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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 computationTue, 13 Dec 2011 11:11:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/13/t1323792747oopjid407rx0g9e.htm/, Retrieved Fri, 03 May 2024 03:36:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154476, Retrieved Fri, 03 May 2024 03:36:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Bad example of Hi...] [2010-09-25 09:28:23] [b98453cac15ba1066b407e146608df68]
- R P   [Histogram] [Task 3] [2011-09-30 09:15:05] [54b1f171ce7a12209ffa11b565e1dcf5]
-   PD    [Histogram] [Paper: Histogram] [2011-12-13 16:07:19] [54b1f171ce7a12209ffa11b565e1dcf5]
-   PD        [Histogram] [Paper: Histogram ...] [2011-12-13 16:11:21] [70041e5e9044b1d424b6896a10522877] [Current]
-   PD          [Histogram] [Paper: Histogram ...] [2011-12-13 16:30:23] [54b1f171ce7a12209ffa11b565e1dcf5]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
213
13
196
200
271
201
233
33
150
88
204
80
269
274
156
98
159
72
258
137
294
276
145
99
51
249
162
33
167
82
17
58
123
205
251
11
66
9
283
198
183
149
28
194
268
33
233
85
247
143
177
142
157
86
97
234
126
119
152
52
252
41
109
174
291
262
203
48
203
85
229
45
73
56
210
289
295
218
82
143
32
35
269
118
229
213
163
270
12
86
167
7
178
76
259
38
263
263

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154476&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154476&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,20[1060.0612240.0612240.003061
[20,40[3070.0714290.1326530.003571
[40,60[5070.0714290.2040820.003571
[60,80[7040.0408160.2448980.002041
[80,100[90110.1122450.3571430.005612
[100,120[11030.0306120.3877550.001531
[120,140[13030.0306120.4183670.001531
[140,160[150100.1020410.5204080.005102
[160,180[17070.0714290.5918370.003571
[180,200[19040.0408160.6326530.002041
[200,220[210100.1020410.7346940.005102
[220,240[23050.051020.7857140.002551
[240,260[25060.0612240.8469390.003061
[260,280[270100.1020410.948980.005102
[280,300]29050.0510210.002551

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,20[ & 10 & 6 & 0.061224 & 0.061224 & 0.003061 \tabularnewline
[20,40[ & 30 & 7 & 0.071429 & 0.132653 & 0.003571 \tabularnewline
[40,60[ & 50 & 7 & 0.071429 & 0.204082 & 0.003571 \tabularnewline
[60,80[ & 70 & 4 & 0.040816 & 0.244898 & 0.002041 \tabularnewline
[80,100[ & 90 & 11 & 0.112245 & 0.357143 & 0.005612 \tabularnewline
[100,120[ & 110 & 3 & 0.030612 & 0.387755 & 0.001531 \tabularnewline
[120,140[ & 130 & 3 & 0.030612 & 0.418367 & 0.001531 \tabularnewline
[140,160[ & 150 & 10 & 0.102041 & 0.520408 & 0.005102 \tabularnewline
[160,180[ & 170 & 7 & 0.071429 & 0.591837 & 0.003571 \tabularnewline
[180,200[ & 190 & 4 & 0.040816 & 0.632653 & 0.002041 \tabularnewline
[200,220[ & 210 & 10 & 0.102041 & 0.734694 & 0.005102 \tabularnewline
[220,240[ & 230 & 5 & 0.05102 & 0.785714 & 0.002551 \tabularnewline
[240,260[ & 250 & 6 & 0.061224 & 0.846939 & 0.003061 \tabularnewline
[260,280[ & 270 & 10 & 0.102041 & 0.94898 & 0.005102 \tabularnewline
[280,300] & 290 & 5 & 0.05102 & 1 & 0.002551 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154476&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]6[/C][C]0.061224[/C][C]0.061224[/C][C]0.003061[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]7[/C][C]0.071429[/C][C]0.132653[/C][C]0.003571[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]7[/C][C]0.071429[/C][C]0.204082[/C][C]0.003571[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]4[/C][C]0.040816[/C][C]0.244898[/C][C]0.002041[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]11[/C][C]0.112245[/C][C]0.357143[/C][C]0.005612[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]3[/C][C]0.030612[/C][C]0.387755[/C][C]0.001531[/C][/ROW]
[ROW][C][120,140[[/C][C]130[/C][C]3[/C][C]0.030612[/C][C]0.418367[/C][C]0.001531[/C][/ROW]
[ROW][C][140,160[[/C][C]150[/C][C]10[/C][C]0.102041[/C][C]0.520408[/C][C]0.005102[/C][/ROW]
[ROW][C][160,180[[/C][C]170[/C][C]7[/C][C]0.071429[/C][C]0.591837[/C][C]0.003571[/C][/ROW]
[ROW][C][180,200[[/C][C]190[/C][C]4[/C][C]0.040816[/C][C]0.632653[/C][C]0.002041[/C][/ROW]
[ROW][C][200,220[[/C][C]210[/C][C]10[/C][C]0.102041[/C][C]0.734694[/C][C]0.005102[/C][/ROW]
[ROW][C][220,240[[/C][C]230[/C][C]5[/C][C]0.05102[/C][C]0.785714[/C][C]0.002551[/C][/ROW]
[ROW][C][240,260[[/C][C]250[/C][C]6[/C][C]0.061224[/C][C]0.846939[/C][C]0.003061[/C][/ROW]
[ROW][C][260,280[[/C][C]270[/C][C]10[/C][C]0.102041[/C][C]0.94898[/C][C]0.005102[/C][/ROW]
[ROW][C][280,300][/C][C]290[/C][C]5[/C][C]0.05102[/C][C]1[/C][C]0.002551[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154476&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[1060.0612240.0612240.003061
[20,40[3070.0714290.1326530.003571
[40,60[5070.0714290.2040820.003571
[60,80[7040.0408160.2448980.002041
[80,100[90110.1122450.3571430.005612
[100,120[11030.0306120.3877550.001531
[120,140[13030.0306120.4183670.001531
[140,160[150100.1020410.5204080.005102
[160,180[17070.0714290.5918370.003571
[180,200[19040.0408160.6326530.002041
[200,220[210100.1020410.7346940.005102
[220,240[23050.051020.7857140.002551
[240,260[25060.0612240.8469390.003061
[260,280[270100.1020410.948980.005102
[280,300]29050.0510210.002551


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 20 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 20 ; 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')
}