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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, 14 Dec 2016 13:56:40 +0100
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/Dec/14/t1481720434axuy2lzsi8r99cd.htm/, Retrieved Fri, 03 May 2024 19:49:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299386, Retrieved Fri, 03 May 2024 19:49:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram IVHB1] [2016-12-14 12:56:40] [dfff7639a5c2d8e28b3442052a637c76] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2
4
4
4
3
4
1
4
3
4
2
4
4
5
4
1
2
4
5
5
4
1
4
2
4
5
3
5
3
5
2
1
NA
4
4
3
5
4
NA
4
2
3
1
3
3
3
4
4
4
4
4
2
5
3
3
4
4
4
3
4
4
4
4
4
2
4
4
4
4
4
5
3
2
4
5
4
5
5
2
4
4
4
3
4
2
5
3
4
2
4
3
3
4
4
4
3
4
3
3
1
4
3
3
5
5
4
5
4
4
4
4
3
4
3
4
2
1
5
4
3
4
4
4
4
2
4
4
4
4
3
4
5
2
5
4
3
NA
2
2
2
4
4
5
3
3
4
4
4
4
4
4
4
2
5
4
4
4
4
4
2
3
3
4
4
4
4
3
3

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299386&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299386&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299386&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1,1.5[1.2570.0416670.0416670.084848
[1.5,2[1.75000.0416670
[2,2.5[2.25200.1190480.1607140.242424
[2.5,3[2.75000.1607140
[3,3.5[3.25330.1964290.3571430.4
[3.5,4[3.75000.3571430
[4,4.5[4.25840.50.8571431.018182
[4.5,5]4.75210.1250.9821430.254545

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1,1.5[ & 1.25 & 7 & 0.041667 & 0.041667 & 0.084848 \tabularnewline
[1.5,2[ & 1.75 & 0 & 0 & 0.041667 & 0 \tabularnewline
[2,2.5[ & 2.25 & 20 & 0.119048 & 0.160714 & 0.242424 \tabularnewline
[2.5,3[ & 2.75 & 0 & 0 & 0.160714 & 0 \tabularnewline
[3,3.5[ & 3.25 & 33 & 0.196429 & 0.357143 & 0.4 \tabularnewline
[3.5,4[ & 3.75 & 0 & 0 & 0.357143 & 0 \tabularnewline
[4,4.5[ & 4.25 & 84 & 0.5 & 0.857143 & 1.018182 \tabularnewline
[4.5,5] & 4.75 & 21 & 0.125 & 0.982143 & 0.254545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299386&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][1,1.5[[/C][C]1.25[/C][C]7[/C][C]0.041667[/C][C]0.041667[/C][C]0.084848[/C][/ROW]
[ROW][C][1.5,2[[/C][C]1.75[/C][C]0[/C][C]0[/C][C]0.041667[/C][C]0[/C][/ROW]
[ROW][C][2,2.5[[/C][C]2.25[/C][C]20[/C][C]0.119048[/C][C]0.160714[/C][C]0.242424[/C][/ROW]
[ROW][C][2.5,3[[/C][C]2.75[/C][C]0[/C][C]0[/C][C]0.160714[/C][C]0[/C][/ROW]
[ROW][C][3,3.5[[/C][C]3.25[/C][C]33[/C][C]0.196429[/C][C]0.357143[/C][C]0.4[/C][/ROW]
[ROW][C][3.5,4[[/C][C]3.75[/C][C]0[/C][C]0[/C][C]0.357143[/C][C]0[/C][/ROW]
[ROW][C][4,4.5[[/C][C]4.25[/C][C]84[/C][C]0.5[/C][C]0.857143[/C][C]1.018182[/C][/ROW]
[ROW][C][4.5,5][/C][C]4.75[/C][C]21[/C][C]0.125[/C][C]0.982143[/C][C]0.254545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299386&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299386&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
[1,1.5[1.2570.0416670.0416670.084848
[1.5,2[1.75000.0416670
[2,2.5[2.25200.1190480.1607140.242424
[2.5,3[2.75000.1607140
[3,3.5[3.25330.1964290.3571430.4
[3.5,4[3.75000.3571430
[4,4.5[4.25840.50.8571431.018182
[4.5,5]4.75210.1250.9821430.254545


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