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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, 04 Dec 2010 14:07:35 +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/2010/Dec/04/t1291471695xwd179l4du27fts.htm/, Retrieved Sat, 04 May 2024 22:19:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105154, Retrieved Sat, 04 May 2024 22:19:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Central Tendency] [Time needed to su...] [2010-09-25 09:42:08] [b98453cac15ba1066b407e146608df68]
-    D  [Central Tendency] [Geschatte tijd se...] [2010-11-26 16:23:58] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
- RMP       [Histogram] [tijd nodig om de ...] [2010-12-04 14:07:35] [6ff6d3268c67efbfcd6d6506b34b66fb] [Current]
-   P         [Histogram] [Paper: histogram&...] [2010-12-11 14:14:53] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
299
157
169
85
105
132
169
74
98
82
141
200
266
122
175
158
137
131
164
169
116
180
150
171
128
140
165
151
180
110
181
182
115
254
125
111
136
132
216
303
331
118
118
104
395
106
115
621
114
98
153
140
179
759
106
83
133
169
204
178
129
110
149
100
221
158
127
158
107
213
578
569
151
170
287
175
76
131
209
152
246
191
129
169
287
124
174
154
247
110
157
196
128
129
128
147
125
140
155
378
157
86
118
202
523
239
108
155
314
221
232
558
471
131
103
175
81
221
258
165
114
223
191
144
149
115
88
130
117
201
136
136
289
142
143
191
106
180
81
252
126
250
192
223
133
139
858
147
84
144
82
129
94
105
122
140

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105154&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105154&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105154&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,100[50140.0897440.0897440.000897
[100,200[1501040.6666670.756410.006667
[200,300[250250.1602560.9166670.001603
[300,400[35050.0320510.9487180.000321
[400,500[45010.006410.9551286.4e-05
[500,600[55040.0256410.9807690.000256
[600,700[65010.006410.9871796.4e-05
[700,800[75010.006410.993596.4e-05
[800,900]85010.0064116.4e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,100[ & 50 & 14 & 0.089744 & 0.089744 & 0.000897 \tabularnewline
[100,200[ & 150 & 104 & 0.666667 & 0.75641 & 0.006667 \tabularnewline
[200,300[ & 250 & 25 & 0.160256 & 0.916667 & 0.001603 \tabularnewline
[300,400[ & 350 & 5 & 0.032051 & 0.948718 & 0.000321 \tabularnewline
[400,500[ & 450 & 1 & 0.00641 & 0.955128 & 6.4e-05 \tabularnewline
[500,600[ & 550 & 4 & 0.025641 & 0.980769 & 0.000256 \tabularnewline
[600,700[ & 650 & 1 & 0.00641 & 0.987179 & 6.4e-05 \tabularnewline
[700,800[ & 750 & 1 & 0.00641 & 0.99359 & 6.4e-05 \tabularnewline
[800,900] & 850 & 1 & 0.00641 & 1 & 6.4e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105154&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][0,100[[/C][C]50[/C][C]14[/C][C]0.089744[/C][C]0.089744[/C][C]0.000897[/C][/ROW]
[ROW][C][100,200[[/C][C]150[/C][C]104[/C][C]0.666667[/C][C]0.75641[/C][C]0.006667[/C][/ROW]
[ROW][C][200,300[[/C][C]250[/C][C]25[/C][C]0.160256[/C][C]0.916667[/C][C]0.001603[/C][/ROW]
[ROW][C][300,400[[/C][C]350[/C][C]5[/C][C]0.032051[/C][C]0.948718[/C][C]0.000321[/C][/ROW]
[ROW][C][400,500[[/C][C]450[/C][C]1[/C][C]0.00641[/C][C]0.955128[/C][C]6.4e-05[/C][/ROW]
[ROW][C][500,600[[/C][C]550[/C][C]4[/C][C]0.025641[/C][C]0.980769[/C][C]0.000256[/C][/ROW]
[ROW][C][600,700[[/C][C]650[/C][C]1[/C][C]0.00641[/C][C]0.987179[/C][C]6.4e-05[/C][/ROW]
[ROW][C][700,800[[/C][C]750[/C][C]1[/C][C]0.00641[/C][C]0.99359[/C][C]6.4e-05[/C][/ROW]
[ROW][C][800,900][/C][C]850[/C][C]1[/C][C]0.00641[/C][C]1[/C][C]6.4e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105154&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105154&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
[0,100[50140.0897440.0897440.000897
[100,200[1501040.6666670.756410.006667
[200,300[250250.1602560.9166670.001603
[300,400[35050.0320510.9487180.000321
[400,500[45010.006410.9551286.4e-05
[500,600[55040.0256410.9807690.000256
[600,700[65010.006410.9871796.4e-05
[700,800[75010.006410.993596.4e-05
[800,900]85010.0064116.4e-05


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):
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')
}