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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationSun, 21 Oct 2007 11:26:46 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/21/qyhnfd7xv3ynnau1192991194.htm/, Retrieved Thu, 09 May 2024 07:21:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1289, Retrieved Thu, 09 May 2024 07:21:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ3 Univariate explorative data analysis
Estimated Impact479

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Univariate Explorative Data Analysis] [Investigating Dis...] [2007-10-21 18:26:46] [3cbd35878d9bd3c68c81c01c5c6ec146] [Current]
F    D    [Univariate Explorative Data Analysis] [q3 univariate exp...] [2008-10-22 13:40:40] [7173087adebe3e3a714c80ea2417b3eb]
F           [Univariate Explorative Data Analysis] [q3] [2008-10-27 10:30:59] [e43247bc0ab243a5af99ac7f55ba0b41]
F           [Univariate Explorative Data Analysis] [Q3 Univariate Exp...] [2008-10-27 19:44:51] [c993f605b206b366f754f7f8c1fcc291]
- R  D    [Univariate Explorative Data Analysis] [q3 Univariate exp...] [2008-10-22 13:57:47] [e43247bc0ab243a5af99ac7f55ba0b41]
F R PD    [Univariate Explorative Data Analysis] [Univariate EDA Q7...] [2008-10-22 14:37:05] [819b576fab25b35cfda70f80599828ec]
-   P       [Univariate Explorative Data Analysis] [Q7 Univariate exp...] [2008-11-02 14:15:44] [d134696a922d84037f02d49ded84b0bd]
- RMP       [Central Tendency] [] [2008-11-03 08:48:28] [f5709eefd05c649ca6dad46019ffd879]
F   PD    [Univariate Explorative Data Analysis] [Q3:] [2008-10-23 10:25:21] [cb714085b233acee8e8acd879ea442b6]
-    D    [Univariate Explorative Data Analysis] [Univariate explor...] [2008-10-23 10:38:46] [adb6b6905cde49db36d59ca44433140d]
F    D    [Univariate Explorative Data Analysis] [] [2008-10-23 10:41:45] [2a30350413961f11db13c46be07a5f73]
-    D    [Univariate Explorative Data Analysis] [Q3:Univariate EDA] [2008-10-23 11:24:01] [1ce0d16c8f4225c977b42c8fa93bc163]
-    D    [Univariate Explorative Data Analysis] [vraag 1: Q3 Growt...] [2008-10-23 11:28:10] [82d201ca7b4e7cd2c6f885d29b5b6937]
F   PD    [Univariate Explorative Data Analysis] [Q3 met lags] [2008-10-23 13:08:11] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-           [Univariate Explorative Data Analysis] [Q3] [2008-10-27 09:28:09] [b5373f20234c18c6452d5f98d8abf0fe]
- RMP       [Central Tendency] [Q3 verbetering] [2008-10-28 19:05:04] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMP       [Central Tendency] [Q3 verbetering (2)] [2008-10-28 19:06:46] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-    D    [Univariate Explorative Data Analysis] [Q2 Investigating ...] [2008-10-23 13:14:55] [74be16979710d4c4e7c6647856088456]
F    D    [Univariate Explorative Data Analysis] [Q3: Prove that gr...] [2008-10-23 13:30:10] [1e1d8320a8a1170c475bf6e4ce119de6]
-           [Univariate Explorative Data Analysis] [Q3: Prove that gr...] [2008-10-27 19:05:42] [988ab43f527fc78aae41c84649095267]
-   P       [Univariate Explorative Data Analysis] [Seizoenailteit] [2008-11-03 21:03:22] [85841a4a203c2f9589565c024425a91b]
- RMPD    [Maximum-likelihood Fitting - Lognormal Distribution] [QQ Log] [2008-10-23 14:53:17] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMPD    [Maximum-likelihood Fitting - Weibull Distribution] [QQ Weibull] [2008-10-23 14:54:45] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RM        [Maximum-likelihood Fitting - Gamma Distribution] [QQ Gamma] [2008-10-23 14:57:54] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMPD    [Harrell-Davis Quantiles] [Q5 - distributions] [2008-10-23 16:14:37] [e5d91604aae608e98a8ea24759233f66]
F    D    [Univariate Explorative Data Analysis] [Univariate explor...] [2008-10-23 18:32:20] [45822fdf1b746b5c6b4ce78e65a55a58]
-           [Univariate Explorative Data Analysis] [Investigation val...] [2008-10-27 21:42:21] [74be16979710d4c4e7c6647856088456]
F    D    [Univariate Explorative Data Analysis] [Vraag 3] [2008-10-24 08:27:19] [87cabf13a90315c7085b765dcebb7412]
F           [Univariate Explorative Data Analysis] [Q3] [2008-10-27 21:38:01] [d2d412c7f4d35ffbf5ee5ee89db327d4]
F    D    [Univariate Explorative Data Analysis] [Investigating dis...] [2008-10-24 08:58:00] [58bf45a666dc5198906262e8815a9722]
-    D    [Univariate Explorative Data Analysis] [Q3 Clothing Produ...] [2008-10-24 09:47:35] [f9b9e85820b2a54b20380c3265aca831]
F    D    [Univariate Explorative Data Analysis] [Prove that growth...] [2008-10-24 13:49:02] [1376d48f59a7212e8dd85a587491a69b]
-    D    [Univariate Explorative Data Analysis] [Q3 Univariate Exp...] [2008-10-24 14:04:29] [7d3039e6253bb5fb3b26df1537d500b4]
F    D    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-24 14:43:18] [063e4b67ad7d3a8a83eccec794cd5aa7]
F           [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-24 15:00:51] [063e4b67ad7d3a8a83eccec794cd5aa7]
F    D    [Univariate Explorative Data Analysis] [q3 inv distr] [2008-10-24 16:14:09] [8545382734d98368249ce527c6558129]
F   PD    [Univariate Explorative Data Analysis] [herberekening vra...] [2008-10-24 15:58:05] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-24 17:04:13] [a57f5cc542637534b8bb5bcb4d37eab1]
F    D    [Univariate Explorative Data Analysis] [Investigating dis...] [2008-10-25 11:24:17] [2d4aec5ed1856c4828162be37be304d9]
F    D      [Univariate Explorative Data Analysis] [Investigating dis...] [2008-10-27 18:03:14] [2d4aec5ed1856c4828162be37be304d9]
F    D    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-25 12:18:54] [6743688719638b0cb1c0a6e0bf433315]
F    D    [Univariate Explorative Data Analysis] [Q3] [2008-10-25 12:44:46] [b187fac1a1b0cb3920f54366df47fea3]
-    D    [Univariate Explorative Data Analysis] [Q3 U EDA] [2008-10-25 16:56:45] [547636b63517c1c2916a747d66b36ebf]
F    D    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-25 20:12:43] [b82ef11dce0545f3fd4676ec3ebed828]
-    D    [Univariate Explorative Data Analysis] [Investigating dis...] [2008-10-25 20:28:11] [d32f94eec6fe2d8c421bd223368a5ced]
-           [Univariate Explorative Data Analysis] [] [2008-11-03 13:50:00] [888addc516c3b812dd7be4bd54caa358]
-           [Univariate Explorative Data Analysis] [] [2008-11-03 13:52:34] [888addc516c3b812dd7be4bd54caa358]
-           [Univariate Explorative Data Analysis] [] [2008-11-03 14:01:41] [888addc516c3b812dd7be4bd54caa358]
-           [Univariate Explorative Data Analysis] [] [2008-11-03 14:59:06] [888addc516c3b812dd7be4bd54caa358]

[Truncated]
Feedback Forum
2008-10-31 16:25:56 [Bob Leysen] [reply] 
In de run sequence plot zien we duidelijk een dalende trend.
De LT-evolutie van totale productie komen niet overeen met kledingproductie. De kledingproductie wijkt af van economische groei in totale industrie.
Met onderstaande link kan je ook de grafiek van de autocorrelatie bekijken. http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/30/t12253728791frueq4z3rg1624.htm
Dit is beter voor de seasoniliteit af te lezen. De pieken boven de 95% betrouwbaarheidsinterval wijzen op seasonaliteit.
2008-11-02 17:29:26 [Bernard Femont] [reply] 
Indien de kledingproductie en de totale productie in gelijke mate evolueren, dan zou de grafiek geen dalend karakter hebben, maar horizontaal zijn (de deling kledingproductie/totale productie geeft dan een steeds wederkerende waarde

Doordat deze grafiek een dalend karakter heeft, kunnen we vaststellen dat de groei van de totale productie sterker is dan deze van de kledingproductie wat goed geinterpreteerd werd door de student!


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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.989130435
0.919087137
0.925417076
0.925612053
1.066666667
0.851108765
1.030693069
0.989031079
0.913000978
0.792723264
0.978170478
0.987513007
0.909433962
0.883608147
0.82745098
0.8252149
1.023255814
0.815418024
1.026192703
0.914742451
0.807276303
0.739130435
0.98973306
0.972164948
0.853889943
0.856864654
0.775739042
0.789473684
0.931350114
0.73971079
0.885245902
0.842435094
0.818458418
0.72755418
0.923238696
0.922680412
0.883762201
0.818270165
0.771047228
0.825852783
0.924485126
0.755165289
0.874671341
0.815956482
0.799807507
0.712598425
0.832980973
0.910323253
0.869149952
0.779182879
0.750254842
0.75856014
0.920889988
0.743991641
0.816254417
0.769593957
0.784007353
0.683284457
0.850505051
0.900695134
0.868398268

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1289&T=0

[TABLE]
[ROW][C]Summary of compuational 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]2 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=1289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1289&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Descriptive Statistics
# observations61
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.683284457 \tabularnewline
Q1 & 0.792723264 \tabularnewline
median & 0.853889943 \tabularnewline
mean & 0.86210009042623 \tabularnewline
Q3 & 0.922680412 \tabularnewline
maximum & 1.066666667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1289&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.683284457[/C][/ROW]
[ROW][C]Q1[/C][C]0.792723264[/C][/ROW]
[ROW][C]median[/C][C]0.853889943[/C][/ROW]
[ROW][C]mean[/C][C]0.86210009042623[/C][/ROW]
[ROW][C]Q3[/C][C]0.922680412[/C][/ROW]
[ROW][C]maximum[/C][C]1.066666667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1289&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:

Descriptive Statistics
# observations61
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
library(lattice)
bitmap(file='pic1.png')
plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(x)
grid()
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~x,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
} else {
densityplot(~x,col='black',main='Density Plot')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(x)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Lag plot, lowess, and regression line'))
lines(lowess(z))
abline(lm(z))
dev.off()
bitmap(file='pic5.png')
acf(x,lag.max=par2,main='Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(x,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(x,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')