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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 computationMon, 12 Dec 2016 15:04:12 +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/12/t1481551497dhq3t8gh18mmx76.htm/, Retrieved Fri, 03 May 2024 23:04:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298907, Retrieved Fri, 03 May 2024 23:04:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [GMsum zonder 1] [2016-12-12 14:04:12] [8263efc94e08b372ab727a2b95bd56b1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9
8
10
NA
NA
10
9
NA
NA
9
10
9
13
11
10
8
NA
NA
6
NA
9
NA
10
NA
NA
NA
10
10
11
NA
9
7
11
NA
11
10
NA
10
10
9
NA
9
9
10
11
NA
NA
10
8
NA
10
NA
NA
4
NA
8
NA
13
10
NA
9
11
10
9
NA
NA
10
10
11
12
NA
NA
NA
NA
NA
10
10
8
10
9
NA
NA
10
11
NA
12
7
9
NA
11
8
NA
9
NA
9
11
9
7
NA
9
NA
12
NA
9
NA
NA
NA
NA
NA
9
NA
NA
NA
11
NA
7
11
NA
7
12
8
9
NA
9
NA
11
9
10
NA
NA
8
NA
9
NA
10
NA
13
NA
NA
11
9
8
9
10
NA
10
9
11
NA
NA
NA
11
8
8
7
NA
9
NA
NA
11
8
11
NA
NA
NA
NA
10
NA
9

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=298907&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=298907&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298907&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
[4,5[4.510.0059170.0059170.010101
[5,6[5.5000.0059170
[6,7[6.510.0059170.0118340.010101
[7,8[7.560.0355030.0473370.060606
[8,9[8.5120.0710060.1183430.121212
[9,10[9.5280.165680.2840240.282828
[10,11[10.5260.1538460.437870.262626
[11,12[11.5180.1065090.5443790.181818
[12,13]12.570.041420.5857990.070707

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4,5[ & 4.5 & 1 & 0.005917 & 0.005917 & 0.010101 \tabularnewline
[5,6[ & 5.5 & 0 & 0 & 0.005917 & 0 \tabularnewline
[6,7[ & 6.5 & 1 & 0.005917 & 0.011834 & 0.010101 \tabularnewline
[7,8[ & 7.5 & 6 & 0.035503 & 0.047337 & 0.060606 \tabularnewline
[8,9[ & 8.5 & 12 & 0.071006 & 0.118343 & 0.121212 \tabularnewline
[9,10[ & 9.5 & 28 & 0.16568 & 0.284024 & 0.282828 \tabularnewline
[10,11[ & 10.5 & 26 & 0.153846 & 0.43787 & 0.262626 \tabularnewline
[11,12[ & 11.5 & 18 & 0.106509 & 0.544379 & 0.181818 \tabularnewline
[12,13] & 12.5 & 7 & 0.04142 & 0.585799 & 0.070707 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298907&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][4,5[[/C][C]4.5[/C][C]1[/C][C]0.005917[/C][C]0.005917[/C][C]0.010101[/C][/ROW]
[ROW][C][5,6[[/C][C]5.5[/C][C]0[/C][C]0[/C][C]0.005917[/C][C]0[/C][/ROW]
[ROW][C][6,7[[/C][C]6.5[/C][C]1[/C][C]0.005917[/C][C]0.011834[/C][C]0.010101[/C][/ROW]
[ROW][C][7,8[[/C][C]7.5[/C][C]6[/C][C]0.035503[/C][C]0.047337[/C][C]0.060606[/C][/ROW]
[ROW][C][8,9[[/C][C]8.5[/C][C]12[/C][C]0.071006[/C][C]0.118343[/C][C]0.121212[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]28[/C][C]0.16568[/C][C]0.284024[/C][C]0.282828[/C][/ROW]
[ROW][C][10,11[[/C][C]10.5[/C][C]26[/C][C]0.153846[/C][C]0.43787[/C][C]0.262626[/C][/ROW]
[ROW][C][11,12[[/C][C]11.5[/C][C]18[/C][C]0.106509[/C][C]0.544379[/C][C]0.181818[/C][/ROW]
[ROW][C][12,13][/C][C]12.5[/C][C]7[/C][C]0.04142[/C][C]0.585799[/C][C]0.070707[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298907&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298907&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
[4,5[4.510.0059170.0059170.010101
[5,6[5.5000.0059170
[6,7[6.510.0059170.0118340.010101
[7,8[7.560.0355030.0473370.060606
[8,9[8.5120.0710060.1183430.121212
[9,10[9.5280.165680.2840240.282828
[10,11[10.5260.1538460.437870.262626
[11,12[11.5180.1065090.5443790.181818
[12,13]12.570.041420.5857990.070707


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 20 ; par2 = greygreygreygreygrey ; par3 = FALSEFALSEFALSEFALSEFALSE ; par4 = 5-point LikertUnknownUnknownUnknownUnknown ;
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')
}