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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 computationSat, 17 Dec 2016 12:44:36 +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/17/t1481975094uezk2ufpmbo78au.htm/, Retrieved Fri, 01 Nov 2024 03:39:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300722, Retrieved Fri, 01 Nov 2024 03:39:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [leeftijd enquete] [2016-12-17 11:44:36] [8263efc94e08b372ab727a2b95bd56b1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
22
24
21
21
24
20
22
20
19
23
21
19
19
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21
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18
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25
19
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26
19
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18
24
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25
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25
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19
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28
19
18
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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=300722&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=300722&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300722&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
[18,19[18.580.0481930.0481930.048193
[19,20[19.5350.2108430.2590360.210843
[20,21[20.5130.0783130.3373490.078313
[21,22[21.5470.2831330.6204820.283133
[22,23[22.5320.1927710.8132530.192771
[23,24[23.5180.1084340.9216870.108434
[24,25[24.580.0481930.969880.048193
[25,26[25.530.0180720.9879520.018072
[26,27[26.510.0060240.9939760.006024
[27,28]27.510.00602410.006024

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[18,19[ & 18.5 & 8 & 0.048193 & 0.048193 & 0.048193 \tabularnewline
[19,20[ & 19.5 & 35 & 0.210843 & 0.259036 & 0.210843 \tabularnewline
[20,21[ & 20.5 & 13 & 0.078313 & 0.337349 & 0.078313 \tabularnewline
[21,22[ & 21.5 & 47 & 0.283133 & 0.620482 & 0.283133 \tabularnewline
[22,23[ & 22.5 & 32 & 0.192771 & 0.813253 & 0.192771 \tabularnewline
[23,24[ & 23.5 & 18 & 0.108434 & 0.921687 & 0.108434 \tabularnewline
[24,25[ & 24.5 & 8 & 0.048193 & 0.96988 & 0.048193 \tabularnewline
[25,26[ & 25.5 & 3 & 0.018072 & 0.987952 & 0.018072 \tabularnewline
[26,27[ & 26.5 & 1 & 0.006024 & 0.993976 & 0.006024 \tabularnewline
[27,28] & 27.5 & 1 & 0.006024 & 1 & 0.006024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300722&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][18,19[[/C][C]18.5[/C][C]8[/C][C]0.048193[/C][C]0.048193[/C][C]0.048193[/C][/ROW]
[ROW][C][19,20[[/C][C]19.5[/C][C]35[/C][C]0.210843[/C][C]0.259036[/C][C]0.210843[/C][/ROW]
[ROW][C][20,21[[/C][C]20.5[/C][C]13[/C][C]0.078313[/C][C]0.337349[/C][C]0.078313[/C][/ROW]
[ROW][C][21,22[[/C][C]21.5[/C][C]47[/C][C]0.283133[/C][C]0.620482[/C][C]0.283133[/C][/ROW]
[ROW][C][22,23[[/C][C]22.5[/C][C]32[/C][C]0.192771[/C][C]0.813253[/C][C]0.192771[/C][/ROW]
[ROW][C][23,24[[/C][C]23.5[/C][C]18[/C][C]0.108434[/C][C]0.921687[/C][C]0.108434[/C][/ROW]
[ROW][C][24,25[[/C][C]24.5[/C][C]8[/C][C]0.048193[/C][C]0.96988[/C][C]0.048193[/C][/ROW]
[ROW][C][25,26[[/C][C]25.5[/C][C]3[/C][C]0.018072[/C][C]0.987952[/C][C]0.018072[/C][/ROW]
[ROW][C][26,27[[/C][C]26.5[/C][C]1[/C][C]0.006024[/C][C]0.993976[/C][C]0.006024[/C][/ROW]
[ROW][C][27,28][/C][C]27.5[/C][C]1[/C][C]0.006024[/C][C]1[/C][C]0.006024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300722&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300722&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
[18,19[18.580.0481930.0481930.048193
[19,20[19.5350.2108430.2590360.210843
[20,21[20.5130.0783130.3373490.078313
[21,22[21.5470.2831330.6204820.283133
[22,23[22.5320.1927710.8132530.192771
[23,24[23.5180.1084340.9216870.108434
[24,25[24.580.0481930.969880.048193
[25,26[25.530.0180720.9879520.018072
[26,27[26.510.0060240.9939760.006024
[27,28]27.510.00602410.006024


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
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')
}