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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 computationFri, 08 Dec 2017 21:24:28 +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/08/t1512764779siijt0tkdz9lbxw.htm/, Retrieved Tue, 14 May 2024 12:48:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308824, Retrieved Tue, 14 May 2024 12:48:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact57

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Frequentie tabel ...] [2017-12-08 20:24:28] [624f75095443dc501dbf5befeca42dec] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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'31'
'31'

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=308824&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=308824&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308824&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 (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
91200.0458
51060.0404
101020.0389
2990.0378
8980.0374
1940.0359
17940.0359
15930.0355
11910.0347
16910.0347
24890.034
27890.034
14870.0332
20870.0332
18840.032
19840.032
6840.032
22830.0317
28820.0313
26810.0309
3810.0309
21800.0305
4800.0305
25780.0298
12770.0294
7770.0294
29700.0267
23690.0263
13630.024
30620.0237
31460.0176

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
9 & 120 & 0.0458 \tabularnewline
5 & 106 & 0.0404 \tabularnewline
10 & 102 & 0.0389 \tabularnewline
2 & 99 & 0.0378 \tabularnewline
8 & 98 & 0.0374 \tabularnewline
1 & 94 & 0.0359 \tabularnewline
17 & 94 & 0.0359 \tabularnewline
15 & 93 & 0.0355 \tabularnewline
11 & 91 & 0.0347 \tabularnewline
16 & 91 & 0.0347 \tabularnewline
24 & 89 & 0.034 \tabularnewline
27 & 89 & 0.034 \tabularnewline
14 & 87 & 0.0332 \tabularnewline
20 & 87 & 0.0332 \tabularnewline
18 & 84 & 0.032 \tabularnewline
19 & 84 & 0.032 \tabularnewline
6 & 84 & 0.032 \tabularnewline
22 & 83 & 0.0317 \tabularnewline
28 & 82 & 0.0313 \tabularnewline
26 & 81 & 0.0309 \tabularnewline
3 & 81 & 0.0309 \tabularnewline
21 & 80 & 0.0305 \tabularnewline
4 & 80 & 0.0305 \tabularnewline
25 & 78 & 0.0298 \tabularnewline
12 & 77 & 0.0294 \tabularnewline
7 & 77 & 0.0294 \tabularnewline
29 & 70 & 0.0267 \tabularnewline
23 & 69 & 0.0263 \tabularnewline
13 & 63 & 0.024 \tabularnewline
30 & 62 & 0.0237 \tabularnewline
31 & 46 & 0.0176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308824&T=1

[TABLE]
[ROW][C]Frequency Table (Categorical Data)[/C][/ROW]
[ROW][C]Category[/C][C]Abs. Frequency[/C][C]Rel. Frequency[/C][/ROW]
[ROW][C]9[/C][C]120[/C][C]0.0458[/C][/ROW]
[ROW][C]5[/C][C]106[/C][C]0.0404[/C][/ROW]
[ROW][C]10[/C][C]102[/C][C]0.0389[/C][/ROW]
[ROW][C]2[/C][C]99[/C][C]0.0378[/C][/ROW]
[ROW][C]8[/C][C]98[/C][C]0.0374[/C][/ROW]
[ROW][C]1[/C][C]94[/C][C]0.0359[/C][/ROW]
[ROW][C]17[/C][C]94[/C][C]0.0359[/C][/ROW]
[ROW][C]15[/C][C]93[/C][C]0.0355[/C][/ROW]
[ROW][C]11[/C][C]91[/C][C]0.0347[/C][/ROW]
[ROW][C]16[/C][C]91[/C][C]0.0347[/C][/ROW]
[ROW][C]24[/C][C]89[/C][C]0.034[/C][/ROW]
[ROW][C]27[/C][C]89[/C][C]0.034[/C][/ROW]
[ROW][C]14[/C][C]87[/C][C]0.0332[/C][/ROW]
[ROW][C]20[/C][C]87[/C][C]0.0332[/C][/ROW]
[ROW][C]18[/C][C]84[/C][C]0.032[/C][/ROW]
[ROW][C]19[/C][C]84[/C][C]0.032[/C][/ROW]
[ROW][C]6[/C][C]84[/C][C]0.032[/C][/ROW]
[ROW][C]22[/C][C]83[/C][C]0.0317[/C][/ROW]
[ROW][C]28[/C][C]82[/C][C]0.0313[/C][/ROW]
[ROW][C]26[/C][C]81[/C][C]0.0309[/C][/ROW]
[ROW][C]3[/C][C]81[/C][C]0.0309[/C][/ROW]
[ROW][C]21[/C][C]80[/C][C]0.0305[/C][/ROW]
[ROW][C]4[/C][C]80[/C][C]0.0305[/C][/ROW]
[ROW][C]25[/C][C]78[/C][C]0.0298[/C][/ROW]
[ROW][C]12[/C][C]77[/C][C]0.0294[/C][/ROW]
[ROW][C]7[/C][C]77[/C][C]0.0294[/C][/ROW]
[ROW][C]29[/C][C]70[/C][C]0.0267[/C][/ROW]
[ROW][C]23[/C][C]69[/C][C]0.0263[/C][/ROW]
[ROW][C]13[/C][C]63[/C][C]0.024[/C][/ROW]
[ROW][C]30[/C][C]62[/C][C]0.0237[/C][/ROW]
[ROW][C]31[/C][C]46[/C][C]0.0176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308824&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308824&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 (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
91200.0458
51060.0404
101020.0389
2990.0378
8980.0374
1940.0359
17940.0359
15930.0355
11910.0347
16910.0347
24890.034
27890.034
14870.0332
20870.0332
18840.032
19840.032
6840.032
22830.0317
28820.0313
26810.0309
3810.0309
21800.0305
4800.0305
25780.0298
12770.0294
7770.0294
29700.0267
23690.0263
13630.024
30620.0237
31460.0176


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 31 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 31 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '31'
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')
}