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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 computationMon, 15 Dec 2014 18:46:01 +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/15/t141866917255eyt7t3f9udngr.htm/, Retrieved Thu, 16 May 2024 07:22:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268886, Retrieved Thu, 16 May 2024 07:22:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact52

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [skew1] [2014-12-13 18:52:26] [6aa28f01a40e2da66a40e1bfb2b28c13]
- R PD    [Histogram] [] [2014-12-15 18:46:01] [9a966322e4d935aee68609d815c1a240] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26
51
57
37
67
43
52
52
43
84
67
49
70
58
68
62
43
56
74
63
58
63
53
57
64
53
29
54
58
51
54
56
47
50
35
30
68
56
43
67
62
57
54
61
56
41
53
46
51
37
42
38
66
53
49
49
59
40
63
34
32
67
61
60
63
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

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=268886&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=268886&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268886&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
[10,20[1510.0042370.0042370.000424
[20,30[2550.0211860.0254240.002119
[30,40[35170.0720340.0974580.007203
[40,50[45470.1991530.296610.019915
[50,60[551040.4406780.7372880.044068
[60,70[65530.2245760.9618640.022458
[70,80[7570.0296610.9915250.002966
[80,90]8520.00847510.000847

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[10,20[ & 15 & 1 & 0.004237 & 0.004237 & 0.000424 \tabularnewline
[20,30[ & 25 & 5 & 0.021186 & 0.025424 & 0.002119 \tabularnewline
[30,40[ & 35 & 17 & 0.072034 & 0.097458 & 0.007203 \tabularnewline
[40,50[ & 45 & 47 & 0.199153 & 0.29661 & 0.019915 \tabularnewline
[50,60[ & 55 & 104 & 0.440678 & 0.737288 & 0.044068 \tabularnewline
[60,70[ & 65 & 53 & 0.224576 & 0.961864 & 0.022458 \tabularnewline
[70,80[ & 75 & 7 & 0.029661 & 0.991525 & 0.002966 \tabularnewline
[80,90] & 85 & 2 & 0.008475 & 1 & 0.000847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268886&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][10,20[[/C][C]15[/C][C]1[/C][C]0.004237[/C][C]0.004237[/C][C]0.000424[/C][/ROW]
[ROW][C][20,30[[/C][C]25[/C][C]5[/C][C]0.021186[/C][C]0.025424[/C][C]0.002119[/C][/ROW]
[ROW][C][30,40[[/C][C]35[/C][C]17[/C][C]0.072034[/C][C]0.097458[/C][C]0.007203[/C][/ROW]
[ROW][C][40,50[[/C][C]45[/C][C]47[/C][C]0.199153[/C][C]0.29661[/C][C]0.019915[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]104[/C][C]0.440678[/C][C]0.737288[/C][C]0.044068[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]53[/C][C]0.224576[/C][C]0.961864[/C][C]0.022458[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]7[/C][C]0.029661[/C][C]0.991525[/C][C]0.002966[/C][/ROW]
[ROW][C][80,90][/C][C]85[/C][C]2[/C][C]0.008475[/C][C]1[/C][C]0.000847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268886&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268886&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
[10,20[1510.0042370.0042370.000424
[20,30[2550.0211860.0254240.002119
[30,40[35170.0720340.0974580.007203
[40,50[45470.1991530.296610.019915
[50,60[551040.4406780.7372880.044068
[60,70[65530.2245760.9618640.022458
[70,80[7570.0296610.9915250.002966
[80,90]8520.00847510.000847


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')
}