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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationSat, 27 Sep 2014 16:50:22 +0100
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/Sep/27/t141183314348mnq8qzkyl4tur.htm/, Retrieved Fri, 10 May 2024 02:38:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=236558, Retrieved Fri, 10 May 2024 02:38:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Internationale ha...] [2014-09-20 09:20:08] [646b2e45c853a5eeaa778aa28018f97d]
- RMP     [Histogram] [] [2014-09-27 15:50:22] [e9c24c4a54e855481a8eaf4353236c0f] [Current]
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Dataseries X:
24175
23658
26727
24397
25829
25503
24914
24875
25461
27647
28382
25259
28100
27900
28078
28479
28156
29219
28782
27078
30031
29579
26532
23995
22067
21818
23787
21551
21309
22395
22906
21430
23492
24144
24438
24689
24569
23754
28473
27051
27081
29635
27715
26373
28009
29472
30005
29777
28886
28549
33348
29017
30924
30435
29431
30290
31286
30622
31742
30391
30740
32086
33947
31312
33239
32362
32170
32665
31412
34891
33919
30706
32846
31368
33130
31665
33139
32201
32230
30287
31918
33853
32232
31484




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=236558&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=236558&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236558&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
[21000,22000[2150040.0476190.0476194.8e-05
[22000,23000[2250030.0357140.0833333.6e-05
[23000,24000[2350050.0595240.1428576e-05
[24000,25000[2450080.0952380.2380959.5e-05
[25000,26000[2550040.0476190.2857144.8e-05
[26000,27000[2650030.0357140.3214293.6e-05
[27000,28000[2750060.0714290.3928577.1e-05
[28000,29000[28500100.1190480.5119050.000119
[29000,30000[2950070.0833330.5952388.3e-05
[30000,31000[30500100.1190480.7142860.000119
[31000,32000[3150080.0952380.8095249.5e-05
[32000,33000[3250080.0952380.9047629.5e-05
[33000,34000[3350070.0833330.9880958.3e-05
[34000,35000]3450010.01190511.2e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[21000,22000[ & 21500 & 4 & 0.047619 & 0.047619 & 4.8e-05 \tabularnewline
[22000,23000[ & 22500 & 3 & 0.035714 & 0.083333 & 3.6e-05 \tabularnewline
[23000,24000[ & 23500 & 5 & 0.059524 & 0.142857 & 6e-05 \tabularnewline
[24000,25000[ & 24500 & 8 & 0.095238 & 0.238095 & 9.5e-05 \tabularnewline
[25000,26000[ & 25500 & 4 & 0.047619 & 0.285714 & 4.8e-05 \tabularnewline
[26000,27000[ & 26500 & 3 & 0.035714 & 0.321429 & 3.6e-05 \tabularnewline
[27000,28000[ & 27500 & 6 & 0.071429 & 0.392857 & 7.1e-05 \tabularnewline
[28000,29000[ & 28500 & 10 & 0.119048 & 0.511905 & 0.000119 \tabularnewline
[29000,30000[ & 29500 & 7 & 0.083333 & 0.595238 & 8.3e-05 \tabularnewline
[30000,31000[ & 30500 & 10 & 0.119048 & 0.714286 & 0.000119 \tabularnewline
[31000,32000[ & 31500 & 8 & 0.095238 & 0.809524 & 9.5e-05 \tabularnewline
[32000,33000[ & 32500 & 8 & 0.095238 & 0.904762 & 9.5e-05 \tabularnewline
[33000,34000[ & 33500 & 7 & 0.083333 & 0.988095 & 8.3e-05 \tabularnewline
[34000,35000] & 34500 & 1 & 0.011905 & 1 & 1.2e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=236558&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][21000,22000[[/C][C]21500[/C][C]4[/C][C]0.047619[/C][C]0.047619[/C][C]4.8e-05[/C][/ROW]
[ROW][C][22000,23000[[/C][C]22500[/C][C]3[/C][C]0.035714[/C][C]0.083333[/C][C]3.6e-05[/C][/ROW]
[ROW][C][23000,24000[[/C][C]23500[/C][C]5[/C][C]0.059524[/C][C]0.142857[/C][C]6e-05[/C][/ROW]
[ROW][C][24000,25000[[/C][C]24500[/C][C]8[/C][C]0.095238[/C][C]0.238095[/C][C]9.5e-05[/C][/ROW]
[ROW][C][25000,26000[[/C][C]25500[/C][C]4[/C][C]0.047619[/C][C]0.285714[/C][C]4.8e-05[/C][/ROW]
[ROW][C][26000,27000[[/C][C]26500[/C][C]3[/C][C]0.035714[/C][C]0.321429[/C][C]3.6e-05[/C][/ROW]
[ROW][C][27000,28000[[/C][C]27500[/C][C]6[/C][C]0.071429[/C][C]0.392857[/C][C]7.1e-05[/C][/ROW]
[ROW][C][28000,29000[[/C][C]28500[/C][C]10[/C][C]0.119048[/C][C]0.511905[/C][C]0.000119[/C][/ROW]
[ROW][C][29000,30000[[/C][C]29500[/C][C]7[/C][C]0.083333[/C][C]0.595238[/C][C]8.3e-05[/C][/ROW]
[ROW][C][30000,31000[[/C][C]30500[/C][C]10[/C][C]0.119048[/C][C]0.714286[/C][C]0.000119[/C][/ROW]
[ROW][C][31000,32000[[/C][C]31500[/C][C]8[/C][C]0.095238[/C][C]0.809524[/C][C]9.5e-05[/C][/ROW]
[ROW][C][32000,33000[[/C][C]32500[/C][C]8[/C][C]0.095238[/C][C]0.904762[/C][C]9.5e-05[/C][/ROW]
[ROW][C][33000,34000[[/C][C]33500[/C][C]7[/C][C]0.083333[/C][C]0.988095[/C][C]8.3e-05[/C][/ROW]
[ROW][C][34000,35000][/C][C]34500[/C][C]1[/C][C]0.011905[/C][C]1[/C][C]1.2e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=236558&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=236558&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
[21000,22000[2150040.0476190.0476194.8e-05
[22000,23000[2250030.0357140.0833333.6e-05
[23000,24000[2350050.0595240.1428576e-05
[24000,25000[2450080.0952380.2380959.5e-05
[25000,26000[2550040.0476190.2857144.8e-05
[26000,27000[2650030.0357140.3214293.6e-05
[27000,28000[2750060.0714290.3928577.1e-05
[28000,29000[28500100.1190480.5119050.000119
[29000,30000[2950070.0833330.5952388.3e-05
[30000,31000[30500100.1190480.7142860.000119
[31000,32000[3150080.0952380.8095249.5e-05
[32000,33000[3250080.0952380.9047629.5e-05
[33000,34000[3350070.0833330.9880958.3e-05
[34000,35000]3450010.01190511.2e-05



Parameters (Session):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 10 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '5'
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')
}