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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 13 Dec 2012 03:16:26 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/13/t1355387164b7e2kaypjzrut72.htm/, Retrieved Sun, 28 Apr 2024 20:55:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199099, Retrieved Sun, 28 Apr 2024 20:55:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Verdeling Hapiness] [2012-12-13 08:16:26] [908f17a9de5f9a248c0a6ccff2e5399c] [Current]
- R       [Histogram] [Seperate Histogram] [2012-12-13 08:26:23] [c2ad4d8e77d85a93bcbf48e9e7fc0d94]
- R  D      [Histogram] [] [2012-12-13 08:39:34] [c2ad4d8e77d85a93bcbf48e9e7fc0d94]
- R  D    [Histogram] [Paper deel 1] [2012-12-13 08:28:45] [c2ad4d8e77d85a93bcbf48e9e7fc0d94]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
38
32
35
33
37
29
31
36
35
38
31
34
35
38
37
33
32
38
38
32
33
31
38
39
32
32
35
37
33
33
28
32
31
37
30
33
31
33
31
33
32
33
32
33
28
35
39
34
38
32
38
30
33
38
32
32
34
34
36
34
28
34
35
35
31
37
35
27
40
37
36
38
39
41
27
30
37
31
31
27
36
38
37
33
34
31
39
34
32
33
36
32
41
28
30
36
35
31
34
36
36
35
37
28
39
32
35
39
35
42
34
33
41
33
34
32
40
40
35
36
37
27
39
38
31
33
32
39
36
33
33
32
37
30
38
29
22
35
35
34
35
34
34
35
23
31
27
36
31
32
39
37
38
39
34
31
32
37
36
32
35
36

Tables (Output of Computation)





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=199099&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=199099&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199099&T=0

As an alternative you can also use a QR Code:  
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
[22,23[22.510.0061730.0061730.006173
[23,24[23.510.0061730.0123460.006173
[24,25[24.5000.0123460
[25,26[25.5000.0123460
[26,27[26.5000.0123460
[27,28[27.550.0308640.043210.030864
[28,29[28.550.0308640.0740740.030864
[29,30[29.520.0123460.086420.012346
[30,31[30.550.0308640.1172840.030864
[31,32[31.5150.0925930.2098770.092593
[32,33[32.5200.1234570.3333330.123457
[33,34[33.5180.1111110.4444440.111111
[34,35[34.5150.0925930.5370370.092593
[35,36[35.5180.1111110.6481480.111111
[36,37[36.5130.0802470.7283950.080247
[37,38[37.5130.0802470.8086420.080247
[38,39[38.5140.086420.8950620.08642
[39,40[39.5100.0617280.956790.061728
[40,41[40.530.0185190.9753090.018519
[41,42]41.540.02469110.024691

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[22,23[ & 22.5 & 1 & 0.006173 & 0.006173 & 0.006173 \tabularnewline
[23,24[ & 23.5 & 1 & 0.006173 & 0.012346 & 0.006173 \tabularnewline
[24,25[ & 24.5 & 0 & 0 & 0.012346 & 0 \tabularnewline
[25,26[ & 25.5 & 0 & 0 & 0.012346 & 0 \tabularnewline
[26,27[ & 26.5 & 0 & 0 & 0.012346 & 0 \tabularnewline
[27,28[ & 27.5 & 5 & 0.030864 & 0.04321 & 0.030864 \tabularnewline
[28,29[ & 28.5 & 5 & 0.030864 & 0.074074 & 0.030864 \tabularnewline
[29,30[ & 29.5 & 2 & 0.012346 & 0.08642 & 0.012346 \tabularnewline
[30,31[ & 30.5 & 5 & 0.030864 & 0.117284 & 0.030864 \tabularnewline
[31,32[ & 31.5 & 15 & 0.092593 & 0.209877 & 0.092593 \tabularnewline
[32,33[ & 32.5 & 20 & 0.123457 & 0.333333 & 0.123457 \tabularnewline
[33,34[ & 33.5 & 18 & 0.111111 & 0.444444 & 0.111111 \tabularnewline
[34,35[ & 34.5 & 15 & 0.092593 & 0.537037 & 0.092593 \tabularnewline
[35,36[ & 35.5 & 18 & 0.111111 & 0.648148 & 0.111111 \tabularnewline
[36,37[ & 36.5 & 13 & 0.080247 & 0.728395 & 0.080247 \tabularnewline
[37,38[ & 37.5 & 13 & 0.080247 & 0.808642 & 0.080247 \tabularnewline
[38,39[ & 38.5 & 14 & 0.08642 & 0.895062 & 0.08642 \tabularnewline
[39,40[ & 39.5 & 10 & 0.061728 & 0.95679 & 0.061728 \tabularnewline
[40,41[ & 40.5 & 3 & 0.018519 & 0.975309 & 0.018519 \tabularnewline
[41,42] & 41.5 & 4 & 0.024691 & 1 & 0.024691 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199099&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][22,23[[/C][C]22.5[/C][C]1[/C][C]0.006173[/C][C]0.006173[/C][C]0.006173[/C][/ROW]
[ROW][C][23,24[[/C][C]23.5[/C][C]1[/C][C]0.006173[/C][C]0.012346[/C][C]0.006173[/C][/ROW]
[ROW][C][24,25[[/C][C]24.5[/C][C]0[/C][C]0[/C][C]0.012346[/C][C]0[/C][/ROW]
[ROW][C][25,26[[/C][C]25.5[/C][C]0[/C][C]0[/C][C]0.012346[/C][C]0[/C][/ROW]
[ROW][C][26,27[[/C][C]26.5[/C][C]0[/C][C]0[/C][C]0.012346[/C][C]0[/C][/ROW]
[ROW][C][27,28[[/C][C]27.5[/C][C]5[/C][C]0.030864[/C][C]0.04321[/C][C]0.030864[/C][/ROW]
[ROW][C][28,29[[/C][C]28.5[/C][C]5[/C][C]0.030864[/C][C]0.074074[/C][C]0.030864[/C][/ROW]
[ROW][C][29,30[[/C][C]29.5[/C][C]2[/C][C]0.012346[/C][C]0.08642[/C][C]0.012346[/C][/ROW]
[ROW][C][30,31[[/C][C]30.5[/C][C]5[/C][C]0.030864[/C][C]0.117284[/C][C]0.030864[/C][/ROW]
[ROW][C][31,32[[/C][C]31.5[/C][C]15[/C][C]0.092593[/C][C]0.209877[/C][C]0.092593[/C][/ROW]
[ROW][C][32,33[[/C][C]32.5[/C][C]20[/C][C]0.123457[/C][C]0.333333[/C][C]0.123457[/C][/ROW]
[ROW][C][33,34[[/C][C]33.5[/C][C]18[/C][C]0.111111[/C][C]0.444444[/C][C]0.111111[/C][/ROW]
[ROW][C][34,35[[/C][C]34.5[/C][C]15[/C][C]0.092593[/C][C]0.537037[/C][C]0.092593[/C][/ROW]
[ROW][C][35,36[[/C][C]35.5[/C][C]18[/C][C]0.111111[/C][C]0.648148[/C][C]0.111111[/C][/ROW]
[ROW][C][36,37[[/C][C]36.5[/C][C]13[/C][C]0.080247[/C][C]0.728395[/C][C]0.080247[/C][/ROW]
[ROW][C][37,38[[/C][C]37.5[/C][C]13[/C][C]0.080247[/C][C]0.808642[/C][C]0.080247[/C][/ROW]
[ROW][C][38,39[[/C][C]38.5[/C][C]14[/C][C]0.08642[/C][C]0.895062[/C][C]0.08642[/C][/ROW]
[ROW][C][39,40[[/C][C]39.5[/C][C]10[/C][C]0.061728[/C][C]0.95679[/C][C]0.061728[/C][/ROW]
[ROW][C][40,41[[/C][C]40.5[/C][C]3[/C][C]0.018519[/C][C]0.975309[/C][C]0.018519[/C][/ROW]
[ROW][C][41,42][/C][C]41.5[/C][C]4[/C][C]0.024691[/C][C]1[/C][C]0.024691[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199099&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199099&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[22,23[22.510.0061730.0061730.006173
[23,24[23.510.0061730.0123460.006173
[24,25[24.5000.0123460
[25,26[25.5000.0123460
[26,27[26.5000.0123460
[27,28[27.550.0308640.043210.030864
[28,29[28.550.0308640.0740740.030864
[29,30[29.520.0123460.086420.012346
[30,31[30.550.0308640.1172840.030864
[31,32[31.5150.0925930.2098770.092593
[32,33[32.5200.1234570.3333330.123457
[33,34[33.5180.1111110.4444440.111111
[34,35[34.5150.0925930.5370370.092593
[35,36[35.5180.1111110.6481480.111111
[36,37[36.5130.0802470.7283950.080247
[37,38[37.5130.0802470.8086420.080247
[38,39[38.5140.086420.8950620.08642
[39,40[39.5100.0617280.956790.061728
[40,41[40.530.0185190.9753090.018519
[41,42]41.540.02469110.024691


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '50'
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')
}