Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSun, 21 Feb 2016 11:24:47 +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/2016/Feb/21/t1456053916erjvolv78rfdhga.htm/, Retrieved Sat, 27 Apr 2024 15:23:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=292376, Retrieved Sat, 27 Apr 2024 15:23:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [vervaardiging cac...] [2016-02-20 18:09:16] [74be16979710d4c4e7c6647856088456]
- R P   [Histogram] [] [2016-02-21 11:23:50] [600dd77654e74003cbd3c8172f556ebd]
-           [Histogram] [] [2016-02-21 11:24:47] [bfab382a4ab6d7836f6b75894769f754] [Current]
-   P         [Histogram] [] [2016-02-21 11:34:19] [600dd77654e74003cbd3c8172f556ebd]
- RMP         [Kernel Density Estimation] [] [2016-02-21 11:54:57] [600dd77654e74003cbd3c8172f556ebd]
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Dataseries X:
100
99
99.3
99.5
100.7
102.9
101.2
99.5
99.5
99.5
99.4
99.5
99.7
99.8
99.8
100.1
100
100
100.1
100.1
100
99.9
99.9
99.8
100.4
102.2
103.1
103
102.9
102.8
103
103.5
103.6
103.2
103
103
106.1
104.8
105.3
106.3
107.9
106.1
106.8
108.7
110.8
111.8
111.3
111.7
110.8
110.3
110.5
110.5
112.5
113
113.5
112.8
109.5
111.5
111.5
111.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292376&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292376&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'Sir Maurice George Kendall' @ kendall.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[99,100[99.5140.2333330.2333330.233333
[100,101[100.590.150.3833330.15
[101,102[101.510.0166670.40.016667
[102,103[102.540.0666670.4666670.066667
[103,104[103.580.1333330.60.133333
[104,105[104.510.0166670.6166670.016667
[105,106[105.510.0166670.6333330.016667
[106,107[106.540.0666670.70.066667
[107,108[107.510.0166670.7166670.016667
[108,109[108.510.0166670.7333330.016667
[109,110[109.510.0166670.750.016667
[110,111[110.550.0833330.8333330.083333
[111,112[111.560.10.9333330.1
[112,113[112.520.0333330.9666670.033333
[113,114]113.520.03333310.033333

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[99,100[ & 99.5 & 14 & 0.233333 & 0.233333 & 0.233333 \tabularnewline
[100,101[ & 100.5 & 9 & 0.15 & 0.383333 & 0.15 \tabularnewline
[101,102[ & 101.5 & 1 & 0.016667 & 0.4 & 0.016667 \tabularnewline
[102,103[ & 102.5 & 4 & 0.066667 & 0.466667 & 0.066667 \tabularnewline
[103,104[ & 103.5 & 8 & 0.133333 & 0.6 & 0.133333 \tabularnewline
[104,105[ & 104.5 & 1 & 0.016667 & 0.616667 & 0.016667 \tabularnewline
[105,106[ & 105.5 & 1 & 0.016667 & 0.633333 & 0.016667 \tabularnewline
[106,107[ & 106.5 & 4 & 0.066667 & 0.7 & 0.066667 \tabularnewline
[107,108[ & 107.5 & 1 & 0.016667 & 0.716667 & 0.016667 \tabularnewline
[108,109[ & 108.5 & 1 & 0.016667 & 0.733333 & 0.016667 \tabularnewline
[109,110[ & 109.5 & 1 & 0.016667 & 0.75 & 0.016667 \tabularnewline
[110,111[ & 110.5 & 5 & 0.083333 & 0.833333 & 0.083333 \tabularnewline
[111,112[ & 111.5 & 6 & 0.1 & 0.933333 & 0.1 \tabularnewline
[112,113[ & 112.5 & 2 & 0.033333 & 0.966667 & 0.033333 \tabularnewline
[113,114] & 113.5 & 2 & 0.033333 & 1 & 0.033333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=292376&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][99,100[[/C][C]99.5[/C][C]14[/C][C]0.233333[/C][C]0.233333[/C][C]0.233333[/C][/ROW]
[ROW][C][100,101[[/C][C]100.5[/C][C]9[/C][C]0.15[/C][C]0.383333[/C][C]0.15[/C][/ROW]
[ROW][C][101,102[[/C][C]101.5[/C][C]1[/C][C]0.016667[/C][C]0.4[/C][C]0.016667[/C][/ROW]
[ROW][C][102,103[[/C][C]102.5[/C][C]4[/C][C]0.066667[/C][C]0.466667[/C][C]0.066667[/C][/ROW]
[ROW][C][103,104[[/C][C]103.5[/C][C]8[/C][C]0.133333[/C][C]0.6[/C][C]0.133333[/C][/ROW]
[ROW][C][104,105[[/C][C]104.5[/C][C]1[/C][C]0.016667[/C][C]0.616667[/C][C]0.016667[/C][/ROW]
[ROW][C][105,106[[/C][C]105.5[/C][C]1[/C][C]0.016667[/C][C]0.633333[/C][C]0.016667[/C][/ROW]
[ROW][C][106,107[[/C][C]106.5[/C][C]4[/C][C]0.066667[/C][C]0.7[/C][C]0.066667[/C][/ROW]
[ROW][C][107,108[[/C][C]107.5[/C][C]1[/C][C]0.016667[/C][C]0.716667[/C][C]0.016667[/C][/ROW]
[ROW][C][108,109[[/C][C]108.5[/C][C]1[/C][C]0.016667[/C][C]0.733333[/C][C]0.016667[/C][/ROW]
[ROW][C][109,110[[/C][C]109.5[/C][C]1[/C][C]0.016667[/C][C]0.75[/C][C]0.016667[/C][/ROW]
[ROW][C][110,111[[/C][C]110.5[/C][C]5[/C][C]0.083333[/C][C]0.833333[/C][C]0.083333[/C][/ROW]
[ROW][C][111,112[[/C][C]111.5[/C][C]6[/C][C]0.1[/C][C]0.933333[/C][C]0.1[/C][/ROW]
[ROW][C][112,113[[/C][C]112.5[/C][C]2[/C][C]0.033333[/C][C]0.966667[/C][C]0.033333[/C][/ROW]
[ROW][C][113,114][/C][C]113.5[/C][C]2[/C][C]0.033333[/C][C]1[/C][C]0.033333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=292376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=292376&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
[99,100[99.5140.2333330.2333330.233333
[100,101[100.590.150.3833330.15
[101,102[101.510.0166670.40.016667
[102,103[102.540.0666670.4666670.066667
[103,104[103.580.1333330.60.133333
[104,105[104.510.0166670.6166670.016667
[105,106[105.510.0166670.6333330.016667
[106,107[106.540.0666670.70.066667
[107,108[107.510.0166670.7166670.016667
[108,109[108.510.0166670.7333330.016667
[109,110[109.510.0166670.750.016667
[110,111[110.550.0833330.8333330.083333
[111,112[111.560.10.9333330.1
[112,113[112.520.0333330.9666670.033333
[113,114]113.520.03333310.033333



Parameters (Session):
par1 = 12 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 12 ; 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 {
barplot(mytab <- sort(table(x),T),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')
}