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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 computationSat, 10 Sep 2016 21:02:38 +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/Sep/10/t1473534164jkrwlkmomgihr6x.htm/, Retrieved Sun, 05 May 2024 03:27:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296517, Retrieved Sun, 05 May 2024 03:27:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Tijdreeks A Stap 3] [2014-08-09 15:40:12] [2064a7ed2562130dd70fccaf2dd61d5a]
- RM    [Kernel Density Estimation] [Tijdreeks A Stap 6] [2014-08-09 16:26:48] [2064a7ed2562130dd70fccaf2dd61d5a]
- RMP     [Moments] [] [2016-09-10 18:52:52] [597f04887712160a284bcf6998091a8a]
- RMPD        [Histogram] [] [2016-09-10 19:02:38] [101a6ec9f938885df0a44f20458d2eb4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
56
55
54
52
72
71
56
46
47
47
48
50
44
38
33
33
52
54
39
22
31
31
38
42
41
31
36
34
51
47
31
19
30
33
36
40
32
25
28
29
55
55
40
38
44
41
49
59
61
47
43
39
66
68
63
68
67
59
68
78
82
70
62
68
94
102
100
104
103
93
110
114
120
102
95
103
122
139
135
135
137
130
148
148
145
128
131
133
146
163
151
157
152
149
172
167
160
150
160
165
171
179
171
176
170
169
194
196
188
174
186
191
197
206
197
204
201
190
213
213

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296517&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296517&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296517&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 time0 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,20[1010.0083330.0083330.000417
[20,40[30210.1750.1833330.00875
[40,60[50280.2333330.4166670.011667
[60,80[70130.1083330.5250.005417
[80,100[9040.0333330.5583330.001667
[100,120[11080.0666670.6250.003333
[120,140[130100.0833330.7083330.004167
[140,160[15090.0750.7833330.00375
[160,180[170130.1083330.8916670.005417
[180,200[19080.0666670.9583330.003333
[200,220]21050.04166710.002083

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20[ & 10 & 1 & 0.008333 & 0.008333 & 0.000417 \tabularnewline
[20,40[ & 30 & 21 & 0.175 & 0.183333 & 0.00875 \tabularnewline
[40,60[ & 50 & 28 & 0.233333 & 0.416667 & 0.011667 \tabularnewline
[60,80[ & 70 & 13 & 0.108333 & 0.525 & 0.005417 \tabularnewline
[80,100[ & 90 & 4 & 0.033333 & 0.558333 & 0.001667 \tabularnewline
[100,120[ & 110 & 8 & 0.066667 & 0.625 & 0.003333 \tabularnewline
[120,140[ & 130 & 10 & 0.083333 & 0.708333 & 0.004167 \tabularnewline
[140,160[ & 150 & 9 & 0.075 & 0.783333 & 0.00375 \tabularnewline
[160,180[ & 170 & 13 & 0.108333 & 0.891667 & 0.005417 \tabularnewline
[180,200[ & 190 & 8 & 0.066667 & 0.958333 & 0.003333 \tabularnewline
[200,220] & 210 & 5 & 0.041667 & 1 & 0.002083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296517&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][0,20[[/C][C]10[/C][C]1[/C][C]0.008333[/C][C]0.008333[/C][C]0.000417[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]21[/C][C]0.175[/C][C]0.183333[/C][C]0.00875[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]28[/C][C]0.233333[/C][C]0.416667[/C][C]0.011667[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]13[/C][C]0.108333[/C][C]0.525[/C][C]0.005417[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]4[/C][C]0.033333[/C][C]0.558333[/C][C]0.001667[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]8[/C][C]0.066667[/C][C]0.625[/C][C]0.003333[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]10[/C][C]0.083333[/C][C]0.708333[/C][C]0.004167[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]9[/C][C]0.075[/C][C]0.783333[/C][C]0.00375[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]13[/C][C]0.108333[/C][C]0.891667[/C][C]0.005417[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]8[/C][C]0.066667[/C][C]0.958333[/C][C]0.003333[/C][/ROW]
[ROW][C][200,220][/C][C]210[/C][C]5[/C][C]0.041667[/C][C]1[/C][C]0.002083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=296517&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296517&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
[0,20[1010.0083330.0083330.000417
[20,40[30210.1750.1833330.00875
[40,60[50280.2333330.4166670.011667
[60,80[70130.1083330.5250.005417
[80,100[9040.0333330.5583330.001667
[100,120[11080.0666670.6250.003333
[120,140[130100.0833330.7083330.004167
[140,160[15090.0750.7833330.00375
[160,180[170130.1083330.8916670.005417
[180,200[19080.0666670.9583330.003333
[200,220]21050.04166710.002083


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = ; par2 = yellow ; 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,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')
}