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, 27 Oct 2014 14:45:18 +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/Oct/27/t14144211308amc7klw8qh5opw.htm/, Retrieved Fri, 01 Nov 2024 00:03:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=247117, Retrieved Fri, 01 Nov 2024 00:03:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Care Age 10 Data] [2009-10-26 09:01:50] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Boxplot and Trimmed Means] [Care Age 7 Data] [2009-10-26 18:36:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P     [CARE Data - Boxplots and Scatterplot Matrix] [CARE Data] [2010-10-19 14:16:27] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [CARE Data - Boxplots and Scatterplot Matrix] [CARE data - works...] [2011-10-17 10:23:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP         [Boxplot and Trimmed Means] [CARE Study Age 7 ] [2013-10-17 12:59:45] [34296d8f7657c52ed60d5bff9133afec]
- RMPD            [Histogram] [WJ7ARD] [2014-10-27 14:45:18] [179cc397bc7ba643a7ca8fd40ad387b9] [Current]
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Dataseries X:
89
90
82
82
71
80
62
77
80
87
96
80
85
89
89
73
88
86
83
91
98
80
84
90
92
86
117
88
86
78
104
89
99
84
89
95
58
77
77
98
58
81
92
94
87
75
80
84
87
114
97
102
80
112
104
75
82
92
102
73
78
74
92
97
92
91
102
89
98
117
92
70
63
91
106
81
98
88
95
105
90
58
86
112
71
98
87
98
117
98
98
90
84
86
68
86
77
83
90
107
102
90
113
86
105
110
82
89
99
113
91
92
86
91
82
86
86
102
84
80
96
117
88
99
89
86
98
58
98
58
81
90
112
84
84
75
78
94
75
82
87
59
68
80
94
87
70
113
99
90
102
80
98
98
95
104
86
84
85
90
86
97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247117&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247117&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247117&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'Gwilym Jenkins' @ jenkins.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[55,60[57.560.0370370.0370370.007407
[60,65[62.520.0123460.0493830.002469
[65,70[67.520.0123460.0617280.002469
[70,75[72.570.043210.1049380.008642
[75,80[77.5110.0679010.172840.01358
[80,85[82.5280.172840.3456790.034568
[85,90[87.5330.2037040.5493830.040741
[90,95[92.5240.1481480.6975310.02963
[95,100[97.5240.1481480.8456790.02963
[100,105[102.590.0555560.9012350.011111
[105,110[107.540.0246910.9259260.004938
[110,115[112.580.0493830.9753090.009877
[115,120]117.540.02469110.004938

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[55,60[ & 57.5 & 6 & 0.037037 & 0.037037 & 0.007407 \tabularnewline
[60,65[ & 62.5 & 2 & 0.012346 & 0.049383 & 0.002469 \tabularnewline
[65,70[ & 67.5 & 2 & 0.012346 & 0.061728 & 0.002469 \tabularnewline
[70,75[ & 72.5 & 7 & 0.04321 & 0.104938 & 0.008642 \tabularnewline
[75,80[ & 77.5 & 11 & 0.067901 & 0.17284 & 0.01358 \tabularnewline
[80,85[ & 82.5 & 28 & 0.17284 & 0.345679 & 0.034568 \tabularnewline
[85,90[ & 87.5 & 33 & 0.203704 & 0.549383 & 0.040741 \tabularnewline
[90,95[ & 92.5 & 24 & 0.148148 & 0.697531 & 0.02963 \tabularnewline
[95,100[ & 97.5 & 24 & 0.148148 & 0.845679 & 0.02963 \tabularnewline
[100,105[ & 102.5 & 9 & 0.055556 & 0.901235 & 0.011111 \tabularnewline
[105,110[ & 107.5 & 4 & 0.024691 & 0.925926 & 0.004938 \tabularnewline
[110,115[ & 112.5 & 8 & 0.049383 & 0.975309 & 0.009877 \tabularnewline
[115,120] & 117.5 & 4 & 0.024691 & 1 & 0.004938 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247117&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][55,60[[/C][C]57.5[/C][C]6[/C][C]0.037037[/C][C]0.037037[/C][C]0.007407[/C][/ROW]
[ROW][C][60,65[[/C][C]62.5[/C][C]2[/C][C]0.012346[/C][C]0.049383[/C][C]0.002469[/C][/ROW]
[ROW][C][65,70[[/C][C]67.5[/C][C]2[/C][C]0.012346[/C][C]0.061728[/C][C]0.002469[/C][/ROW]
[ROW][C][70,75[[/C][C]72.5[/C][C]7[/C][C]0.04321[/C][C]0.104938[/C][C]0.008642[/C][/ROW]
[ROW][C][75,80[[/C][C]77.5[/C][C]11[/C][C]0.067901[/C][C]0.17284[/C][C]0.01358[/C][/ROW]
[ROW][C][80,85[[/C][C]82.5[/C][C]28[/C][C]0.17284[/C][C]0.345679[/C][C]0.034568[/C][/ROW]
[ROW][C][85,90[[/C][C]87.5[/C][C]33[/C][C]0.203704[/C][C]0.549383[/C][C]0.040741[/C][/ROW]
[ROW][C][90,95[[/C][C]92.5[/C][C]24[/C][C]0.148148[/C][C]0.697531[/C][C]0.02963[/C][/ROW]
[ROW][C][95,100[[/C][C]97.5[/C][C]24[/C][C]0.148148[/C][C]0.845679[/C][C]0.02963[/C][/ROW]
[ROW][C][100,105[[/C][C]102.5[/C][C]9[/C][C]0.055556[/C][C]0.901235[/C][C]0.011111[/C][/ROW]
[ROW][C][105,110[[/C][C]107.5[/C][C]4[/C][C]0.024691[/C][C]0.925926[/C][C]0.004938[/C][/ROW]
[ROW][C][110,115[[/C][C]112.5[/C][C]8[/C][C]0.049383[/C][C]0.975309[/C][C]0.009877[/C][/ROW]
[ROW][C][115,120][/C][C]117.5[/C][C]4[/C][C]0.024691[/C][C]1[/C][C]0.004938[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247117&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247117&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
[55,60[57.560.0370370.0370370.007407
[60,65[62.520.0123460.0493830.002469
[65,70[67.520.0123460.0617280.002469
[70,75[72.570.043210.1049380.008642
[75,80[77.5110.0679010.172840.01358
[80,85[82.5280.172840.3456790.034568
[85,90[87.5330.2037040.5493830.040741
[90,95[92.5240.1481480.6975310.02963
[95,100[97.5240.1481480.8456790.02963
[100,105[102.590.0555560.9012350.011111
[105,110[107.540.0246910.9259260.004938
[110,115[112.580.0493830.9753090.009877
[115,120]117.540.02469110.004938



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')
}