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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationTue, 01 Dec 2015 10:34:08 +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/2015/Dec/01/t1448966205p62uw3ncsapndee.htm/, Retrieved Thu, 16 May 2024 06:19:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284669, Retrieved Thu, 16 May 2024 06:19:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Histogram] [Hoeveelheid pond ...] [2015-12-01 10:34:08] [bf0d5eb0caf2a926d5d81273b164b1d3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
589
561
640
656
727
697
640
599
568
577
553
582
600
566
653
673
742
716
660
617
583
587
565
598
628
618
688
705
770
736
678
639
604
611
594
634
658
622
709
722
782
756
702
653
615
621
602
635
677
635
736
755
811
798
735
697
661
667
645
688
713
667
762
784
837
817
767
722
681
687
660
698
717
696
775
796
858
826
783
740
701
706
677
711
734
690
785
805
871
845
801
764
725
723
690
734
750
707
807
824
886
859
819
783
740
747
711
751
804
756
860
878
942
913
869
834
790
800
763
800
826
799
890
900
961
935
894
855
809
810
766
805
821
773
883
898
957
924
881
837
784
791
760
802
828
778
889
902
969
947
908
867
815
812
773
813
834
782
892
903
966
937
896
858
817
827
797
843

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284669&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284669&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284669&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[550,600[575130.0773810.0773810.001548
[600,650[625170.101190.1785710.002024
[650,700[675230.1369050.3154760.002738
[700,750[725250.148810.4642860.002976
[750,800[775290.1726190.6369050.003452
[800,850[825290.1726190.8095240.003452
[850,900[875180.1071430.9166670.002143
[900,950[925100.0595240.976190.00119
[950,1000]97540.0238110.000476

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[550,600[ & 575 & 13 & 0.077381 & 0.077381 & 0.001548 \tabularnewline
[600,650[ & 625 & 17 & 0.10119 & 0.178571 & 0.002024 \tabularnewline
[650,700[ & 675 & 23 & 0.136905 & 0.315476 & 0.002738 \tabularnewline
[700,750[ & 725 & 25 & 0.14881 & 0.464286 & 0.002976 \tabularnewline
[750,800[ & 775 & 29 & 0.172619 & 0.636905 & 0.003452 \tabularnewline
[800,850[ & 825 & 29 & 0.172619 & 0.809524 & 0.003452 \tabularnewline
[850,900[ & 875 & 18 & 0.107143 & 0.916667 & 0.002143 \tabularnewline
[900,950[ & 925 & 10 & 0.059524 & 0.97619 & 0.00119 \tabularnewline
[950,1000] & 975 & 4 & 0.02381 & 1 & 0.000476 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284669&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][550,600[[/C][C]575[/C][C]13[/C][C]0.077381[/C][C]0.077381[/C][C]0.001548[/C][/ROW]
[ROW][C][600,650[[/C][C]625[/C][C]17[/C][C]0.10119[/C][C]0.178571[/C][C]0.002024[/C][/ROW]
[ROW][C][650,700[[/C][C]675[/C][C]23[/C][C]0.136905[/C][C]0.315476[/C][C]0.002738[/C][/ROW]
[ROW][C][700,750[[/C][C]725[/C][C]25[/C][C]0.14881[/C][C]0.464286[/C][C]0.002976[/C][/ROW]
[ROW][C][750,800[[/C][C]775[/C][C]29[/C][C]0.172619[/C][C]0.636905[/C][C]0.003452[/C][/ROW]
[ROW][C][800,850[[/C][C]825[/C][C]29[/C][C]0.172619[/C][C]0.809524[/C][C]0.003452[/C][/ROW]
[ROW][C][850,900[[/C][C]875[/C][C]18[/C][C]0.107143[/C][C]0.916667[/C][C]0.002143[/C][/ROW]
[ROW][C][900,950[[/C][C]925[/C][C]10[/C][C]0.059524[/C][C]0.97619[/C][C]0.00119[/C][/ROW]
[ROW][C][950,1000][/C][C]975[/C][C]4[/C][C]0.02381[/C][C]1[/C][C]0.000476[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284669&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284669&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
[550,600[575130.0773810.0773810.001548
[600,650[625170.101190.1785710.002024
[650,700[675230.1369050.3154760.002738
[700,750[725250.148810.4642860.002976
[750,800[775290.1726190.6369050.003452
[800,850[825290.1726190.8095240.003452
[850,900[875180.1071430.9166670.002143
[900,950[925100.0595240.976190.00119
[950,1000]97540.0238110.000476


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 13 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 13 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
R code (references can be found in the software module):
par4 <- 'Unknown'
par3 <- 'FALSE'
par2 <- 'grey'
par1 <- '13'
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')
}