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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 11 Apr 2015 20:45:54 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/11/t1428781630pf9psq7423v841o.htm/, Retrieved Thu, 09 May 2024 16:29:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278707, Retrieved Thu, 09 May 2024 16:29:54 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Near Distances ] [2015-04-11 19:45:54] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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200.424933
157.264098
316.652499
313.228096
134.275019
139.253471
194.143412
247.401723
303.812052
349.903165
129.692890
150.588614
281.824666
280.984687
225.637199
123.169361
125.183481
247.695681
282.292826
265.629298
159.621103
219.820780
147.072893
63.015267
82.359381
82.774201
222.895512
100.920070
220.984936
61.901331
430.640207
101.592715
319.152083
99.597286
121.081686
518.485106
289.789178
230.009768
427.548916
403.795061
234.686181
195.815732
96.404714
557.519407
138.838289
101.004608
97.711617
96.580115
561.384719
236.095977
404.093311
145.089127
349.495785
99.468812
109.550052
347.056505
151.390473
100.118045
398.942094
329.325527
89.317223
97.187584
81.887715
220.860758
852.026410
99.374713
647.499875
335.859915
857.148487
334.476318
87.699178
125.310130
107.020813
175.284144
202.268246
229.481717
198.337808
226.585161
155.685984
201.492431
204.251875
564.110188
174.940682
50.509036
50.679782
207.092520
50.449308
50.389575
252.641252
320.915712
177.934012
191.325308
191.672447
254.321605
316.721617
114.157364
114.937461
232.288417
222.276061
553.641088
214.680566
396.070728
138.835258
336.012099
336.506031
285.658158
401.529587
515.618783
254.559388
475.716639
216.546974
513.872267
172.626713
177.213796
204.784747
406.488990
244.207291
78.017525
68.833825
88.612932
213.053111
472.648264
95.308481
90.762390
331.120376
399.569888
370.973573
265.798017
422.642025
354.830817
477.207433
195.644547
344.731653
195.815732
186.485890
107.081746
857.682280
857.148487
91.163341
90.619419
106.498515
138.748100
308.315245
484.047195
90.915950
857.636776
262.462898
258.410374
104.032318
103.728897

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278707&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278707&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278707&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 time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[0,100[505180.1370730.1370730.001371
[100,200[15010530.2786450.4157180.002786
[200,300[2508370.2214870.6372060.002215
[300,400[3505900.1561260.7933320.001561
[400,500[4503160.083620.8769520.000836
[500,600[5501830.0484260.9253770.000484
[600,700[650970.0256680.9510450.000257
[700,800[750420.0111140.9621590.000111
[800,900[850440.0116430.9738030.000116
[900,1000[950290.0076740.9814777.7e-05
[1000,1100[1050120.0031750.9846523.2e-05
[1100,1200[1150140.0037050.9883573.7e-05
[1200,1300[125090.0023820.9907382.4e-05
[1300,1400[135090.0023820.993122.4e-05
[1400,1500[145030.0007940.9939148e-06
[1500,1600[155030.0007940.9947088e-06
[1600,1700[165040.0010580.9957661.1e-05
[1700,1800[175020.0005290.9962955e-06
[1800,1900[185010.0002650.996563e-06
[1900,2000[1950000.996560
[2000,2100[205010.0002650.9968253e-06
[2100,2200[215010.0002650.9970893e-06
[2200,2300[225040.0010580.9981481.1e-05
[2300,2400[235010.0002650.9984123e-06
[2400,2500[245020.0005290.9989425e-06
[2500,2600[2550000.9989420
[2600,2700[2650000.9989420
[2700,2800[2750000.9989420
[2800,2900[2850000.9989420
[2900,3000[2950000.9989420
[3000,3100[305030.0007940.9997358e-06
[3100,3200[3150000.9997350
[3200,3300[3250000.9997350
[3300,3400[3350000.9997350
[3400,3500[3450000.9997350
[3500,3600]355010.00026513e-06

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[0,100[ & 50 & 518 & 0.137073 & 0.137073 & 0.001371 \tabularnewline
[100,200[ & 150 & 1053 & 0.278645 & 0.415718 & 0.002786 \tabularnewline
[200,300[ & 250 & 837 & 0.221487 & 0.637206 & 0.002215 \tabularnewline
[300,400[ & 350 & 590 & 0.156126 & 0.793332 & 0.001561 \tabularnewline
[400,500[ & 450 & 316 & 0.08362 & 0.876952 & 0.000836 \tabularnewline
[500,600[ & 550 & 183 & 0.048426 & 0.925377 & 0.000484 \tabularnewline
[600,700[ & 650 & 97 & 0.025668 & 0.951045 & 0.000257 \tabularnewline
[700,800[ & 750 & 42 & 0.011114 & 0.962159 & 0.000111 \tabularnewline
[800,900[ & 850 & 44 & 0.011643 & 0.973803 & 0.000116 \tabularnewline
[900,1000[ & 950 & 29 & 0.007674 & 0.981477 & 7.7e-05 \tabularnewline
[1000,1100[ & 1050 & 12 & 0.003175 & 0.984652 & 3.2e-05 \tabularnewline
[1100,1200[ & 1150 & 14 & 0.003705 & 0.988357 & 3.7e-05 \tabularnewline
[1200,1300[ & 1250 & 9 & 0.002382 & 0.990738 & 2.4e-05 \tabularnewline
[1300,1400[ & 1350 & 9 & 0.002382 & 0.99312 & 2.4e-05 \tabularnewline
[1400,1500[ & 1450 & 3 & 0.000794 & 0.993914 & 8e-06 \tabularnewline
[1500,1600[ & 1550 & 3 & 0.000794 & 0.994708 & 8e-06 \tabularnewline
[1600,1700[ & 1650 & 4 & 0.001058 & 0.995766 & 1.1e-05 \tabularnewline
[1700,1800[ & 1750 & 2 & 0.000529 & 0.996295 & 5e-06 \tabularnewline
[1800,1900[ & 1850 & 1 & 0.000265 & 0.99656 & 3e-06 \tabularnewline
[1900,2000[ & 1950 & 0 & 0 & 0.99656 & 0 \tabularnewline
[2000,2100[ & 2050 & 1 & 0.000265 & 0.996825 & 3e-06 \tabularnewline
[2100,2200[ & 2150 & 1 & 0.000265 & 0.997089 & 3e-06 \tabularnewline
[2200,2300[ & 2250 & 4 & 0.001058 & 0.998148 & 1.1e-05 \tabularnewline
[2300,2400[ & 2350 & 1 & 0.000265 & 0.998412 & 3e-06 \tabularnewline
[2400,2500[ & 2450 & 2 & 0.000529 & 0.998942 & 5e-06 \tabularnewline
[2500,2600[ & 2550 & 0 & 0 & 0.998942 & 0 \tabularnewline
[2600,2700[ & 2650 & 0 & 0 & 0.998942 & 0 \tabularnewline
[2700,2800[ & 2750 & 0 & 0 & 0.998942 & 0 \tabularnewline
[2800,2900[ & 2850 & 0 & 0 & 0.998942 & 0 \tabularnewline
[2900,3000[ & 2950 & 0 & 0 & 0.998942 & 0 \tabularnewline
[3000,3100[ & 3050 & 3 & 0.000794 & 0.999735 & 8e-06 \tabularnewline
[3100,3200[ & 3150 & 0 & 0 & 0.999735 & 0 \tabularnewline
[3200,3300[ & 3250 & 0 & 0 & 0.999735 & 0 \tabularnewline
[3300,3400[ & 3350 & 0 & 0 & 0.999735 & 0 \tabularnewline
[3400,3500[ & 3450 & 0 & 0 & 0.999735 & 0 \tabularnewline
[3500,3600] & 3550 & 1 & 0.000265 & 1 & 3e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278707&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]518[/C][C]0.137073[/C][C]0.137073[/C][C]0.001371[/C][/ROW]
[ROW][C][100,200[[/C][C]150[/C][C]1053[/C][C]0.278645[/C][C]0.415718[/C][C]0.002786[/C][/ROW]
[ROW][C][200,300[[/C][C]250[/C][C]837[/C][C]0.221487[/C][C]0.637206[/C][C]0.002215[/C][/ROW]
[ROW][C][300,400[[/C][C]350[/C][C]590[/C][C]0.156126[/C][C]0.793332[/C][C]0.001561[/C][/ROW]
[ROW][C][400,500[[/C][C]450[/C][C]316[/C][C]0.08362[/C][C]0.876952[/C][C]0.000836[/C][/ROW]
[ROW][C][500,600[[/C][C]550[/C][C]183[/C][C]0.048426[/C][C]0.925377[/C][C]0.000484[/C][/ROW]
[ROW][C][600,700[[/C][C]650[/C][C]97[/C][C]0.025668[/C][C]0.951045[/C][C]0.000257[/C][/ROW]
[ROW][C][700,800[[/C][C]750[/C][C]42[/C][C]0.011114[/C][C]0.962159[/C][C]0.000111[/C][/ROW]
[ROW][C][800,900[[/C][C]850[/C][C]44[/C][C]0.011643[/C][C]0.973803[/C][C]0.000116[/C][/ROW]
[ROW][C][900,1000[[/C][C]950[/C][C]29[/C][C]0.007674[/C][C]0.981477[/C][C]7.7e-05[/C][/ROW]
[ROW][C][1000,1100[[/C][C]1050[/C][C]12[/C][C]0.003175[/C][C]0.984652[/C][C]3.2e-05[/C][/ROW]
[ROW][C][1100,1200[[/C][C]1150[/C][C]14[/C][C]0.003705[/C][C]0.988357[/C][C]3.7e-05[/C][/ROW]
[ROW][C][1200,1300[[/C][C]1250[/C][C]9[/C][C]0.002382[/C][C]0.990738[/C][C]2.4e-05[/C][/ROW]
[ROW][C][1300,1400[[/C][C]1350[/C][C]9[/C][C]0.002382[/C][C]0.99312[/C][C]2.4e-05[/C][/ROW]
[ROW][C][1400,1500[[/C][C]1450[/C][C]3[/C][C]0.000794[/C][C]0.993914[/C][C]8e-06[/C][/ROW]
[ROW][C][1500,1600[[/C][C]1550[/C][C]3[/C][C]0.000794[/C][C]0.994708[/C][C]8e-06[/C][/ROW]
[ROW][C][1600,1700[[/C][C]1650[/C][C]4[/C][C]0.001058[/C][C]0.995766[/C][C]1.1e-05[/C][/ROW]
[ROW][C][1700,1800[[/C][C]1750[/C][C]2[/C][C]0.000529[/C][C]0.996295[/C][C]5e-06[/C][/ROW]
[ROW][C][1800,1900[[/C][C]1850[/C][C]1[/C][C]0.000265[/C][C]0.99656[/C][C]3e-06[/C][/ROW]
[ROW][C][1900,2000[[/C][C]1950[/C][C]0[/C][C]0[/C][C]0.99656[/C][C]0[/C][/ROW]
[ROW][C][2000,2100[[/C][C]2050[/C][C]1[/C][C]0.000265[/C][C]0.996825[/C][C]3e-06[/C][/ROW]
[ROW][C][2100,2200[[/C][C]2150[/C][C]1[/C][C]0.000265[/C][C]0.997089[/C][C]3e-06[/C][/ROW]
[ROW][C][2200,2300[[/C][C]2250[/C][C]4[/C][C]0.001058[/C][C]0.998148[/C][C]1.1e-05[/C][/ROW]
[ROW][C][2300,2400[[/C][C]2350[/C][C]1[/C][C]0.000265[/C][C]0.998412[/C][C]3e-06[/C][/ROW]
[ROW][C][2400,2500[[/C][C]2450[/C][C]2[/C][C]0.000529[/C][C]0.998942[/C][C]5e-06[/C][/ROW]
[ROW][C][2500,2600[[/C][C]2550[/C][C]0[/C][C]0[/C][C]0.998942[/C][C]0[/C][/ROW]
[ROW][C][2600,2700[[/C][C]2650[/C][C]0[/C][C]0[/C][C]0.998942[/C][C]0[/C][/ROW]
[ROW][C][2700,2800[[/C][C]2750[/C][C]0[/C][C]0[/C][C]0.998942[/C][C]0[/C][/ROW]
[ROW][C][2800,2900[[/C][C]2850[/C][C]0[/C][C]0[/C][C]0.998942[/C][C]0[/C][/ROW]
[ROW][C][2900,3000[[/C][C]2950[/C][C]0[/C][C]0[/C][C]0.998942[/C][C]0[/C][/ROW]
[ROW][C][3000,3100[[/C][C]3050[/C][C]3[/C][C]0.000794[/C][C]0.999735[/C][C]8e-06[/C][/ROW]
[ROW][C][3100,3200[[/C][C]3150[/C][C]0[/C][C]0[/C][C]0.999735[/C][C]0[/C][/ROW]
[ROW][C][3200,3300[[/C][C]3250[/C][C]0[/C][C]0[/C][C]0.999735[/C][C]0[/C][/ROW]
[ROW][C][3300,3400[[/C][C]3350[/C][C]0[/C][C]0[/C][C]0.999735[/C][C]0[/C][/ROW]
[ROW][C][3400,3500[[/C][C]3450[/C][C]0[/C][C]0[/C][C]0.999735[/C][C]0[/C][/ROW]
[ROW][C][3500,3600][/C][C]3550[/C][C]1[/C][C]0.000265[/C][C]1[/C][C]3e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278707&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278707&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[505180.1370730.1370730.001371
[100,200[15010530.2786450.4157180.002786
[200,300[2508370.2214870.6372060.002215
[300,400[3505900.1561260.7933320.001561
[400,500[4503160.083620.8769520.000836
[500,600[5501830.0484260.9253770.000484
[600,700[650970.0256680.9510450.000257
[700,800[750420.0111140.9621590.000111
[800,900[850440.0116430.9738030.000116
[900,1000[950290.0076740.9814777.7e-05
[1000,1100[1050120.0031750.9846523.2e-05
[1100,1200[1150140.0037050.9883573.7e-05
[1200,1300[125090.0023820.9907382.4e-05
[1300,1400[135090.0023820.993122.4e-05
[1400,1500[145030.0007940.9939148e-06
[1500,1600[155030.0007940.9947088e-06
[1600,1700[165040.0010580.9957661.1e-05
[1700,1800[175020.0005290.9962955e-06
[1800,1900[185010.0002650.996563e-06
[1900,2000[1950000.996560
[2000,2100[205010.0002650.9968253e-06
[2100,2200[215010.0002650.9970893e-06
[2200,2300[225040.0010580.9981481.1e-05
[2300,2400[235010.0002650.9984123e-06
[2400,2500[245020.0005290.9989425e-06
[2500,2600[2550000.9989420
[2600,2700[2650000.9989420
[2700,2800[2750000.9989420
[2800,2900[2850000.9989420
[2900,3000[2950000.9989420
[3000,3100[305030.0007940.9997358e-06
[3100,3200[3150000.9997350
[3200,3300[3250000.9997350
[3300,3400[3350000.9997350
[3400,3500[3450000.9997350
[3500,3600]355010.00026513e-06


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1000 ; par2 = blue ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 1000 ; par2 = blue ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '1000'
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')
}