Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationThu, 15 Dec 2016 20:11:34 +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/15/t1481829114pxwqxw18nwlxfbd.htm/, Retrieved Fri, 03 May 2024 07:17:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299968, Retrieved Fri, 03 May 2024 07:17:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram EPsum ] [2016-12-15 19:11:34] [c0b73e623858a81821526bb2f691ccd9] [Current]
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Dataseries X:
15
13
14
13
12
17
12
13
13
16
12
12
13
16
15
12
NA
NA
15
12
15
11
13
13
14
14
14
15
16
16
16
13
13
14
13
14
12
17
14
15
13
14
15
19
14
13
12
NA
14
15
15
12
14
11
12
10
NA
14
14
15
15
13
15
16
12
17
15
NA
12
16
15
15
12
13
10
14
11
12
14
12
14
12
13
13
14
12
15
13
13
11
12
16
11
13
12
17
14
15
8
13
13
15
14
13
14
12
19
15
14
14
15
13
15
14
11
17
13
9
12
13
17
14
13
16
14
14
14
10
12
13
14
18
14
14
13
13
16
NA
13
14
8
13
13
16
14
13
14
12
16
18
16
15
18
15
14
14
15
9
17
11
15
NA
15
13
NA
15
15
14
13




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299968&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299968&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299968&T=0

As an alternative you can also use a 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 time0 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[8,9[8.520.0118340.0118340.012422
[9,10[9.520.0118340.0236690.012422
[10,11[10.530.0177510.041420.018634
[11,12[11.570.041420.082840.043478
[12,13[12.5230.1360950.2189350.142857
[13,14[13.5350.2071010.4260360.217391
[14,15[14.5360.2130180.6390530.223602
[15,16[15.5280.165680.8047340.173913
[16,17[16.5130.0769230.8816570.080745
[17,18[17.570.041420.9230770.043478
[18,19]18.550.0295860.9526630.031056

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[8,9[ & 8.5 & 2 & 0.011834 & 0.011834 & 0.012422 \tabularnewline
[9,10[ & 9.5 & 2 & 0.011834 & 0.023669 & 0.012422 \tabularnewline
[10,11[ & 10.5 & 3 & 0.017751 & 0.04142 & 0.018634 \tabularnewline
[11,12[ & 11.5 & 7 & 0.04142 & 0.08284 & 0.043478 \tabularnewline
[12,13[ & 12.5 & 23 & 0.136095 & 0.218935 & 0.142857 \tabularnewline
[13,14[ & 13.5 & 35 & 0.207101 & 0.426036 & 0.217391 \tabularnewline
[14,15[ & 14.5 & 36 & 0.213018 & 0.639053 & 0.223602 \tabularnewline
[15,16[ & 15.5 & 28 & 0.16568 & 0.804734 & 0.173913 \tabularnewline
[16,17[ & 16.5 & 13 & 0.076923 & 0.881657 & 0.080745 \tabularnewline
[17,18[ & 17.5 & 7 & 0.04142 & 0.923077 & 0.043478 \tabularnewline
[18,19] & 18.5 & 5 & 0.029586 & 0.952663 & 0.031056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299968&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][8,9[[/C][C]8.5[/C][C]2[/C][C]0.011834[/C][C]0.011834[/C][C]0.012422[/C][/ROW]
[ROW][C][9,10[[/C][C]9.5[/C][C]2[/C][C]0.011834[/C][C]0.023669[/C][C]0.012422[/C][/ROW]
[ROW][C][10,11[[/C][C]10.5[/C][C]3[/C][C]0.017751[/C][C]0.04142[/C][C]0.018634[/C][/ROW]
[ROW][C][11,12[[/C][C]11.5[/C][C]7[/C][C]0.04142[/C][C]0.08284[/C][C]0.043478[/C][/ROW]
[ROW][C][12,13[[/C][C]12.5[/C][C]23[/C][C]0.136095[/C][C]0.218935[/C][C]0.142857[/C][/ROW]
[ROW][C][13,14[[/C][C]13.5[/C][C]35[/C][C]0.207101[/C][C]0.426036[/C][C]0.217391[/C][/ROW]
[ROW][C][14,15[[/C][C]14.5[/C][C]36[/C][C]0.213018[/C][C]0.639053[/C][C]0.223602[/C][/ROW]
[ROW][C][15,16[[/C][C]15.5[/C][C]28[/C][C]0.16568[/C][C]0.804734[/C][C]0.173913[/C][/ROW]
[ROW][C][16,17[[/C][C]16.5[/C][C]13[/C][C]0.076923[/C][C]0.881657[/C][C]0.080745[/C][/ROW]
[ROW][C][17,18[[/C][C]17.5[/C][C]7[/C][C]0.04142[/C][C]0.923077[/C][C]0.043478[/C][/ROW]
[ROW][C][18,19][/C][C]18.5[/C][C]5[/C][C]0.029586[/C][C]0.952663[/C][C]0.031056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299968&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299968&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[8,9[8.520.0118340.0118340.012422
[9,10[9.520.0118340.0236690.012422
[10,11[10.530.0177510.041420.018634
[11,12[11.570.041420.082840.043478
[12,13[12.5230.1360950.2189350.142857
[13,14[13.5350.2071010.4260360.217391
[14,15[14.5360.2130180.6390530.223602
[15,16[15.5280.165680.8047340.173913
[16,17[16.5130.0769230.8816570.080745
[17,18[17.570.041420.9230770.043478
[18,19]18.550.0295860.9526630.031056



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')
}