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 computationSun, 14 Dec 2014 10:59:36 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418554792v6btxnivfn5p05u.htm/, Retrieved Thu, 16 May 2024 05:59:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267432, Retrieved Thu, 16 May 2024 05:59:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [paper] [2014-12-14 10:59:36] [9c0bd235307a1b4a36b3290850d9d0d3] [Current]
-    D    [Histogram] [paper] [2014-12-15 11:48:09] [074b0dbc8d3b700fa15927150828e345]
-    D    [Histogram] [paper] [2014-12-15 11:49:06] [074b0dbc8d3b700fa15927150828e345]
-    D    [Histogram] [paper] [2014-12-15 11:49:54] [074b0dbc8d3b700fa15927150828e345]
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Dataseries X:
11
15
19
16
24
15
17
19
19
28
26
15
26
16
24
25
22
15
21
22
27
26
26
22
21
22
20
21
20
22
21
8
22
18
20
24
17
20
23
20
22
19
15
20
22
17
14
24
17
23
25
16
18
20
18
23
24
23
13
20
20
19
22
22
15
17
19
20
22
21
21
16
20
21
20
23
15
18
22
16
17
24
13
19
20
22
19
21
15
21
24
22
20
21
19
14
25
11
17
22
20
22
15
23
20
22
16
25
18
19
25
21
22
21
22
23
20
6
15
18
24
22
21
23
20
20
18
25
16
20
14
22
26
20
17
22
22
20
17
22
17
22
21
25
11
19
24
17
22
22
17
26
19
20
19
21
24
21
19
13
24
28
27
22
23
19
18
23
21
22
17
15
21
20
26
19
28
21
19
22
21
20
19
11
17
19
20
17
21
21
12
23
22
22
21
20
18
21
24
22
20
17
19
16
19
23
8
22
23
15
17
21
25
18
23
20
21
21
24
22
22
23
17
15
24
22
19
18
21
20
19
19
16
18
23
22
23
20
24
25
25
20
23
21
23
23
11
21
27
19
21
16
22
21
22
16
18
23
24
20
20
18
4
14
22
17
23
20
18
19
20
15
24
21
19
19
27
23
23
20
17
21
23
22
16
20
16




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 0 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267432&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267432&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267432&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[4,6[510.0034840.0034840.001742
[6,8[710.0034840.0069690.001742
[8,10[920.0069690.0139370.003484
[10,12[1150.0174220.0313590.008711
[12,14[1340.0139370.0452960.006969
[14,16[15180.0627180.1080140.031359
[16,18[17330.1149830.2229970.057491
[18,20[19430.1498260.3728220.074913
[20,22[21720.2508710.6236930.125436
[22,24[23670.2334490.8571430.116725
[24,26[25270.0940770.951220.047038
[26,28]27140.0487810.02439

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4,6[ & 5 & 1 & 0.003484 & 0.003484 & 0.001742 \tabularnewline
[6,8[ & 7 & 1 & 0.003484 & 0.006969 & 0.001742 \tabularnewline
[8,10[ & 9 & 2 & 0.006969 & 0.013937 & 0.003484 \tabularnewline
[10,12[ & 11 & 5 & 0.017422 & 0.031359 & 0.008711 \tabularnewline
[12,14[ & 13 & 4 & 0.013937 & 0.045296 & 0.006969 \tabularnewline
[14,16[ & 15 & 18 & 0.062718 & 0.108014 & 0.031359 \tabularnewline
[16,18[ & 17 & 33 & 0.114983 & 0.222997 & 0.057491 \tabularnewline
[18,20[ & 19 & 43 & 0.149826 & 0.372822 & 0.074913 \tabularnewline
[20,22[ & 21 & 72 & 0.250871 & 0.623693 & 0.125436 \tabularnewline
[22,24[ & 23 & 67 & 0.233449 & 0.857143 & 0.116725 \tabularnewline
[24,26[ & 25 & 27 & 0.094077 & 0.95122 & 0.047038 \tabularnewline
[26,28] & 27 & 14 & 0.04878 & 1 & 0.02439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267432&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]1[/C][C]0.003484[/C][C]0.003484[/C][C]0.001742[/C][/ROW]
[ROW][C][6,8[[/C][C]7[/C][C]1[/C][C]0.003484[/C][C]0.006969[/C][C]0.001742[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]2[/C][C]0.006969[/C][C]0.013937[/C][C]0.003484[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]5[/C][C]0.017422[/C][C]0.031359[/C][C]0.008711[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]4[/C][C]0.013937[/C][C]0.045296[/C][C]0.006969[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]18[/C][C]0.062718[/C][C]0.108014[/C][C]0.031359[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]33[/C][C]0.114983[/C][C]0.222997[/C][C]0.057491[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]43[/C][C]0.149826[/C][C]0.372822[/C][C]0.074913[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]72[/C][C]0.250871[/C][C]0.623693[/C][C]0.125436[/C][/ROW]
[ROW][C][22,24[[/C][C]23[/C][C]67[/C][C]0.233449[/C][C]0.857143[/C][C]0.116725[/C][/ROW]
[ROW][C][24,26[[/C][C]25[/C][C]27[/C][C]0.094077[/C][C]0.95122[/C][C]0.047038[/C][/ROW]
[ROW][C][26,28][/C][C]27[/C][C]14[/C][C]0.04878[/C][C]1[/C][C]0.02439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267432&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267432&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[510.0034840.0034840.001742
[6,8[710.0034840.0069690.001742
[8,10[920.0069690.0139370.003484
[10,12[1150.0174220.0313590.008711
[12,14[1340.0139370.0452960.006969
[14,16[15180.0627180.1080140.031359
[16,18[17330.1149830.2229970.057491
[18,20[19430.1498260.3728220.074913
[20,22[21720.2508710.6236930.125436
[22,24[23670.2334490.8571430.116725
[24,26[25270.0940770.951220.047038
[26,28]27140.0487810.02439



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 {
plot(mytab <- table(x),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,hyperlink('histogram.htm','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')
}