FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationThu, 07 Dec 2017 13:13:01 +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/2017/Dec/07/t1512648818jfe6dzcmbp4q4mc.htm/, Retrieved Wed, 15 May 2024 18:11:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308700, Retrieved Wed, 15 May 2024 18:11:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Histogram Schakel] [2017-12-07 12:13:01] [0553ded3e3c4af9d05e2b3f12829db4c] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
17
19
14
11
18
13
18
12
19
18
17
15
10
13
15
13
16
17
13
15
19
14
20
20
18
17
19
21
21
15
15
19
16
18
15
15
21
16
12
15
15
14
16
16
20
20
20
20
14
21
5
19
21
19
11
20
18
16
13
18
15
19
16
18
13
17
19
20
15
15
14
15
16
18
22
16
16
20
16
15
18
18
20
18
16
21
20
14
20
15
18
16
15
19
20
19
17
19
12
15
16
19
18
18
21
22
17
19
18
20
16
16
16
16
19
17
18
18
16
19
21
18
18
14
21
19
18
17
12
17
17
21
13
20
19
12
17
10
10
16
17
15
15
20
12
15
17
15
12
11
16
16
15
20
16
16
17
19
11
20
13
14
20
19
17
19
15
13
19
19
18
21
19
16
18
11
18
13
9
19
13
18
10
18
17
16
24
15
14
22
16
11
18
15
20
14
15
12
11
15
15
20
20
16
22
17
21
23
21
22
18
17
20
20
15
19
19
20
20
17
18
21
19
18
22
20
17
16
17
15
17
18
18
20
19
20
22
22
23
23
21
16
18
22
18
12
17
18
15
16
19
23
21
21
24
18
19
22
19
15
18
18
20
17
24
16
16
17
23

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=308700&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=308700&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308700&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
[4,6[510.0037170.0037170.001859
[6,8[7000.0037170
[8,10[910.0037170.0074350.001859
[10,12[11110.0408920.0483270.020446
[12,14[13200.0743490.1226770.037175
[14,16[15420.1561340.278810.078067
[16,18[17590.2193310.4981410.109665
[18,20[19700.2602230.7583640.130112
[20,22[21470.1747210.9330860.087361
[22,24]23180.06691410.033457

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[4,6[ & 5 & 1 & 0.003717 & 0.003717 & 0.001859 \tabularnewline
[6,8[ & 7 & 0 & 0 & 0.003717 & 0 \tabularnewline
[8,10[ & 9 & 1 & 0.003717 & 0.007435 & 0.001859 \tabularnewline
[10,12[ & 11 & 11 & 0.040892 & 0.048327 & 0.020446 \tabularnewline
[12,14[ & 13 & 20 & 0.074349 & 0.122677 & 0.037175 \tabularnewline
[14,16[ & 15 & 42 & 0.156134 & 0.27881 & 0.078067 \tabularnewline
[16,18[ & 17 & 59 & 0.219331 & 0.498141 & 0.109665 \tabularnewline
[18,20[ & 19 & 70 & 0.260223 & 0.758364 & 0.130112 \tabularnewline
[20,22[ & 21 & 47 & 0.174721 & 0.933086 & 0.087361 \tabularnewline
[22,24] & 23 & 18 & 0.066914 & 1 & 0.033457 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308700&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]0.003717[/C][C]0.003717[/C][C]0.001859[/C][/ROW]
[ROW][C][6,8[[/C][C]7[/C][C]0[/C][C]0[/C][C]0.003717[/C][C]0[/C][/ROW]
[ROW][C][8,10[[/C][C]9[/C][C]1[/C][C]0.003717[/C][C]0.007435[/C][C]0.001859[/C][/ROW]
[ROW][C][10,12[[/C][C]11[/C][C]11[/C][C]0.040892[/C][C]0.048327[/C][C]0.020446[/C][/ROW]
[ROW][C][12,14[[/C][C]13[/C][C]20[/C][C]0.074349[/C][C]0.122677[/C][C]0.037175[/C][/ROW]
[ROW][C][14,16[[/C][C]15[/C][C]42[/C][C]0.156134[/C][C]0.27881[/C][C]0.078067[/C][/ROW]
[ROW][C][16,18[[/C][C]17[/C][C]59[/C][C]0.219331[/C][C]0.498141[/C][C]0.109665[/C][/ROW]
[ROW][C][18,20[[/C][C]19[/C][C]70[/C][C]0.260223[/C][C]0.758364[/C][C]0.130112[/C][/ROW]
[ROW][C][20,22[[/C][C]21[/C][C]47[/C][C]0.174721[/C][C]0.933086[/C][C]0.087361[/C][/ROW]
[ROW][C][22,24][/C][C]23[/C][C]18[/C][C]0.066914[/C][C]1[/C][C]0.033457[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308700&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308700&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
[4,6[510.0037170.0037170.001859
[6,8[7000.0037170
[8,10[910.0037170.0074350.001859
[10,12[11110.0408920.0483270.020446
[12,14[13200.0743490.1226770.037175
[14,16[15420.1561340.278810.078067
[16,18[17590.2193310.4981410.109665
[18,20[19700.2602230.7583640.130112
[20,22[21470.1747210.9330860.087361
[22,24]23180.06691410.033457


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ; 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')
}