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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, 29 Nov 2017 11:59:37 +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/2017/Nov/29/t1511953266hjzzf28tc098z6s.htm/, Retrieved Fri, 24 May 2024 23:14:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308294, Retrieved Fri, 24 May 2024 23:14:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram_CarsDer...] [2017-11-29 10:59:37] [daf9a8d262d38e2e737ec3f2901e85ae] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13
0
6
0
0
1
3
6
0
0
5
1
1
2
6
1
0
0
0
7
4
4
0
4
1
0
5
0
3
2
0
3
0
0
1
0
4
0
0
0
0
0
4
0
0
5
20
4
1
0
1
10
3
0
1
4
4
16
5
0
1
1
0
4
0
1
0
2
0
0
6
16
1
1
3
1
35
0
2
0
4
0
3
8
4
0
0
0
1
1
1
0
9
1
2
0
0
3
1
0
8
0
5
0
0
1
0
2
4
1
0
0
0
1
2
0
3
1
1
1
0
1
0
1
1
0
2
2
0
22
4
0
25
0
6
7
10
2
0
0
0
0
0
2
3
7
0
6
0
0
0
0
3
8
0
6
3
3
6
1
0
2
0
25
14
0
0
0
1
1
0
1
2
10
0
0
12
0
0
0
3
29
0
1
5
9
6
1
5
2
5
0
1
1
9
9
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=308294&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=308294&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308294&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
[0,5[2.51560.7918780.7918780.158376
[5,10[7.5270.1370560.9289340.027411
[10,15[12.560.0304570.9593910.006091
[15,20[17.520.0101520.9695430.00203
[20,25[22.520.0101520.9796950.00203
[25,30[27.530.0152280.9949240.003046
[30,35]32.510.00507610.001015

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,5[ & 2.5 & 156 & 0.791878 & 0.791878 & 0.158376 \tabularnewline
[5,10[ & 7.5 & 27 & 0.137056 & 0.928934 & 0.027411 \tabularnewline
[10,15[ & 12.5 & 6 & 0.030457 & 0.959391 & 0.006091 \tabularnewline
[15,20[ & 17.5 & 2 & 0.010152 & 0.969543 & 0.00203 \tabularnewline
[20,25[ & 22.5 & 2 & 0.010152 & 0.979695 & 0.00203 \tabularnewline
[25,30[ & 27.5 & 3 & 0.015228 & 0.994924 & 0.003046 \tabularnewline
[30,35] & 32.5 & 1 & 0.005076 & 1 & 0.001015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308294&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][0,5[[/C][C]2.5[/C][C]156[/C][C]0.791878[/C][C]0.791878[/C][C]0.158376[/C][/ROW]
[ROW][C][5,10[[/C][C]7.5[/C][C]27[/C][C]0.137056[/C][C]0.928934[/C][C]0.027411[/C][/ROW]
[ROW][C][10,15[[/C][C]12.5[/C][C]6[/C][C]0.030457[/C][C]0.959391[/C][C]0.006091[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]2[/C][C]0.010152[/C][C]0.969543[/C][C]0.00203[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]2[/C][C]0.010152[/C][C]0.979695[/C][C]0.00203[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]3[/C][C]0.015228[/C][C]0.994924[/C][C]0.003046[/C][/ROW]
[ROW][C][30,35][/C][C]32.5[/C][C]1[/C][C]0.005076[/C][C]1[/C][C]0.001015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308294&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308294&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
[0,5[2.51560.7918780.7918780.158376
[5,10[7.5270.1370560.9289340.027411
[10,15[12.560.0304570.9593910.006091
[15,20[17.520.0101520.9695430.00203
[20,25[22.520.0101520.9796950.00203
[25,30[27.530.0152280.9949240.003046
[30,35]32.510.00507610.001015


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 {
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')
}