Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 17 Dec 2012 18:23:01 -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/2012/Dec/17/t135578659884kj33cjnljld9z.htm/, Retrieved Thu, 31 Oct 2024 23:25:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201250, Retrieved Thu, 31 Oct 2024 23:25:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2012-12-17 23:23:01] [5ea595149c423d240797ea96f874e024] [Current]
Feedback Forum

Post a new message
Dataseries X:
NA
NA
NA
NA
NA
NA
-6.14157407407407
2.76675925925926
-2.47476851851854
-24.749212962963
-27.3419907407408
-24.0996296296296
-33.0386574074074
-8.16893518518521
-7.48046296296292
7.31495370370374
37.2350925925925
-3.20490740740735
51.4375925925926
27.5334259259259
4.37939814814808
30.0091203703704
-13.662824074074
-0.0871296296296009
28.6988425925926
45.4268981481482
31.4987037037038
19.1482870370371
12.1559259259259
-21.496574074074
-5.81240740740742
-26.7249074074074
-3.03726851851854
-15.2283796296296
6.97884259259257
23.2045370370371
-14.9094907407408
-25.0981018518518
-17.2137962962962
-11.4850462962962
-4.57740740740738
-37.1465740740741
-13.4457407407407
-5.92074074074074
22.5502314814815
26.9341203703704
29.5996759259259
9.35870370370372
-17.2886574074074
-17.2439351851852
-27.3471296296296
-1.68921296296298
16.6309259259259
-28.5215740740741
3.86675925925925
20.9292592592593
22.5293981481481
14.5757870370371
5.99134259259262
2.15870370370371
-9.53865740740738
-30.7189351851852
-18.6679629629629
15.4607870370371
11.4434259259259
-46.9799074074074
-33.029074074074
-35.5249074074074
-24.1331018518519
-30.8908796296296
-25.2169907407408
-8.68712962962957
21.4780092592593
39.6810648148148
52.869537037037
61.0149537037037
52.9142592592593
-24.8965740740741
-2.71657407407406
9.32925925925923
28.7460648148148
0.100787037037037
4.27467592592592
-0.216296296296264
0.0946759259259693
-9.41060185185182
-4.65129629629627
29.5566203703704
8.38509259259257
-40.0507407407407
-33.4207407407407
-9.84990740740739
-8.51226851851851
4.63412037037045
9.95384259259265
13.6003703703704
-15.642824074074
-21.7314351851851
2.63203703703704
5.66495370370376
36.0350925925926
0.678425925925978
5.86675925925925
-14.7165740740741
-14.6414351851852
-15.536712962963
14.9830092592592
20.7587037037037
2.93634259259267
-16.4564351851852
-20.4554629629629
-2.01421296296292
15.955925925926
-12.2924074074073
-23.616574074074
-37.3499074074074
-39.5247685185184
-47.3783796296295
-21.7961574074074
-20.3746296296297
1.50300925925922
41.0018981481482
53.2570370370371
72.7816203703704
62.4142592592594
22.8575925925927
31.9167592592593
15.3375925925926
-15.9414351851852
-21.074212962963
-26.3378240740741
13.0378703703704
13.0613425925926
18.8977314814815
11.2487037037037
-16.5350462962962
-15.9232407407407
-40.571574074074
-27.9457407407407
-16.3624074074074
-9.31226851851858
10.463287037037
29.2288425925926
14.6670370370371
-1.53865740740736
-35.1522685185184
14.1362037037037
-2.88087962962953
-7.30657407407398
-6.28824074074072
-18.5915740740741
-16.6540740740741
-50.5581018518519
-23.1158796296297
-12.1378240740741
26.8212037037036
30.8696759259259
47.6102314814815
41.982037037037
24.4857870370371
22.5642592592593
15.8117592592592
10.8917592592592
-1.67490740740749
-14.4956018518519
-6.92421296296294
-13.1711574074073
3.17537037037044
-2.75949074074066
-17.1856018518518
-4.57629629629628
-5.08504629629624
28.2600925925926
-15.821574074074
-28.1582407407407
3.16675925925927
-19.3414351851851
-26.6575462962963
0.703842592592707
1.51287037037042
12.3113425925926
28.0435648148148
9.04870370370378
3.87745370370374
19.1892592592593
6.17425925925932
-9.37074074074064
-14.041574074074
-21.6247685185184
-11.8242129629629
15.6955092592593
9.66287037037034
11.8113425925926
1.26439814814819
2.88620370370376
5.62745370370379
-0.677407407407372
22.8034259259259
-25.4957407407407
-2.61657407407404
-9.81226851851858
3.21328703703711
-3.37532407407406
7.47537037037034
-9.85949074074063
8.23939814814821
-12.1971296296295
11.3482870370372
8.30592592592598
24.1367592592593
-7.65407407407406
4.95009259259257
-1.65810185185188
6.99245370370375
8.51217592592593
0.99620370370377
-23.0969907407408
-41.2189351851852
-26.7679629629629
-9.88087962962965
19.6517592592592
28.503425925926
0.687592592592637
9.50009259259258
-4.15393518518511
8.29245370370376
0.0538425925926163
8.6920370370371
-16.0969907407407
-22.5647685185185
-24.1971296296297
-16.4017129629629
-19.4524074074073
23.1200925925927
10.8625925925926
11.758425925926
25.0418981481482
47.388287037037
22.5413425925926
3.72953703703706
-33.892824074074
-19.3856018518518
-29.7721296296296
-30.0725462962963
-24.6399074074074
36.2325925925927
24.0375925925926
13.5542592592593
17.6377314814815
24.3049537037037
9.39967592592598
-6.65379629629626
-33.080324074074
-36.1772685185185
-32.1429629629629
-15.0225462962962
-20.2274074074074
14.4950925925926
16.1292592592592
10.758425925926
30.1293981481481
25.8341203703704
-17.200324074074
-36.5537962962963
-42.7261574074074
-22.7189351851852
-16.4971296296296
-5.61004629629616
-15.2982407407408
24.0784259259259
16.958425925926
4.39592592592589
17.0293981481481
18.7841203703704
23.3080092592593
17.3712037037038
15.1238425925926
3.36856481481487
-5.6137962962963
-16.8350462962963
-28.0690740740741
7.57009259259257
16.7042592592592
21.4625925925926
17.6293981481481
6.27162037037033
9.65800925925925
-3.07462962962961
-0.1636574074073
-9.79393518518503
-4.38046296296289
-14.5475462962963
-26.2149074074074
13.8367592592594
19.6834259259259
25.333425925926
29.0335648148148
31.163287037037
-6.09615740740742
-17.620462962963
-29.9219907407407
-15.2564351851852
-20.292962962963
-8.63504629629631
-21.3857407407407
11.6825925925927
6.35425925925927
1.20842592592595
12.9752314814815
-12.9450462962962
-6.92115740740735
-11.5871296296296
5.02384259259264
4.81023148148148
-17.3262962962963
-31.9267129629629
-38.8232407407407
-3.39240740740735
-11.6249074074072
-43.8749074074073
-22.0872685185184
-51.7450462962962
-38.1128240740741
-25.0037962962963
83.6113425925927
64.8768981481481
72.0028703703705
39.7274537037038
25.3475925925926
36.1200925925926
21.1250925925926
2.67092592592621
8.20439814814836
3.57578703703712
-9.66282407407391
-5.1662962962962
25.9655092592593
8.42273148148149
-15.2471296296296
-34.5100462962963
-69.9024074074075
-6.36324074074071
13.4334259259261
20.6459259259261
8.90856481481501
6.64245370370372
13.512175925926
6.48370370370378
19.3655092592594
42.8352314814816
15.8487037037039
-37.4892129629629
-52.5899074074074
12.6409259259258
-4.3207407407408
18.6209259259259
15.1252314814816
17.5007870370372
15.249675925926
-24.970462962963
10.3113425925927
-7.58560185185195
-3.97212962962965
-36.776712962963
-32.7899074074074
-15.1049074074074
NA
NA
NA
NA
NA
NA




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201250&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201250&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[-80,-60[-7010.0026880.0026880.000139
[-60,-40[-50100.0268820.029570.001389
[-40,-20[-30630.1693550.1989250.00875
[-20,0[-101050.2822580.4811830.014583
[0,20[101160.3118280.7930110.016111
[20,40[30490.131720.9247310.006806
[40,60[50100.0268820.9516130.001389
[60,80[7050.0134410.9650540.000694
[80,100]9010.0026880.9677420.000139

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[-80,-60[ & -70 & 1 & 0.002688 & 0.002688 & 0.000139 \tabularnewline
[-60,-40[ & -50 & 10 & 0.026882 & 0.02957 & 0.001389 \tabularnewline
[-40,-20[ & -30 & 63 & 0.169355 & 0.198925 & 0.00875 \tabularnewline
[-20,0[ & -10 & 105 & 0.282258 & 0.481183 & 0.014583 \tabularnewline
[0,20[ & 10 & 116 & 0.311828 & 0.793011 & 0.016111 \tabularnewline
[20,40[ & 30 & 49 & 0.13172 & 0.924731 & 0.006806 \tabularnewline
[40,60[ & 50 & 10 & 0.026882 & 0.951613 & 0.001389 \tabularnewline
[60,80[ & 70 & 5 & 0.013441 & 0.965054 & 0.000694 \tabularnewline
[80,100] & 90 & 1 & 0.002688 & 0.967742 & 0.000139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201250&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]1[/C][C]0.002688[/C][C]0.002688[/C][C]0.000139[/C][/ROW]
[ROW][C][-60,-40[[/C][C]-50[/C][C]10[/C][C]0.026882[/C][C]0.02957[/C][C]0.001389[/C][/ROW]
[ROW][C][-40,-20[[/C][C]-30[/C][C]63[/C][C]0.169355[/C][C]0.198925[/C][C]0.00875[/C][/ROW]
[ROW][C][-20,0[[/C][C]-10[/C][C]105[/C][C]0.282258[/C][C]0.481183[/C][C]0.014583[/C][/ROW]
[ROW][C][0,20[[/C][C]10[/C][C]116[/C][C]0.311828[/C][C]0.793011[/C][C]0.016111[/C][/ROW]
[ROW][C][20,40[[/C][C]30[/C][C]49[/C][C]0.13172[/C][C]0.924731[/C][C]0.006806[/C][/ROW]
[ROW][C][40,60[[/C][C]50[/C][C]10[/C][C]0.026882[/C][C]0.951613[/C][C]0.001389[/C][/ROW]
[ROW][C][60,80[[/C][C]70[/C][C]5[/C][C]0.013441[/C][C]0.965054[/C][C]0.000694[/C][/ROW]
[ROW][C][80,100][/C][C]90[/C][C]1[/C][C]0.002688[/C][C]0.967742[/C][C]0.000139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201250&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)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[-80,-60[-7010.0026880.0026880.000139
[-60,-40[-50100.0268820.029570.001389
[-40,-20[-30630.1693550.1989250.00875
[-20,0[-101050.2822580.4811830.014583
[0,20[101160.3118280.7930110.016111
[20,40[30490.131720.9247310.006806
[40,60[50100.0268820.9516130.001389
[60,80[7050.0134410.9650540.000694
[80,100]9010.0026880.9677420.000139



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')
}