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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, 16 Dec 2011 07:39:23 -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/16/t1324039187l9a9ytiil8oxkah.htm/, Retrieved Sun, 05 May 2024 13:16:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155869, Retrieved Sun, 05 May 2024 13:16:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

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] [WS1 SHW Task 3] [2011-09-30 15:05:56] [2ca9890f29577b21e1107ae30466e88a]
-   PD    [Histogram] [Paper - histogram...] [2011-12-16 12:17:58] [2ca9890f29577b21e1107ae30466e88a]
-   PD        [Histogram] [paper - histogram...] [2011-12-16 12:39:23] [2489a3445a7d2af96337a363cd642931] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
86.239
99.674
106.341
111.579
119.166
128.025
131.816
132.373
132.599
135.419
137.434
140.944
141.536
144.093
145.049
146.413
147.397
148.338
149.066
151.254
152.194
158.481
160.454
160.709
162.229
162.942
164.128
168.359
168.574
169.266
171.426
172.653
174.055
174.194
174.529
175.922
176.094
177.794
178.705
183.312
183.445
183.913
184.932
185.032
186.126
186.148
186.732
186.966
187.418
187.809
187.874
188.237
188.269
189.556
189.727
190.706
190.889
191.253
191.444
192.436
193.276
193.451
198.779
198.781
199.164
199.774
200.352
201.536
202.606
202.754
204.077
204.516
206.275
209.164
209.679
210.515
211.375
211.901
212.513
213.393
213.439
213.447
213.859
213.939
214.781
214.858
215.518
215.826
217.424
218.735
219.639
219.687
222.839
228.474
230.739
233.134
233.626
235.155
240.619
241.958
245.107
247.713
251.211
253.792
256.928
258.391
259.533
263.205
269.203
269.412
269.896
287.867
291.328
292.059
292.059
292.208
295.651
297.935
306.713
307.655
311.735
314.343
322.535
324.418
332.405
335.093
342.334
354.741
356.178
367.468
371.465
372.051
385.924
395.029
396.076
412.188
424.356
452.975
455.764
466.301
152.64
159.58
161.99
167.39
179.2
181.88
197.64
203.67
216.06
226.36
241.86
243.79
269.78
328.32
329.82
399.61
98.27

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155869&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155869&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'Gertrude Mary Cox' @ cox.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[50,100[7530.0191080.0191080.000382
[100,150[125170.108280.1273890.002166
[150,200[175540.3439490.4713380.006879
[200,250[225410.2611460.7324840.005223
[250,300[275170.108280.8407640.002166
[300,350[325110.0700640.9108280.001401
[350,400[37590.0573250.9681530.001146
[400,450[42520.0127390.9808920.000255
[450,500]47530.01910810.000382

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[50,100[ & 75 & 3 & 0.019108 & 0.019108 & 0.000382 \tabularnewline
[100,150[ & 125 & 17 & 0.10828 & 0.127389 & 0.002166 \tabularnewline
[150,200[ & 175 & 54 & 0.343949 & 0.471338 & 0.006879 \tabularnewline
[200,250[ & 225 & 41 & 0.261146 & 0.732484 & 0.005223 \tabularnewline
[250,300[ & 275 & 17 & 0.10828 & 0.840764 & 0.002166 \tabularnewline
[300,350[ & 325 & 11 & 0.070064 & 0.910828 & 0.001401 \tabularnewline
[350,400[ & 375 & 9 & 0.057325 & 0.968153 & 0.001146 \tabularnewline
[400,450[ & 425 & 2 & 0.012739 & 0.980892 & 0.000255 \tabularnewline
[450,500] & 475 & 3 & 0.019108 & 1 & 0.000382 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155869&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][50,100[[/C][C]75[/C][C]3[/C][C]0.019108[/C][C]0.019108[/C][C]0.000382[/C][/ROW]
[ROW][C][100,150[[/C][C]125[/C][C]17[/C][C]0.10828[/C][C]0.127389[/C][C]0.002166[/C][/ROW]
[ROW][C][150,200[[/C][C]175[/C][C]54[/C][C]0.343949[/C][C]0.471338[/C][C]0.006879[/C][/ROW]
[ROW][C][200,250[[/C][C]225[/C][C]41[/C][C]0.261146[/C][C]0.732484[/C][C]0.005223[/C][/ROW]
[ROW][C][250,300[[/C][C]275[/C][C]17[/C][C]0.10828[/C][C]0.840764[/C][C]0.002166[/C][/ROW]
[ROW][C][300,350[[/C][C]325[/C][C]11[/C][C]0.070064[/C][C]0.910828[/C][C]0.001401[/C][/ROW]
[ROW][C][350,400[[/C][C]375[/C][C]9[/C][C]0.057325[/C][C]0.968153[/C][C]0.001146[/C][/ROW]
[ROW][C][400,450[[/C][C]425[/C][C]2[/C][C]0.012739[/C][C]0.980892[/C][C]0.000255[/C][/ROW]
[ROW][C][450,500][/C][C]475[/C][C]3[/C][C]0.019108[/C][C]1[/C][C]0.000382[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155869&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
[50,100[7530.0191080.0191080.000382
[100,150[125170.108280.1273890.002166
[150,200[175540.3439490.4713380.006879
[200,250[225410.2611460.7324840.005223
[250,300[275170.108280.8407640.002166
[300,350[325110.0700640.9108280.001401
[350,400[37590.0573250.9681530.001146
[400,450[42520.0127390.9808920.000255
[450,500]47530.01910810.000382


Figures (Output of Computation)

Input Parameters & R Code

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