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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 computationWed, 17 Dec 2014 20:04:08 +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/2014/Dec/17/t1418846660duo2d7nf8xz03v8.htm/, Retrieved Thu, 16 May 2024 15:49:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270635, Retrieved Thu, 16 May 2024 15:49:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Frequency Plot (B...] [2014-10-01 12:48:26] [1a6d42b46b3d01bc960fcfb45e99fecd]
-   PD  [Histogram] [leeftijd studenten] [2014-12-17 14:57:15] [be945163e51ed825733188af308451be]
-   PD      [Histogram] [age schakel] [2014-12-17 20:04:08] [88f8137dd67cdcd531568536dca46410] [Current]
- R P         [Histogram] [age bachelor] [2014-12-17 20:11:32] [be945163e51ed825733188af308451be]
- RMP         [Kernel Density Estimation] [] [2014-12-17 20:12:50] [be945163e51ed825733188af308451be]
-    D        [Histogram] [lfm] [2014-12-17 20:27:09] [be945163e51ed825733188af308451be]
- RMPD        [Kernel Density Estimation] [] [2014-12-17 20:28:13] [be945163e51ed825733188af308451be]
- RMPD        [Pearson Correlation] [] [2014-12-17 22:01:44] [be945163e51ed825733188af308451be]
-   PD        [Histogram] [] [2014-12-17 22:07:47] [be945163e51ed825733188af308451be]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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21
21
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21
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 0 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270635&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270635&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270635&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 time0 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20,20.5[20.2580.0563380.0563380.112676
[20.5,21[20.75000.0563380
[21,21.5[21.25680.4788730.5352110.957746
[21.5,22[21.75000.5352110
[22,22.5[22.25400.281690.8169010.56338
[22.5,23[22.75000.8169010
[23,23.5[23.25120.0845070.9014080.169014
[23.5,24[23.75000.9014080
[24,24.5[24.2570.0492960.9507040.098592
[24.5,25]24.7570.04929610.098592

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20,20.5[ & 20.25 & 8 & 0.056338 & 0.056338 & 0.112676 \tabularnewline
[20.5,21[ & 20.75 & 0 & 0 & 0.056338 & 0 \tabularnewline
[21,21.5[ & 21.25 & 68 & 0.478873 & 0.535211 & 0.957746 \tabularnewline
[21.5,22[ & 21.75 & 0 & 0 & 0.535211 & 0 \tabularnewline
[22,22.5[ & 22.25 & 40 & 0.28169 & 0.816901 & 0.56338 \tabularnewline
[22.5,23[ & 22.75 & 0 & 0 & 0.816901 & 0 \tabularnewline
[23,23.5[ & 23.25 & 12 & 0.084507 & 0.901408 & 0.169014 \tabularnewline
[23.5,24[ & 23.75 & 0 & 0 & 0.901408 & 0 \tabularnewline
[24,24.5[ & 24.25 & 7 & 0.049296 & 0.950704 & 0.098592 \tabularnewline
[24.5,25] & 24.75 & 7 & 0.049296 & 1 & 0.098592 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270635&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][20,20.5[[/C][C]20.25[/C][C]8[/C][C]0.056338[/C][C]0.056338[/C][C]0.112676[/C][/ROW]
[ROW][C][20.5,21[[/C][C]20.75[/C][C]0[/C][C]0[/C][C]0.056338[/C][C]0[/C][/ROW]
[ROW][C][21,21.5[[/C][C]21.25[/C][C]68[/C][C]0.478873[/C][C]0.535211[/C][C]0.957746[/C][/ROW]
[ROW][C][21.5,22[[/C][C]21.75[/C][C]0[/C][C]0[/C][C]0.535211[/C][C]0[/C][/ROW]
[ROW][C][22,22.5[[/C][C]22.25[/C][C]40[/C][C]0.28169[/C][C]0.816901[/C][C]0.56338[/C][/ROW]
[ROW][C][22.5,23[[/C][C]22.75[/C][C]0[/C][C]0[/C][C]0.816901[/C][C]0[/C][/ROW]
[ROW][C][23,23.5[[/C][C]23.25[/C][C]12[/C][C]0.084507[/C][C]0.901408[/C][C]0.169014[/C][/ROW]
[ROW][C][23.5,24[[/C][C]23.75[/C][C]0[/C][C]0[/C][C]0.901408[/C][C]0[/C][/ROW]
[ROW][C][24,24.5[[/C][C]24.25[/C][C]7[/C][C]0.049296[/C][C]0.950704[/C][C]0.098592[/C][/ROW]
[ROW][C][24.5,25][/C][C]24.75[/C][C]7[/C][C]0.049296[/C][C]1[/C][C]0.098592[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270635&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270635&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
[20,20.5[20.2580.0563380.0563380.112676
[20.5,21[20.75000.0563380
[21,21.5[21.25680.4788730.5352110.957746
[21.5,22[21.75000.5352110
[22,22.5[22.25400.281690.8169010.56338
[22.5,23[22.75000.8169010
[23,23.5[23.25120.0845070.9014080.169014
[23.5,24[23.75000.9014080
[24,24.5[24.2570.0492960.9507040.098592
[24.5,25]24.7570.04929610.098592


Figures (Output of Computation)

Input Parameters & R Code

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