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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 computationSat, 20 Oct 2018 13:06:21 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2018/Oct/20/t15400336057irjon7uytmamqt.htm/, Retrieved Thu, 02 May 2024 10:16:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=315587, Retrieved Thu, 02 May 2024 10:16:21 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
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] [] [2018-10-20 11:06:21] [a6035a474e73fd5aa12b17012adbf5e6] [Current]
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Dataseries X:
1.925116033
-0.4544064903
1.349617082
0.7156961088
-0.5202801944
-0.09299998795
2.145846658
-0.3142517814
0.714321046
-0.7367133801
1.654830279
1.005786577
1.418191397
-0.01916491944
-1.172455688
1.244012885
0.1860980131
-1.431410621
-0.6954454106
0.3214569595
1.65133546
1.188431038
-0.171263781
0.4520400283
-0.4218669669
-0.4750693595
-0.482631857
0.442013418
0.8134369214
1.014473555
-0.006396759655
-0.6512281936
0.09806746596
0.4337608957
1.377312427
1.499041876
-0.2627484776
-0.1523142443
1.135305076
0.8664456577
1.130529445
1.91658385
-0.2090766818
0.8084391305
-1.838962519
0.5628596758
-0.5069882345
0.1626255856
-1.555835031
-1.003012583
0.4442624723
1.702444171
1.435586624
-0.8971129081
2.188934487
-0.04776664867
2.398669405
0.1826752839
-0.240051333
-1.638330574
-1.768744656
-0.9392087767
0.6853572076
-0.1604201685
-0.8481816791
0.5474978013
-0.1458112406
0.6471318137
-0.7550035127
0.2617576163
0.2416676931
0.6503959725
-0.1335007272
-1.186516351
1.493809268
0.9322844048
0.9073898901
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0.3713888728
-0.2361354497
-1.082257551
0.4328706524
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1.089674138
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0.2992099834
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0.09975245006
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0.4717821211
1.549839093
0.8107775173
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2.418018055
0.174934549
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2.210166239
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1.284017366
0.3539083418
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1.723015013
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1.2785988
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1.547510754
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3.00628521
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0.6984656625
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0.1665565966
1.660112508
3.079821655
-1.971865631
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-0.01236114574
0.6633420394
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1.018169719
0.6481647151
-1.215935292
0.1228956441
-0.4189216546
0.1323489839
0.4249266162
-0.4098406385
1.010350025
-1.706071435
0.3116116268
-0.1223475962
-0.4842409616




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 time7 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315587&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]7 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=315587&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315587&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 time7 seconds
R ServerBig Analytics Cloud Computing Center







ParameterEstimated ValueStandard Deviation
mean0.1720180472369670.0839512060742811
standard deviation1.028188090866140.0593624671039134

\begin{tabular}{lllllllll}
\hline
Parameter & Estimated Value & Standard Deviation \tabularnewline
mean & 0.172018047236967 & 0.0839512060742811 \tabularnewline
standard deviation & 1.02818809086614 & 0.0593624671039134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=315587&T=1

[TABLE]
[ROW][C]Parameter[/C][C]Estimated Value[/C][C]Standard Deviation[/C][/ROW]
[ROW][C]mean[/C][C]0.172018047236967[/C][C]0.0839512060742811[/C][/ROW]
[ROW][C]standard deviation[/C][C]1.02818809086614[/C][C]0.0593624671039134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=315587&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=315587&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
mean0.1720180472369670.0839512060742811
standard deviation1.028188090866140.0593624671039134



Parameters (Session):
par1 = 8 ; par2 = 0 ;
Parameters (R input):
par1 = 8 ; par2 = 0 ;
R code (references can be found in the software module):
par2 <- '0'
par1 <- '8'
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')