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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_fitdistrnorm.wasp
Title produced by softwareML Fitting and QQ Plot- Normal Distribution
Date of computationFri, 02 Dec 2016 12:39:44 +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/Dec/02/t14806791559lh9c3uikcikkjv.htm/, Retrieved Fri, 01 Nov 2024 03:41:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=297565, Retrieved Fri, 01 Nov 2024 03:41:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [ML Fitting and QQ Plot- Normal Distribution] [Histogram] [2016-12-02 11:39:44] [863feeaf19a0ddfce7bd9c25059c4d8a] [Current]
- RMP     [Stem-and-leaf Plot] [Stem & Leaf STATPAP] [2016-12-11 13:07:14] [937b9e6718912fc8986df66e31b6c342]
- RMP     [Skewness-Kurtosis Plot] [SKEW STATPAP] [2016-12-11 13:38:51] [937b9e6718912fc8986df66e31b6c342]
- RMP     [Histogram] [HISTO&FREQ STATPAP] [2016-12-11 13:44:30] [937b9e6718912fc8986df66e31b6c342]
- RMP       [Mean Plot] [mean plot] [2016-12-17 16:47:20] [937b9e6718912fc8986df66e31b6c342]
- RMP       [ARIMA Forecasting] [arimafore] [2016-12-17 17:02:14] [937b9e6718912fc8986df66e31b6c342]
- RMP       [Structural Time Series Models] [structural time s...] [2016-12-17 17:08:21] [937b9e6718912fc8986df66e31b6c342]
- RMP       [Exponential Smoothing] [exp smo pap] [2016-12-17 17:15:48] [937b9e6718912fc8986df66e31b6c342]
- RMP       [Variance Reduction Matrix] [] [2016-12-17 17:20:54] [937b9e6718912fc8986df66e31b6c342]
- RMP       [(Partial) Autocorrelation Function] [] [2016-12-17 17:32:40] [937b9e6718912fc8986df66e31b6c342]
- RMP     [Bootstrap Plot - Central Tendency] [BOOT CENTR-TEND S...] [2016-12-11 13:53:02] [937b9e6718912fc8986df66e31b6c342]
- RMP     [Tukey lambda PPCC Plot] [TUKEY STATPAP] [2016-12-11 14:10:16] [937b9e6718912fc8986df66e31b6c342]
- RM D      [Notched Boxplots] [NOT BOX STATPAP] [2016-12-11 14:15:45] [937b9e6718912fc8986df66e31b6c342]
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Dataseries X:
4790.92
4795.33
4822.62
4797.52
4822.17
4843.08
4850.79
4827.02
4796.65
4854.96
4870.81
4891.06
4881.38
4921.43
4956.21
4962.81
4949.38
4977.99
4992.73
5009.02
4990.98
5014.96
5022.23
5028.83
4894.36
4918.13
4936.4
4899.87
4862.89
4882.69
4895.46
4883.8
4855.4
4874.33
4880.94
4861.79
4851.44
4840.22
4842.42
4827.02
4749.77
4866.63
4734.37
4726.44
4753.51
4867.29
4793.35
4822.4
4865.09
4987.67
4900.96
4904.71
4889.52
5015.63
4938.81
4924.73
4871.48
4998.24
4891.06
4876.54
4824.15




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=297565&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=297565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297565&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center







ParameterEstimated ValueStandard Deviation
mean4883.285081967219.39105908483741
standard deviation73.34651617377166.64048156141207

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 4883.28508196721 & 9.39105908483741 \tabularnewline
standard deviation & 73.3465161737716 & 6.64048156141207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=297565&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]4883.28508196721[/C][C]9.39105908483741[/C][/ROW]
[ROW][C]standard deviation[/C][C]73.3465161737716[/C][C]6.64048156141207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=297565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=297565&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ParameterEstimated ValueStandard Deviation
mean4883.285081967219.39105908483741
standard deviation73.34651617377166.64048156141207



Parameters (Session):
par1 = 8 ; par2 = 0 ;
Parameters (R input):
par1 = 8 ; par2 = 0 ;
R code (references can be found in the software module):
library(MASS)
library(car)
par1 <- as.numeric(par1)
if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
r <- fitdistr(x,'normal')
print(r)
bitmap(file='test1.png')
myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F)
curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)
dev.off()
bitmap(file='test3.png')
qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$estimate[1])
a<-table.element(a,r$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'standard deviation',header=TRUE)
a<-table.element(a,r$estimate[2])
a<-table.element(a,r$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')