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 computationTue, 09 Dec 2014 11:57:55 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/09/t1418126301jl1187o0lj1mqee.htm/, Retrieved Thu, 16 May 2024 20:09:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264501, Retrieved Thu, 16 May 2024 20:09:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Maximum-likelihood Fitting - Normal Distribution] [Intrinsic Motivat...] [2010-10-12 11:57:21] [b98453cac15ba1066b407e146608df68]
- RMP   [Maximum-likelihood Fitting - Normal Distribution] [] [2014-10-14 18:01:50] [32b17a345b130fdf5cc88718ed94a974]
- RMPD      [Histogram] [paper11] [2014-12-09 11:57:55] [0015a2406d94cac8c1a56a29b9122359] [Current]
Feedback Forum

Post a new message
Dataseries X:
26
51
57
37
67
43
52
52
43
84
67
49
70
52
58
68
62
43
56
56
74
65
63
58
57
63
53
57
51
64
53
29
54
51
58
43
51
53
54
56
61
47
39
48
50
35
30
68
49
61
67
47
56
50
43
67
62
57
41
54
45
48
61
56
41
43
53
44
66
58
46
37
51
51
56
66
45
37
59
42
38
66
34
53
49
55
49
59
40
58
60
63
56
54
52
34
69
32
48
67
58
57
42
64
58
66
26
61
52
51
55
50
60
56
63
61
52
16
46
56
52
55
50
59
60
52
44
67
52
55
37
54
72
51
48
60
50
63
33
67
46
54
59
61
33
47
69
52
55
55
41
73
51
52
50
51
60
56
56
29
66
66
73
55
64
40
46
58
43
61
51
50
52
54
66
61
80
51
56
56
56
53
47
25
47
46
50
39
51
58
35
58
60
62
63
53
46
67
59
64
38
50
48
48
47
66
47
63
58
44
51
43
55
38
56
45
50
54
57
60
55
56
49
37
43
59
46
51
58
64
53
48
51
47
59
62
62
51
64
52
67
50
54
58
56
63
31
65
71
50
57
47
54
47
57
43
41
63
63
56
51
50
22
41
59
56
66
53
42
52
54
44
62
53
50
36
76
66
62
59
47
55
58
60
44
57
45
58
51
57
30
46
51
56
58
44
14
53
42
49
44
62
30
46
56
50
54
48
55
35
55
41
59
54
66
55
45
51
47
42
53
53
41
55
55
46
63
43
65
59
39
44
60
57
67
52
52
69
46
46
53
40
70
54
77
45
60
47
50
66
60
41
53
34
51
69
60
45
58
39
51
52
49
63
44
51
52
60
53
53
52
31
51
65
51
49
61
58
62
54
52
72
50
65
53
56
63
62
66
50
45
58
52
53
68
59
58
52
45
58
70
69
71
46
58
39
46
64
67
44
54
41
68
63
57
61
39
69
64
38
59
51
59
51
65
47
50
57
21
47
51
37
67
43
58
51
40
41
58
64
64
58
50
59
55
59
58
41
56
63
77
60
58
64
47
46
62
60
50
46
44
58
56
43
54
54
56
65
66
62
58
67
25
56
53
56
59
46
49
56
76
33
49
53
58
72
51
42
69
51
54
52
59
51
67
64
58
53




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=264501&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=264501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264501&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[10,15[12.510.0020080.0020080.000402
[15,20[17.510.0020080.0040160.000402
[20,25[22.520.0040160.0080320.000803
[25,30[27.560.0120480.020080.00241
[30,35[32.5120.0240960.0441770.004819
[35,40[37.5200.0401610.0843370.008032
[40,45[42.5450.0903610.1746990.018072
[45,50[47.5600.1204820.2951810.024096
[50,55[52.51180.2369480.5321290.04739
[55,60[57.51060.2128510.744980.04257
[60,65[62.5640.1285140.8734940.025703
[65,70[67.5460.0923690.9658630.018474
[70,75[72.5110.0220880.9879520.004418
[75,80[77.540.0080320.9959840.001606
[80,85]82.520.00401610.000803

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10,15[ & 12.5 & 1 & 0.002008 & 0.002008 & 0.000402 \tabularnewline
[15,20[ & 17.5 & 1 & 0.002008 & 0.004016 & 0.000402 \tabularnewline
[20,25[ & 22.5 & 2 & 0.004016 & 0.008032 & 0.000803 \tabularnewline
[25,30[ & 27.5 & 6 & 0.012048 & 0.02008 & 0.00241 \tabularnewline
[30,35[ & 32.5 & 12 & 0.024096 & 0.044177 & 0.004819 \tabularnewline
[35,40[ & 37.5 & 20 & 0.040161 & 0.084337 & 0.008032 \tabularnewline
[40,45[ & 42.5 & 45 & 0.090361 & 0.174699 & 0.018072 \tabularnewline
[45,50[ & 47.5 & 60 & 0.120482 & 0.295181 & 0.024096 \tabularnewline
[50,55[ & 52.5 & 118 & 0.236948 & 0.532129 & 0.04739 \tabularnewline
[55,60[ & 57.5 & 106 & 0.212851 & 0.74498 & 0.04257 \tabularnewline
[60,65[ & 62.5 & 64 & 0.128514 & 0.873494 & 0.025703 \tabularnewline
[65,70[ & 67.5 & 46 & 0.092369 & 0.965863 & 0.018474 \tabularnewline
[70,75[ & 72.5 & 11 & 0.022088 & 0.987952 & 0.004418 \tabularnewline
[75,80[ & 77.5 & 4 & 0.008032 & 0.995984 & 0.001606 \tabularnewline
[80,85] & 82.5 & 2 & 0.004016 & 1 & 0.000803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264501&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][10,15[[/C][C]12.5[/C][C]1[/C][C]0.002008[/C][C]0.002008[/C][C]0.000402[/C][/ROW]
[ROW][C][15,20[[/C][C]17.5[/C][C]1[/C][C]0.002008[/C][C]0.004016[/C][C]0.000402[/C][/ROW]
[ROW][C][20,25[[/C][C]22.5[/C][C]2[/C][C]0.004016[/C][C]0.008032[/C][C]0.000803[/C][/ROW]
[ROW][C][25,30[[/C][C]27.5[/C][C]6[/C][C]0.012048[/C][C]0.02008[/C][C]0.00241[/C][/ROW]
[ROW][C][30,35[[/C][C]32.5[/C][C]12[/C][C]0.024096[/C][C]0.044177[/C][C]0.004819[/C][/ROW]
[ROW][C][35,40[[/C][C]37.5[/C][C]20[/C][C]0.040161[/C][C]0.084337[/C][C]0.008032[/C][/ROW]
[ROW][C][40,45[[/C][C]42.5[/C][C]45[/C][C]0.090361[/C][C]0.174699[/C][C]0.018072[/C][/ROW]
[ROW][C][45,50[[/C][C]47.5[/C][C]60[/C][C]0.120482[/C][C]0.295181[/C][C]0.024096[/C][/ROW]
[ROW][C][50,55[[/C][C]52.5[/C][C]118[/C][C]0.236948[/C][C]0.532129[/C][C]0.04739[/C][/ROW]
[ROW][C][55,60[[/C][C]57.5[/C][C]106[/C][C]0.212851[/C][C]0.74498[/C][C]0.04257[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]64[/C][C]0.128514[/C][C]0.873494[/C][C]0.025703[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]46[/C][C]0.092369[/C][C]0.965863[/C][C]0.018474[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]11[/C][C]0.022088[/C][C]0.987952[/C][C]0.004418[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]4[/C][C]0.008032[/C][C]0.995984[/C][C]0.001606[/C][/ROW]
[ROW][C][80,85][/C][C]82.5[/C][C]2[/C][C]0.004016[/C][C]1[/C][C]0.000803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264501&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
[10,15[12.510.0020080.0020080.000402
[15,20[17.510.0020080.0040160.000402
[20,25[22.520.0040160.0080320.000803
[25,30[27.560.0120480.020080.00241
[30,35[32.5120.0240960.0441770.004819
[35,40[37.5200.0401610.0843370.008032
[40,45[42.5450.0903610.1746990.018072
[45,50[47.5600.1204820.2951810.024096
[50,55[52.51180.2369480.5321290.04739
[55,60[57.51060.2128510.744980.04257
[60,65[62.5640.1285140.8734940.025703
[65,70[67.5460.0923690.9658630.018474
[70,75[72.5110.0220880.9879520.004418
[75,80[77.540.0080320.9959840.001606
[80,85]82.520.00401610.000803



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')
}