2.8,2.9[[/C][C]2.85[/C][C]4[/C][C]0.047619[/C][C]0.904762[/C][C]0.47619[/C][/ROW]
[ROW][C][2.9,3[[/C][C]2.95[/C][C]2[/C][C]0.02381[/C][C]0.928571[/C][C]0.238095[/C][/ROW]
[ROW][C][3,3.1[[/C][C]3.05[/C][C]2[/C][C]0.02381[/C][C]0.952381[/C][C]0.238095[/C][/ROW]
[ROW][C][3.1,3.2[[/C][C]3.15[/C][C]1[/C][C]0.011905[/C][C]0.964286[/C][C]0.119048[/C][/ROW]
[ROW][C][3.2,3.3][/C][C]3.25[/C][C]3[/C][C]0.035714[/C][C]1[/C][C]0.357143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=212008&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=212008&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
[1.7,1.8[1.7530.0357140.0357140.357143
[1.8,1.9[1.85150.1785710.2142861.785714
[1.9,2[1.9570.0833330.2976190.833333
[2,2.1[2.0530.0357140.3333330.357143
[2.1,2.2[2.1590.1071430.4404761.071429
[2.2,2.3[2.25170.2023810.6428572.02381
[2.3,2.4[2.3560.0714290.7142860.714286
[2.4,2.5[2.4530.0357140.750.357143
[2.5,2.6[2.5550.0595240.8095240.595238
[2.6,2.7[2.6520.023810.8333330.238095
[2.7,2.8[2.7520.023810.8571430.238095
[2.8,2.9[2.8540.0476190.9047620.47619
[2.9,3[2.9520.023810.9285710.238095
[3,3.1[3.0520.023810.9523810.238095
[3.1,3.2[3.1510.0119050.9642860.119048
[3.2,3.3]3.2530.03571410.357143



Parameters (Session):
par1 = 14 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 14 ; 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 {
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')
}