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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Wed, 12 Dec 2012 10:09:34 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/12/t1355324990k0opxhgw9bysrtq.htm/, Retrieved Mon, 29 Apr 2024 06:21:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198927, Retrieved Mon, 29 Apr 2024 06:21:44 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Histogram] [eshist] [2012-12-12 15:09:34] [e357aba3893873b930815b56a53f1005] [Current]

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Dataseries X:

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Histogram

Boxplots

60.105502136752000
7.907312589228700
-1.629491887131730
-1.523957559467700
-1.566427606620550
-3.789554566451050
54.200457074549000
-32.163510672247400
-30.402014378527600
33.723646041332600
-53.295571899362000
-14.104598762058100
7.823650371650560
-23.492157461915400
-39.202849795559900
-54.438726552717300
-63.160118106051600
-14.485513312119400
-6.628558771563010
-37.251050153206200
7.170462889295040
-12.467581386629100
23.642668315511900
-1.088791886433090
-51.662325993329800
-35.512251522296000
5.730258768588780
-4.402113954364150
-19.401440515526700
1.520637597479090
20.301634328476600
21.129552578314700
32.299041793952500
25.405520281557300
16.249817632919000
-24.017154073341100
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-15.622858322169500
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15.385614471917900
-5.431603723902270
-13.878589038249800
24.544117388533300
28.999963471410300
1.823381546043520
9.408070370187970
3.027664330040980
-4.924275934007740
-9.914609211208590
-41.194180801578900
4.537200239685570
23.270218164366300
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10.759626115194600
24.269471838984300
35.926564997673600
32.318324426507600
37.872923673265400
36.110268543315900
50.367586366732600
19.674537875964500
10.769621706194800
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21.213182978857300
0.785421269382084
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16.888358118621200
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14.542044173700200
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11.029760211128600
14.736685076468700
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15.326629227714100
29.089261351332600
54.294590941540900
31.116771502448300
48.848504485926100
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6.259586476791070
0.125927575354126
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34.583810001181300
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29.797534213448200
28.099060232233400
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41.416164263170000
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35.128077583754800
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8.648082866597060
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39.644586972684100
30.126766094770500
59.366912136556700
28.053251004387100
21.594556562382100
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4.602911543302070
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-8.798035530515340
13.884425824100000
4.869115945923970
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14.553069972311400
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28.668939513433700
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35.065571570143000
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34.799821814800400
26.382577058530900
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18.505687742399500
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27.734506649469200
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22.355040813270000
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-2.606079633912260
-7.148573088618780
-11.133931876000000
18.463790548064300
10.431606141974300
20.111394906474100
17.585817125854700
-7.287709889268740
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4.236220472917470
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14.098999815588100
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3.813803754024780
2.058393512826170
4.052997857020270
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50.853012324373200
15.264595051509300
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14.857709931226600
10.891750422069800
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19.049784411625500
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57.140945046846900
19.424142212143000
-26.830983001473100
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-8.535389246669300
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11.530320435740700
13.995248188981200
-12.322825473095300
24.042058033293400
39.967059599686800
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20.790634404711600
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-13.213953207478000
21.010630015082000
32.219715891287000
19.962339504755600
10.717014437494100
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32.442592185996000
36.686806257020900
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8.795770356075250
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12.913345730458800
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5.070944864413150
33.521277765799400
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24.516643860920200
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14.500002323189400
-5.710688022182180
4.477170448968650
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0.746187934154989
20.624401595029300
11.721153781144800
13.531505025554600
-26.309844364410300
13.476158699179900
2.534010682220700
29.753080445948200
9.046961144409860
-12.287076964116900
-12.523129418815900
1.327508167207160
16.347057213377300
33.449424050193600
6.395776893376880
43.777257340183200
1.295681207232460
38.135431520262000
39.459479737038400
131.183597606530000
7.175545616393490
15.292626067378000
-37.518684587387300
-26.973262898070600
-35.786051835778500
-14.023070258689400
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-23.408807568463500
-18.877586017302100
-38.708702989784300
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5.956315671720860
-7.058043321348120
-29.814249740754300
-29.324599906597200
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20.360623535237100
33.106532569123400
23.529990999874700
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0.94132987310752
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38.257466963522000
-22.406062405960700
-61.804184623424200
-30.868578939543700
10.934468801689900
-10.126286331900500
31.925762581573300
-10.207648081455900
-1.090251191291600
-8.301356733144980
-45.956006137348100
13.524671856492900
-1.020698593768880
18.509844184136300
-24.784269672428800
-7.760453189621440
-32.817236164421200
54.038726371657500
3.627317145533770
13.025417693240100
-9.993761806170820
-2.366689948430460
17.782239152593700

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198927&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198927&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198927&T=0

As an alternative you can also use a 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 Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[-80,-60[	-70	2	0.005556	0.005556	0.000278
[-60,-40[	-50	12	0.033333	0.038889	0.001667
[-40,-20[	-30	64	0.177778	0.216667	0.008889
[-20,0[	-10	117	0.325	0.541667	0.01625
[0,20[	10	96	0.266667	0.808333	0.013333
[20,40[	30	55	0.152778	0.961111	0.007639
[40,60[	50	12	0.033333	0.994444	0.001667
[60,80[	70	1	0.002778	0.997222	0.000139
[80,100[	90	0	0	0.997222	0
[100,120[	110	0	0	0.997222	0
[120,140]	130	1	0.002778	1	0.000139

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-80,-60[ & -70 & 2 & 0.005556 & 0.005556 & 0.000278 \tabularnewline
[-60,-40[ & -50 & 12 & 0.033333 & 0.038889 & 0.001667 \tabularnewline
[-40,-20[ & -30 & 64 & 0.177778 & 0.216667 & 0.008889 \tabularnewline
[-20,0[ & -10 & 117 & 0.325 & 0.541667 & 0.01625 \tabularnewline
[0,20[ & 10 & 96 & 0.266667 & 0.808333 & 0.013333 \tabularnewline
[20,40[ & 30 & 55 & 0.152778 & 0.961111 & 0.007639 \tabularnewline
[40,60[ & 50 & 12 & 0.033333 & 0.994444 & 0.001667 \tabularnewline
[60,80[ & 70 & 1 & 0.002778 & 0.997222 & 0.000139 \tabularnewline
[80,100[ & 90 & 0 & 0 & 0.997222 & 0 \tabularnewline
[100,120[ & 110 & 0 & 0 & 0.997222 & 0 \tabularnewline
[120,140] & 130 & 1 & 0.002778 & 1 & 0.000139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198927&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][-80,-60[[/C][C]-70[/C][C]2[/C][C]0.005556[/C][C]0.005556[/C][C]0.000278[/C][/ROW]
[ROW][C][-60,-40[[/C][C]-50[/C][C]12[/C][C]0.033333[/C][C]0.038889[/C][C]0.001667[/C][/ROW]
[ROW][C][-40,-20[[/C][C]-30[/C][C]64[/C][C]0.177778[/C][C]0.216667[/C][C]0.008889[/C][/ROW]
[ROW][C][-20,0[[/C][C]-10[/C][C]117[/C][C]0.325[/C][C]0.541667[/C][C]0.01625[/C][/ROW]
[ROW][C][0,20[[/C][C]10[/C][C]96[/C][C]0.266667[/C][C]0.808333[/C][C]0.013333[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]55[/C][C]0.152778[/C][C]0.961111[/C][C]0.007639[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]12[/C][C]0.033333[/C][C]0.994444[/C][C]0.001667[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]1[/C][C]0.002778[/C][C]0.997222[/C][C]0.000139[/C][/ROW]
[ROW][C][80,100[[/C][C]90[/C][C]0[/C][C]0[/C][C]0.997222[/C][C]0[/C][/ROW]
[ROW][C][100,120[[/C][C]110[/C][C]0[/C][C]0[/C][C]0.997222[/C][C]0[/C][/ROW]
[ROW][C][120,140][/C][C]130[/C][C]1[/C][C]0.002778[/C][C]1[/C][C]0.000139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198927&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198927&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Frequency Table (Histogram)
Bins	Midpoint	Abs. Frequency	Rel. Frequency	Cumul. Rel. Freq.	Density
[-80,-60[	-70	2	0.005556	0.005556	0.000278
[-60,-40[	-50	12	0.033333	0.038889	0.001667
[-40,-20[	-30	64	0.177778	0.216667	0.008889
[-20,0[	-10	117	0.325	0.541667	0.01625
[0,20[	10	96	0.266667	0.808333	0.013333
[20,40[	30	55	0.152778	0.961111	0.007639
[40,60[	50	12	0.033333	0.994444	0.001667
[60,80[	70	1	0.002778	0.997222	0.000139
[80,100[	90	0	0	0.997222	0
[100,120[	110	0	0	0.997222	0
[120,140]	130	1	0.002778	1	0.000139

Figure 1

PNG link

Postscript link

PDF link

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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code