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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, 04 Dec 2015 19:10:13 +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/2015/Dec/04/t1449256228t4u8i9tlpwgmwpp.htm/, Retrieved Thu, 16 May 2024 10:03:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285176, Retrieved Thu, 16 May 2024 10:03:53 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2015-12-04 19:10:13] [5d6876d49f009ca238d980a5298af888] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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'27'
'39'
'6'
'17'
'10'
'11'
'26'
'14'
'36'
'23'
'38'
'39'
'29'
'4'
'26'
'24'
'7'
'27'
'1'
'30'
'17'
'40'
'7'
'30'
'32'
'9'
'16'
'37'
'6'
'16'
'29'
'2'
'40'
'1'
'22'
'8'
'10'
'32'
'24'
'38'
'38'
'12'
'36'
'33'
'6'
'7'
'7'
'23'
'19'
'40'
'6'
'4'
'2'
'35'
'9'
'33'
'7'
'4'
'10'
'12'
'25'
'25'
'1'
'33'
'19'
'19'
'27'
'1'
'15'
'11'
'42'
'34'
'41'
'7'
'3'
'29'
'42'
'3'
'10'
'15'
'27'
'24'
'10'
'6'
'5'
'20'
'39'
'42'
'20'
'13'
'9'
'3'
'20'
'33'
'42'
'31'
'17'
'42'
'32'
'26'
'22'
'5'
'1'
'24'
'12'
'24'
'23'
'39'
'24'
'33'
'16'
'25'
'14'
'37'
'12'
'34'
'37'
'3'
'35'
'9'
'36'
'25'
'10'
'4'
'16'
'8'
'3'
'1'
'16'
'22'
'12'
'37'
'18'
'30'
'9'
'38'
'7'
'5'
'13'
'21'
'13'
'12'
'37'
'14'
'14'
'8'
'30'
'17'
'33'
'26'
'22'
'23'
'1'
'25'
'9'
'30'
'42'
'11'
'4'
'22'
'39'
'22'
'6'
'8'
'26'
'5'
'20'
'37'
'32'
'37'
'28'
'13'
'15'
'2'
'17'
'19'
'37'
'36'
'2'
'11'
'29'
'17'
'36'
'4'
'4'
'19'
'20'
'5'
'3'
'19'
'5'
'15'
'8'
'19'
'16'
'27'
'22'
'1'
'4'
'23'
'31'
'28'
'3'
'2'
'2'
'31'
'33'
'19'
'7'
'17'
'6'
'23'
'7'
'1'
'26'
'16'
'29'
'12'
'31'
'27'
'22'
'2'
'24'
'13'
'12'
'34'
'21'
'23'
'39'
'26'
'21'
'14'
'18'
'16'
'21'
'37'
'7'
'4'
'36'
'1'
'26'
'22'
'20'
'11'
'41'
'3'
'5'
'16'
'21'
'34'
'40'
'40'
'30'
'30'
'29'
'19'
'13'
'39'
'3'
'23'
'23'
'13'
'11'
'3'
'24'
'30'
'17'
'38'
'32'
'16'
'24'
'35'
'24'
'33'
'21'
'13'
'33'
'23'
'5'
'21'
'24'
'30'
'7'
'25'
'20'
'38'
'23'
'1'
'41'
'26'
'12'
'27'
'10'
'12'
'12'
'22'
'2'
'15'
'23'
'29'
'27'
'42'
'7'
'22'
'36'
'39'
'25'
'23'
'38'
'14'
'12'
'24'
'22'
'6'
'36'
'20'
'16'
'15'
'22'
'13'
'30'
'19'
'41'
'34'
'40'
'30'
'11'
'20'
'12'
'19'
'25'
'2'
'34'
'5'
'6'
'1'
'32'
'20'
'11'
'14'
'41'
'34'
'23'
'34'
'40'
'23'
'30'
'4'
'10'
'27'
'6'
'24'
'28'
'6'
'2'
'1'
'28'
'21'
'17'
'9'
'3'
'19'
'40'
'2'
'12'
'41'
'36'
'22'
'39'
'32'
'41'
'1'
'6'
'37'
'15'
'34'
'5'
'17'
'4'
'10'
'4'
'41'
'26'
'25'
'34'
'5'
'20'
'31'
'41'
'27'
'30'
'20'
'7'
'38'
'24'
'9'
'17'
'23'
'23'
'24'
'1'
'17'
'8'
'31'
'4'
'41'
'1'
'13'
'7'
'14'
'29'
'3'
'24'
'24'
'6'
'21'
'30'
'21'
'34'
'19'
'38'
'31'
'26'
'8'
'36'
'8'
'25'
'2'
'16'
'38'
'8'
'19'
'24'
'42'
'13'
'39'
'23'
'30'
'24'
'15'
'42'
'27'
'35'
'18'
'2'
'30'
'38'
'33'
'33'
'6'
'12'
'25'
'14'
'22'
'20'
'22'
'8'
'16'
'21'
'18'
'19'
'14'
'23'
'23'
'6'
'33'
'33'
'6'
'32'
'24'
'32'
'22'
'41'
'23'
'24'
'17'
'9'
'39'
'22'
'40'
'11'
'21'
'12'
'29'
'16'
'10'
'42'
'21'
'5'
'26'
'18'
'21'
'37'
'39'
'1'
'27'
'29'
'7'
'15'
'30'
'34'
'9'
'24'
'26'
'24'
'41'
'23'
'26'
'38'
'14'
'27'
'1'
'22'
'12'
'12'
'9'
'26'
'23'
'24'
'18'
'38'
'39'
'8'
'33'
'6'
'5'
'11'
'30'
'41'
'32'
'18'
'19'
'22'
'6'
'32'
'36'
'8'
'27'
'2'
'26'
'8'
'38'
'26'
'3'
'17'
'39'
'14'
'10'
'42'
'31'
'33'
'4'
'37'
'20'
'1'
'9'
'32'
'14'
'28'
'30'
'33'
'12'
'20'
'9'
'33'
'9'
'20'
'23'
'32'
'21'
'42'
'3'
'11'
'12'
'15'
'12'
'37'
'19'
'7'
'32'
'34'
'7'
'42'
'28'
'32'
'27'
'9'
'23'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time49 seconds
R Server'George Udny Yule' @ yule.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 & 49 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285176&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]49 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285176&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285176&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time49 seconds
R Server'George Udny Yule' @ yule.wessa.net






Frequency Table (Categorical Data)
CategoryAbs. FrequencyRel. Frequency
223620.0266
123570.0262
53560.0262
73490.0257
163470.0255
233470.0255
93430.0252
243420.0251
383380.0249
253360.0247
193350.0246
343320.0244
23310.0243
143300.0243
293300.0243
43290.0242
13280.0241
413280.0241
103270.024
33250.0239
423250.0239
333230.0237
133220.0237
363210.0236
63210.0236
283200.0235
373200.0235
213190.0235
263180.0234
273150.0232
303140.0231
173100.0228
403100.0228
113090.0227
323050.0224
203030.0223
353020.0222
313010.0221
82990.022
182970.0218
392950.0217
152800.0206

\begin{tabular}{lllllllll}
\hline
Frequency Table (Categorical Data) \tabularnewline
Category & Abs. Frequency & Rel. Frequency \tabularnewline
22 & 362 & 0.0266 \tabularnewline
12 & 357 & 0.0262 \tabularnewline
5 & 356 & 0.0262 \tabularnewline
7 & 349 & 0.0257 \tabularnewline
16 & 347 & 0.0255 \tabularnewline
23 & 347 & 0.0255 \tabularnewline
9 & 343 & 0.0252 \tabularnewline
24 & 342 & 0.0251 \tabularnewline
38 & 338 & 0.0249 \tabularnewline
25 & 336 & 0.0247 \tabularnewline
19 & 335 & 0.0246 \tabularnewline
34 & 332 & 0.0244 \tabularnewline
2 & 331 & 0.0243 \tabularnewline
14 & 330 & 0.0243 \tabularnewline
29 & 330 & 0.0243 \tabularnewline
4 & 329 & 0.0242 \tabularnewline
1 & 328 & 0.0241 \tabularnewline
41 & 328 & 0.0241 \tabularnewline
10 & 327 & 0.024 \tabularnewline
3 & 325 & 0.0239 \tabularnewline
42 & 325 & 0.0239 \tabularnewline
33 & 323 & 0.0237 \tabularnewline
13 & 322 & 0.0237 \tabularnewline
36 & 321 & 0.0236 \tabularnewline
6 & 321 & 0.0236 \tabularnewline
28 & 320 & 0.0235 \tabularnewline
37 & 320 & 0.0235 \tabularnewline
21 & 319 & 0.0235 \tabularnewline
26 & 318 & 0.0234 \tabularnewline
27 & 315 & 0.0232 \tabularnewline
30 & 314 & 0.0231 \tabularnewline
17 & 310 & 0.0228 \tabularnewline
40 & 310 & 0.0228 \tabularnewline
11 & 309 & 0.0227 \tabularnewline
32 & 305 & 0.0224 \tabularnewline
20 & 303 & 0.0223 \tabularnewline
35 & 302 & 0.0222 \tabularnewline
31 & 301 & 0.0221 \tabularnewline
8 & 299 & 0.022 \tabularnewline
18 & 297 & 0.0218 \tabularnewline
39 & 295 & 0.0217 \tabularnewline
15 & 280 & 0.0206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285176&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]22[/C][C]362[/C][C]0.0266[/C][/ROW]
[ROW][C]12[/C][C]357[/C][C]0.0262[/C][/ROW]
[ROW][C]5[/C][C]356[/C][C]0.0262[/C][/ROW]
[ROW][C]7[/C][C]349[/C][C]0.0257[/C][/ROW]
[ROW][C]16[/C][C]347[/C][C]0.0255[/C][/ROW]
[ROW][C]23[/C][C]347[/C][C]0.0255[/C][/ROW]
[ROW][C]9[/C][C]343[/C][C]0.0252[/C][/ROW]
[ROW][C]24[/C][C]342[/C][C]0.0251[/C][/ROW]
[ROW][C]38[/C][C]338[/C][C]0.0249[/C][/ROW]
[ROW][C]25[/C][C]336[/C][C]0.0247[/C][/ROW]
[ROW][C]19[/C][C]335[/C][C]0.0246[/C][/ROW]
[ROW][C]34[/C][C]332[/C][C]0.0244[/C][/ROW]
[ROW][C]2[/C][C]331[/C][C]0.0243[/C][/ROW]
[ROW][C]14[/C][C]330[/C][C]0.0243[/C][/ROW]
[ROW][C]29[/C][C]330[/C][C]0.0243[/C][/ROW]
[ROW][C]4[/C][C]329[/C][C]0.0242[/C][/ROW]
[ROW][C]1[/C][C]328[/C][C]0.0241[/C][/ROW]
[ROW][C]41[/C][C]328[/C][C]0.0241[/C][/ROW]
[ROW][C]10[/C][C]327[/C][C]0.024[/C][/ROW]
[ROW][C]3[/C][C]325[/C][C]0.0239[/C][/ROW]
[ROW][C]42[/C][C]325[/C][C]0.0239[/C][/ROW]
[ROW][C]33[/C][C]323[/C][C]0.0237[/C][/ROW]
[ROW][C]13[/C][C]322[/C][C]0.0237[/C][/ROW]
[ROW][C]36[/C][C]321[/C][C]0.0236[/C][/ROW]
[ROW][C]6[/C][C]321[/C][C]0.0236[/C][/ROW]
[ROW][C]28[/C][C]320[/C][C]0.0235[/C][/ROW]
[ROW][C]37[/C][C]320[/C][C]0.0235[/C][/ROW]
[ROW][C]21[/C][C]319[/C][C]0.0235[/C][/ROW]
[ROW][C]26[/C][C]318[/C][C]0.0234[/C][/ROW]
[ROW][C]27[/C][C]315[/C][C]0.0232[/C][/ROW]
[ROW][C]30[/C][C]314[/C][C]0.0231[/C][/ROW]
[ROW][C]17[/C][C]310[/C][C]0.0228[/C][/ROW]
[ROW][C]40[/C][C]310[/C][C]0.0228[/C][/ROW]
[ROW][C]11[/C][C]309[/C][C]0.0227[/C][/ROW]
[ROW][C]32[/C][C]305[/C][C]0.0224[/C][/ROW]
[ROW][C]20[/C][C]303[/C][C]0.0223[/C][/ROW]
[ROW][C]35[/C][C]302[/C][C]0.0222[/C][/ROW]
[ROW][C]31[/C][C]301[/C][C]0.0221[/C][/ROW]
[ROW][C]8[/C][C]299[/C][C]0.022[/C][/ROW]
[ROW][C]18[/C][C]297[/C][C]0.0218[/C][/ROW]
[ROW][C]39[/C][C]295[/C][C]0.0217[/C][/ROW]
[ROW][C]15[/C][C]280[/C][C]0.0206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285176&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285176&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
223620.0266
123570.0262
53560.0262
73490.0257
163470.0255
233470.0255
93430.0252
243420.0251
383380.0249
253360.0247
193350.0246
343320.0244
23310.0243
143300.0243
293300.0243
43290.0242
13280.0241
413280.0241
103270.024
33250.0239
423250.0239
333230.0237
133220.0237
363210.0236
63210.0236
283200.0235
373200.0235
213190.0235
263180.0234
273150.0232
303140.0231
173100.0228
403100.0228
113090.0227
323050.0224
203030.0223
353020.0222
313010.0221
82990.022
182970.0218
392950.0217
152800.0206


Figures (Output of Computation)

Input Parameters & R Code

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 <- 'Interval/Ratio'
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,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')
}