Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_histogram.wasp
Title produced by softwareHistogram
Date of computationMon, 08 Dec 2014 17:38:27 +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/2014/Dec/08/t14180603243gc5q1ilvhii3wz.htm/, Retrieved Sun, 19 May 2024 11:37:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264123, Retrieved Sun, 19 May 2024 11:37:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean versus Median] [] [2014-12-08 16:25:59] [78252ca1523d3477f114bddbfa59edb4]
- RMPD    [Histogram] [] [2014-12-08 17:38:27] [54099b55f731ed0aca9a713a2b2a06c3] [Current]
Feedback Forum

Post a new message
Dataseries X:
2132.00
1964.00
2209.00
1965.00
2631.00
2583.00
2714.00
2248.00
2364.00
3042.00
2316.00
2735.00
2493.00
2136.00
2467.00
2414.00
2556.00
2768.00
2998.00
2573.00
3005.00
3469.00
2540.00
3187.00
2689.00
2154.00
3065.00
2397.00
2787.00
3579.00
2915.00
3025.00
3245.00
3328.00
2840.00
3342.00
2261.00
2590.00
2624.00
1860.00
2577.00
2646.00
2639.00
2807.00
2350.00
3053.00
2203.00
2471.00
1967.00
2473.00
2397.00
1904.00
2732.00
2297.00
2734.00
2719.00
2296.00
3243.00
2166.00
2261.00
2408.00
2536.00
2324.00
2178.00
2803.00
2604.00
2782.00
2656.00
2801.00
3122.00
2393.00
2233.00
2451.00
2596.00
2467.00
2210.00
2948.00
2507.00
3019.00
2401.00
2818.00
3305.00
2101.00
2582.00
2407.00
2416.00
2463.00
2228.00
2616.00
2934.00
2668.00
2808.00
2664.00
3112.00
2321.00
2718.00
2297.00
2534.00
2647.00
2064.00
2642.00
2702.00
2348.00
2734.00
2709.00
3206.00
2214.00
2531.00
2119.00
2369.00
2682.00
1840.00
2622.00
2570.00
2447.00
2871.00
2485.00
2957.00
2102.00
2250.00
2051.00
2260.00
2327.00
1781.00
2631.00
2180.00
2150.00
2837.00
1976.00
2836.00
2203.00
1770.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264123&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]0 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=264123&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264123&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Frequency Table (Histogram)
BinsMidpointAbs. FrequencyRel. FrequencyCumul. Rel. Freq.Density
[1600,1800[170020.0151520.0151527.6e-05
[1800,2000[190070.053030.0681820.000265
[2000,2200[2100120.0909090.1590910.000455
[2200,2400[2300260.196970.3560610.000985
[2400,2600[2500270.2045450.5606060.001023
[2600,2800[2700270.2045450.7651520.001023
[2800,3000[2900140.1060610.8712120.00053
[3000,3200[310090.0681820.9393940.000341
[3200,3400[330060.0454550.9848480.000227
[3400,3600]350020.01515217.6e-05

\begin{tabular}{lllllllll}
\hline
Frequency Table (Histogram) \tabularnewline
Bins & Midpoint & Abs. Frequency & Rel. Frequency & Cumul. Rel. Freq. & Density \tabularnewline
[1600,1800[ & 1700 & 2 & 0.015152 & 0.015152 & 7.6e-05 \tabularnewline
[1800,2000[ & 1900 & 7 & 0.05303 & 0.068182 & 0.000265 \tabularnewline
[2000,2200[ & 2100 & 12 & 0.090909 & 0.159091 & 0.000455 \tabularnewline
[2200,2400[ & 2300 & 26 & 0.19697 & 0.356061 & 0.000985 \tabularnewline
[2400,2600[ & 2500 & 27 & 0.204545 & 0.560606 & 0.001023 \tabularnewline
[2600,2800[ & 2700 & 27 & 0.204545 & 0.765152 & 0.001023 \tabularnewline
[2800,3000[ & 2900 & 14 & 0.106061 & 0.871212 & 0.00053 \tabularnewline
[3000,3200[ & 3100 & 9 & 0.068182 & 0.939394 & 0.000341 \tabularnewline
[3200,3400[ & 3300 & 6 & 0.045455 & 0.984848 & 0.000227 \tabularnewline
[3400,3600] & 3500 & 2 & 0.015152 & 1 & 7.6e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264123&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][1600,1800[[/C][C]1700[/C][C]2[/C][C]0.015152[/C][C]0.015152[/C][C]7.6e-05[/C][/ROW]
[ROW][C][1800,2000[[/C][C]1900[/C][C]7[/C][C]0.05303[/C][C]0.068182[/C][C]0.000265[/C][/ROW]
[ROW][C][2000,2200[[/C][C]2100[/C][C]12[/C][C]0.090909[/C][C]0.159091[/C][C]0.000455[/C][/ROW]
[ROW][C][2200,2400[[/C][C]2300[/C][C]26[/C][C]0.19697[/C][C]0.356061[/C][C]0.000985[/C][/ROW]
[ROW][C][2400,2600[[/C][C]2500[/C][C]27[/C][C]0.204545[/C][C]0.560606[/C][C]0.001023[/C][/ROW]
[ROW][C][2600,2800[[/C][C]2700[/C][C]27[/C][C]0.204545[/C][C]0.765152[/C][C]0.001023[/C][/ROW]
[ROW][C][2800,3000[[/C][C]2900[/C][C]14[/C][C]0.106061[/C][C]0.871212[/C][C]0.00053[/C][/ROW]
[ROW][C][3000,3200[[/C][C]3100[/C][C]9[/C][C]0.068182[/C][C]0.939394[/C][C]0.000341[/C][/ROW]
[ROW][C][3200,3400[[/C][C]3300[/C][C]6[/C][C]0.045455[/C][C]0.984848[/C][C]0.000227[/C][/ROW]
[ROW][C][3400,3600][/C][C]3500[/C][C]2[/C][C]0.015152[/C][C]1[/C][C]7.6e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264123&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264123&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
[1600,1800[170020.0151520.0151527.6e-05
[1800,2000[190070.053030.0681820.000265
[2000,2200[2100120.0909090.1590910.000455
[2200,2400[2300260.196970.3560610.000985
[2400,2600[2500270.2045450.5606060.001023
[2600,2800[2700270.2045450.7651520.001023
[2800,3000[2900140.1060610.8712120.00053
[3000,3200[310090.0681820.9393940.000341
[3200,3400[330060.0454550.9848480.000227
[3400,3600]350020.01515217.6e-05



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 {
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')
}