Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 12 Oct 2016 15:27:42 +0200
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/Oct/12/t1476278910sdsyg27j0cfjrqu.htm/, Retrieved Sun, 05 May 2024 12:24:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296651, Retrieved Sun, 05 May 2024 12:24:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2016-10-12 13:27:42] [93189e2c4c7b1a2c7b16a24d5daa98a9] [Current]
Feedback Forum

Post a new message
Dataseries X:
7
20
9
19
12
16
17
9
28
20
16
22
17
12
18
20
12
16
16
21
15
17
17
17
18
15
20
13
21
12
6
13
19
12
14
13
12
17
19
10
10
11
11
10
7
22
12
18
20
9
16
14
11
20
17
14
8
16
11
10
15
15
10
10
18
10
22
16
10
7
16
16
16
22
5
10
8
16
8
16
14
15
9
21
7
17
18
16
16
14
15
8
22
5
13
22
18
15
11
19
19
21
4
17
10
13
15
11
20
13
18
20
15
4
9
18
12
17
12
16
17
14
13
20
16
15
10
16
21
15
16
19
9
19
7
23
14
10
16
12
10
7
20
9
12
10
19
11
15
14
11
14
15
7
22
19
22
11
19
9
11
17
12
17
10
17
13
11
19
21
24
13
16
13
15
15
11
7
13
13
12
8
7
17
9
18
17
17
18
12
14
22
19
21
10
16
11
15
12
21
22
20
15
9
15
14
11
9
12
11
14
10
18
11
14
16
11
16
13
12
17
23
14
10
16
11
16
19
17
12
17
11
19
12
8
17
13
17
7
23
18
13
17
13
8
16
14
13
19
15
15
8
14
7
11
17
19
17
12
12
18
16
15
20
16
12
10
28
19
18
19
8
17
16
18
12
17
13




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=296651&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=296651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296651&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[4,6[540.0143880.0143880.007194
[6,8[7120.0431650.0575540.021583
[8,10[9200.0719420.1294960.035971
[10,12[11390.1402880.2697840.070144
[12,14[13410.1474820.4172660.073741
[14,16[15370.1330940.550360.066547
[16,18[17560.2014390.7517990.100719
[18,20[19330.1187050.8705040.059353
[20,22[21200.0719420.9424460.035971
[22,24[23130.0467630.9892090.023381
[24,26[2510.0035970.9928060.001799
[26,28]2720.00719410.003597

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4,6[ & 5 & 4 & 0.014388 & 0.014388 & 0.007194 \tabularnewline
[6,8[ & 7 & 12 & 0.043165 & 0.057554 & 0.021583 \tabularnewline
[8,10[ & 9 & 20 & 0.071942 & 0.129496 & 0.035971 \tabularnewline
[10,12[ & 11 & 39 & 0.140288 & 0.269784 & 0.070144 \tabularnewline
[12,14[ & 13 & 41 & 0.147482 & 0.417266 & 0.073741 \tabularnewline
[14,16[ & 15 & 37 & 0.133094 & 0.55036 & 0.066547 \tabularnewline
[16,18[ & 17 & 56 & 0.201439 & 0.751799 & 0.100719 \tabularnewline
[18,20[ & 19 & 33 & 0.118705 & 0.870504 & 0.059353 \tabularnewline
[20,22[ & 21 & 20 & 0.071942 & 0.942446 & 0.035971 \tabularnewline
[22,24[ & 23 & 13 & 0.046763 & 0.989209 & 0.023381 \tabularnewline
[24,26[ & 25 & 1 & 0.003597 & 0.992806 & 0.001799 \tabularnewline
[26,28] & 27 & 2 & 0.007194 & 1 & 0.003597 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296651&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][4,6[[/C][C]5[/C][C]4[/C][C]0.014388[/C][C]0.014388[/C][C]0.007194[/C][/ROW]
[ROW][C][6,8[[/C][C]7[/C][C]12[/C][C]0.043165[/C][C]0.057554[/C][C]0.021583[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]20[/C][C]0.071942[/C][C]0.129496[/C][C]0.035971[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]39[/C][C]0.140288[/C][C]0.269784[/C][C]0.070144[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]41[/C][C]0.147482[/C][C]0.417266[/C][C]0.073741[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]37[/C][C]0.133094[/C][C]0.55036[/C][C]0.066547[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]56[/C][C]0.201439[/C][C]0.751799[/C][C]0.100719[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]33[/C][C]0.118705[/C][C]0.870504[/C][C]0.059353[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]20[/C][C]0.071942[/C][C]0.942446[/C][C]0.035971[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]13[/C][C]0.046763[/C][C]0.989209[/C][C]0.023381[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]1[/C][C]0.003597[/C][C]0.992806[/C][C]0.001799[/C][/ROW]
[ROW][C][26,28][/C][C]27[/C][C]2[/C][C]0.007194[/C][C]1[/C][C]0.003597[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296651&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
[4,6[540.0143880.0143880.007194
[6,8[7120.0431650.0575540.021583
[8,10[9200.0719420.1294960.035971
[10,12[11390.1402880.2697840.070144
[12,14[13410.1474820.4172660.073741
[14,16[15370.1330940.550360.066547
[16,18[17560.2014390.7517990.100719
[18,20[19330.1187050.8705040.059353
[20,22[21200.0719420.9424460.035971
[22,24[23130.0467630.9892090.023381
[24,26[2510.0035970.9928060.001799
[26,28]2720.00719410.003597



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')
}