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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_backtobackhist.wasp
Title produced by softwareBack to Back Histogram
Date of computationTue, 21 Oct 2008 00:36:57 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/21/t1224571058ygmjqohdmxchfod.htm/, Retrieved Sun, 19 May 2024 20:27:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18335, Retrieved Sun, 19 May 2024 20:27:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Back to Back Histogram] [Back to Back Invoer] [2008-10-21 06:36:57] [35d0e2338b01fcbd55af9d60f940d770] [Current]
- RMPD    [Histogram] [Data histo] [2008-10-22 18:38:31] [ed2ba3b6182103c15c0ab511ae4e6284]
Feedback Forum
2008-10-22 18:36:04 [Tom Ardies] [reply] 
Je had beter de assen benoemt dan had het duidelijker geweest welke data bij welke histogram hoort.

Als je naar de Back to back histogram kijkt zie je duidelijk dat de verdeling in klasses fout gebeurd. Je had de data beter kunnen analyseren indien je aparte histogrammen had geblogd. Ik heb er één even rap voor jouw gedaan en hierin kan je beter de klasses en spreiding zien van je gegevens: http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/22/t122470037213ja40jlbbwwyho.htm
2008-10-22 18:42:53 [Tom Ardies] [reply] 
De back to back histogram maakt ons hier niet veel wijzer. enkel dat de data andere waardes hebben. De assen hadden beter benoemd geweest in plaats van enkel de titel van de berekening.

De rechter histogram is te onnauwkeurig om daar iets over te kunnen zeggen van spreiding of scheefheid. Ik heb daarom die histogram gereproduceerd als één histogram. Hierin kan je beter de verdeling van gegevens bekijken: http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/22/t1224700733gxloxtj1am9f95o.htm
2008-10-22 18:44:31 [Tom Ardies] [reply] 
Die eerste commentaar hoort bij ander back 2 back.
2008-10-27 18:47:20 [Jeroen Aerts] [reply] 
Het berekenen van dit back-to-back histogram haalt niet veel uit, zelf trek je er ook geen conclusies uit en dat ik ook niet. Maar zoals hier boven al vermeld, en dat is wel een goede oplossing, is de 2 histogrammen apart gaan bekijken en zien of er veel verschillen inzitten.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10772.8
9987.7
8638.7
11063.7
11855.7
10684.5
11337.4
10478
11123.9
12909.3
11339.9
10462.2
12733.5
10519.2
10414.9
12476.8
12384.6
12266.7
12919.9
11497.3
12142
13919.4
12656.8
12034.1
13199.7
10881.3
11301.2
13643.9
12517
13981.1
14275.7
13435
13565.7
16216.3
12970
14079.9
14235
12213.4
12581
14130.4
14210.8
14378.5
13142.8
13714.7
13621.9
15379.8
13306.3
14391.2
14909.9
14025.4
12951.2
14344.3
16213.3
15544.5
14750.6
17292.7
17568.5
17930.8
18644.7
16694.8
17242.8
Dataseries Y:
Download CSV
Histogram 
3421.3
3531.4
3219.2
3552.3
3787.7
3392.7
3550
3681.9
3519.1
4283.2
4046.2
3824.9
4793.1
3977.7
3983.4
4152.9
4286.1
4348.1
3949.3
4166.7
4217.9
4528.2
4232.2
4470.9
5121.2
4170.8
4398.6
4491.4
4251.8
4901.9
4745.2
4666.9
4210.4
5273.6
4095.3
4610.1
4718.1
4185.5
4314.7
4422.6
5059.2
5043.6
4436.6
4922.6
4454.8
5058.7
4768.9
5171.8
4989.3
5202.1
4838.4
4876.5
5845.3
5686.3
4753.8
6620.4
5597.2
5643.5
6357.3
5909.1
6165.8

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18335&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18335&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18335&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'Gwilym Jenkins' @ 72.249.127.135


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = grey ; par3 = TRUE ;
Parameters (R input):
par1 = grey ; par2 = grey ; par3 = TRUE ; par4 = ; par5 = ;
R code (references can be found in the software module):
if (par3 == 'TRUE') par3 <- TRUE
if (par3 == 'FALSE') par3 <- FALSE
library(Hmisc)
z <- data.frame(cbind(x,y))
names(z) <- list(par4,par5)
bitmap(file='plot.png')
out <- histbackback(z, probability=par3, main = main, ylab = ylab)
barplot(-out$left, col=par1, horiz=TRUE, space=0, add=TRUE, axes=FALSE)
barplot(out$right, col=par2, horiz=TRUE, space=0, add=TRUE, axes=FALSE)
dev.off()