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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_skewness_kurtosis_plot.wasp
Title produced by softwareSkewness-Kurtosis Plot
Date of computationFri, 18 Nov 2016 18:36:45 +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/2016/Nov/18/t1479491209h462jvf0al6kgsa.htm/, Retrieved Thu, 02 May 2024 19:11:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296832, Retrieved Thu, 02 May 2024 19:11:57 +0000
QR Codes:

Original text written by user:Hier gaan we kijken naar de Cullen and Frey graph. Gamma verdeling= stippellijn= geeft alle mogelijk verdelingen van kurtosis en skewness weer. Normaalverdeling is er maar 1 punt qua skewness en kurtosis mogelijk. Uniforme verdeling is er maar 1 punt qua skewness en kurtosis mogelijk.De vraag is: Welke verdeling hebben onze data? bv is het een normaalverdeling: sterretje valt buiten de puntenwolk. 0nze reeks is dus niet normaal verdeeld hier. uniforme verdeling. Er is minsten 1 oranje punt binnen de driehoek. Er is een zeker kans dat onze reeks een uniforme verdeling is, maar echt overtuigend is het niet. Als het blauwe bolletje (midden punten wolk waar de meeste observaties liggen) en de driehoek samenvalt, heb je eens schot in de roos. Als de driehoek omsingeld wordt door de puntenwolk is het ook al goed. We kunnen nu al uitspraken doen over de waarschijnlijk hoe iets al dan niet verdeeld is.
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Skewness and Kurtosis Test] [F1 competitie n 1...] [2016-11-18 16:59:44] [95b24d8e95676a05c34b365fb6729343]
- RM      [Skewness-Kurtosis Plot] [Skewness and kurt...] [2016-11-18 17:36:45] [673dd365cbcfe0c4e35658a2fe545652] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3106.78
3235.94
2998.12
2896.3
2952
3060.24
2988.32
2889
2881.82
2969.22
3026.2
3146.08
3032.48
2719.74
2785.18
2797.28
2783.7
2822.84
2835.8
2823.22
2879.14
3003.5
2910.7
2895.54
2982.36
3087.2
3195.28
3272.72
3390.6
3676.12
4052.18
4431.2
4554.96
4279.7
4391.86
4482.82
4530.68
4580.66
4623.5
4720.14
4811.82
4980.18
5174.28
5181.24

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296832&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]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296832&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 time3 seconds
R ServerBig Analytics Cloud Computing Center


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 8 ; par2 = 0 ;
Parameters (R input):
R code (references can be found in the software module):
library(fitdistrplus)
bitmap(file='plot1.png')
plotdist(x, histo = TRUE, demp = TRUE)
dev.off()
bitmap(file='plot.png')
descdist(x, boot = 1000)
dev.off()