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Author

*Unverified author*

R Software Module

rwasp_histogram.wasp

Title produced by software

Histogram

Date of computation

Mon, 27 Aug 2018 02:01:14 +0200

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Aug/27/t153532811831azfcnq1a2xsmj.htm/, Retrieved Sat, 04 May 2024 00:00:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315109, Retrieved Sat, 04 May 2024 00:00:54 +0000

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Original text written by user:

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No (this computation is public)

User-defined keywords

Estimated Impact

106

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Histogram] [Dollar amount] [2018-08-27 00:01:14] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

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60,552.08
60,495.92
60,370.80
60,266.18
60,260.53
60,201.33
60,159.31
60,064.80
60,064.80
60,051.94
60,031.80
60,027.96
60,013.51
59,931.10
59,765.58
59,675.13
59,536.83
59,479.20
59,471.57
59,466.59
59,462.51
59,452.67
59,431.89
59,409.05
59,268.61
59,266.94
59,220.76
59,022.08
59,022.08
58,963.95
58,911.00
58,907.32
58,886.22
58,824.32
58,824.32
58,824.32
58,824.32
58,813.52
58,740.74
58,678.26
58,482.11
58,466.17
58,446.64
58,412.97
58,406.65
58,370.39
58,240.05
58,066.03
58,041.92
57,971.65
57,818.41
57,747.76
57,701.72
57,446.83
57,446.83
57,290.23
57,177.64
57,177.64
57,159.17
57,115.01
57,115.01
57,115.01
57,115.01
57,106.66
57,092.38
57,025.34
56,886.27
56,877.70
56,791.62
56,715.43
56,525.11
56,520.63
56,520.63
56,520.63
56,474.42
56,429.89
56,411.05
56,352.04
56,344.44
56,317.82
56,267.12
56,267.12
56,076.81
55,913.43
55,858.46
55,741.98
55,708.62
55,707.42
55,609.06
55,593.96
55,581.89
55,572.90
55,567.92
55,455.77
55,349.55
55,282.28
55,198.18
55,161.71
55,161.43
55,150.90
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,147.80
55,094.80
54,949.00
54,884.31
54,882.48
54,826.60
54,785.84
54,770.02
54,712.89
54,652.77
54,586.87
54,555.28
54,508.77
54,441.42
54,302.77
54,242.57
54,176.47
54,069.43
54,035.88
54,023.80
53,975.57
53,953.56
53,889.07
53,765.93
53,759.61
53,743.00
53,734.27
53,731.51
53,692.67
53,656.39
53,515.29
53,512.30
53,503.68
53,503.68
53,503.68
53,503.68
53,481.10
53,477.49
53,444.17
53,341.75
53,333.84
53,330.34
53,317.78
53,309.54
53,287.69
53,285.68
53,285.67
53,285.67
53,159.98
53,158.42
53,092.74
53,067.97
53,029.13
53,029.13
52,948.19
52,907.92
52,905.91
52,839.35
52,750.99
52,740.06
52,684.53
52,663.88
52,594.07
52,571.15
52,422.85
52,355.34
52,342.34
52,188.87
52,122.56
52,074.84
52,057.65
52,050.40
51,955.83
51,916.74
51,903.96
51,884.79
51,728.49
51,719.15
51,529.81
51,451.65
51,425.73
51,425.73
51,366.58
51,337.93
51,252.63
51,246.99
51,002.86
51,001.14
50,853.04
50,840.59
50,835.06
50,724.17
50,687.62
50,608.24
50,523.65
50,520.23
50,475.22
50,453.81
50,440.37
50,419.26
50,378.32
50,258.81
50,186.46
50,184.87
50,165.58
50,165.58
50,125.93
50,041.01
50,015.23
50,012.71
50,006.82

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315109&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315109&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315109&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

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 {
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,'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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code