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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationWed, 16 Aug 2017 16:32:57 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/16/t150289407178ecmril70462mj.htm/, Retrieved Sun, 12 May 2024 07:55:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307410, Retrieved Sun, 12 May 2024 07:55:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [] [2017-08-16 14:32:57] [a0ce0558b0177aac41d3fe22da4ea7eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
59.400
57.200
60.500
48.400
62.700
61.600
66.000
68.200
75.900
66.000
62.700
78.100
66.000
49.500
58.300
44.000
61.600
50.600
67.100
60.500
63.800
71.500
70.400
83.600
60.500
50.600
56.100
40.700
58.300
45.100
63.800
60.500
53.900
77.000
69.300
79.200
59.400
55.000
49.500
40.700
53.900
48.400
66.000
63.800
55.000
73.700
68.200
88.000
70.400
42.900
42.900
42.900
50.600
50.600
68.200
62.700
56.100
70.400
64.900
93.500
73.700
42.900
45.100
37.400
51.700
59.400
74.800
73.700
59.400
69.300
61.600
88.000
67.100
53.900
48.400
36.300
53.900
64.900
75.900
71.500
52.800
75.900
59.400
91.300
75.900
55.000
50.600
34.100
53.900
51.700
78.100
78.100
59.400
77.000
57.200
89.100
75.900
56.100
42.900
29.700
58.300
56.100
73.700
84.700
62.700
70.400
52.800
91.300

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig 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=307410&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=307410&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307410&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[20,30[2510.0092590.0092590.000926
[30,40[3530.0277780.0370370.002778
[40,50[45150.1388890.1759260.013889
[50,60[55320.2962960.4722220.02963
[60,70[65270.250.7222220.025
[70,80[75220.2037040.9259260.02037
[80,90[8550.0462960.9722220.00463
[90,100]9530.02777810.002778

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[20,30[ & 25 & 1 & 0.009259 & 0.009259 & 0.000926 \tabularnewline
[30,40[ & 35 & 3 & 0.027778 & 0.037037 & 0.002778 \tabularnewline
[40,50[ & 45 & 15 & 0.138889 & 0.175926 & 0.013889 \tabularnewline
[50,60[ & 55 & 32 & 0.296296 & 0.472222 & 0.02963 \tabularnewline
[60,70[ & 65 & 27 & 0.25 & 0.722222 & 0.025 \tabularnewline
[70,80[ & 75 & 22 & 0.203704 & 0.925926 & 0.02037 \tabularnewline
[80,90[ & 85 & 5 & 0.046296 & 0.972222 & 0.00463 \tabularnewline
[90,100] & 95 & 3 & 0.027778 & 1 & 0.002778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307410&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][20,30[[/C][C]25[/C][C]1[/C][C]0.009259[/C][C]0.009259[/C][C]0.000926[/C][/ROW]
[ROW][C][30,40[[/C][C]35[/C][C]3[/C][C]0.027778[/C][C]0.037037[/C][C]0.002778[/C][/ROW]
[ROW][C][40,50[[/C][C]45[/C][C]15[/C][C]0.138889[/C][C]0.175926[/C][C]0.013889[/C][/ROW]
[ROW][C][50,60[[/C][C]55[/C][C]32[/C][C]0.296296[/C][C]0.472222[/C][C]0.02963[/C][/ROW]
[ROW][C][60,70[[/C][C]65[/C][C]27[/C][C]0.25[/C][C]0.722222[/C][C]0.025[/C][/ROW]
[ROW][C][70,80[[/C][C]75[/C][C]22[/C][C]0.203704[/C][C]0.925926[/C][C]0.02037[/C][/ROW]
[ROW][C][80,90[[/C][C]85[/C][C]5[/C][C]0.046296[/C][C]0.972222[/C][C]0.00463[/C][/ROW]
[ROW][C][90,100][/C][C]95[/C][C]3[/C][C]0.027778[/C][C]1[/C][C]0.002778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307410&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307410&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
[20,30[2510.0092590.0092590.000926
[30,40[3530.0277780.0370370.002778
[40,50[45150.1388890.1759260.013889
[50,60[55320.2962960.4722220.02963
[60,70[65270.250.7222220.025
[70,80[75220.2037040.9259260.02037
[80,90[8550.0462960.9722220.00463
[90,100]9530.02777810.002778


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 {
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')
}