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Description of Statistical Computation

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 computationTue, 13 Oct 2015 15:38:15 +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/2015/Oct/13/t1444747104lyfn34kkvbvyn6g.htm/, Retrieved Mon, 13 May 2024 22:45:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=282360, Retrieved Mon, 13 May 2024 22:45:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

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] [k] [2015-10-13 14:38:15] [fdcee98729d8ae773847ef0dab21bb59] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.6294599697	0.3329896003	0.1126142576	0.4954919697	0.6418077068	0.9978978923	0.209642809	0.07457335308	0.07327471732	0.08264758516	0.7619526171	0.06622483669
0.7154505943	0.6104732527	0.1631689963	0.5507563242	0.9106512767	0.9133627128	0.05440721438	0.2609483915	0.4740156972	0.4571024304	0.007384546584	0.5131788862
0.0837773188	0.3525227508	0.9309104536	0.9414033823	0.2763379138	0.6644242868	0.2968549578	0.14009861	0.8282783466	0.9079860094	0.005327468487	0.8037242116
0.3591993845	0.05702657865	0.3386820788	0.5879526995	0.4472931392	0.9793105827	0.9900971059	0.7118635368	0.4138035381	0.4611616138	0.5948603074	0.2704918265
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0.8580653193	0.8355823318	0.6378025201	0.3849058158	0.2569891476	0.02526387531	0.5081474537	0.06084418563	0.1101164952	0.4923177875	0.1470089006	0.8662509113
0.8270620006	0.6111764178	0.9077587095	0.4515752623	0.9702218461	0.1045327048	0.7405533808	0.5527508244	0.6190042088	0.1552381696	0.3382557869	0.3098068664
0.4064279269	0.3790533515	0.4535802958	0.8964814012	0.3754585295	0.3976607031	0.9161788223	0.4917503024	0.04170883805	0.373421033	0.6957672001	0.9493822366
0.6946393522	0.1456740946	0.08102499555	0.003074084667	0.02115091151	0.5429551143	0.6738836974	0.48241734	0.593470627	0.03631848422	0.4349522098	0.8088909175
0.6274893203	0.146031058	0.4582100695	0.9912712945	0.688216623	0.9172167434	0.5017330453	0.4462961038	0.695778184	0.339605445	0.5560970445	0.2331126549
0.6683864468	0.8023591761	0.8932406292	0.7089883705	0.1279750296	0.5470183272	0.1059478993	0.188955082	0.9896939145	0.6099318705	0.6217473494	0.9235045332
0.05822114046	0.9301051406	0.0549042757	0.5961482345	0.9618536838	0.1392195906	0.5463179134	0.5865990997	0.4695989587	0.04764865248	0.9335166443	0.4455290277
0.6569952192	0.9936147558	0.1915777906	0.3833001989	0.3131478144	0.03220255307	0.09068115871	0.08776497499	0.3144755334	0.406763497	0.427138502	0.8551730003
0.4299191234	0.8673179498	0.5021236356	0.8434205564	0.1678722093	0.1788802989	0.7459608504	0.2383219729	0.8268524085	0.5972039032	0.5157123043	0.2612780989
0.8699378801	0.180262224	0.1299373501	0.2406630251	0.1072534882	0.5508532402	0.1468803083	0.4194441211	0.9412971395	0.1290342804	0.7409751972	0.7779971465
0.1066557781	0.9126650609	0.7874394311	0.9137727528	0.9186677688	0.6001567138	0.9258609576	0.9384161851	0.03484633809	0.2215949567	0.4410660947	0.4281372197
0.1283867984	0.4727260463	0.273188306	0.694572881	0.6748375004	0.6308643799	0.8487409784	0.03108071312	0.2610231343	0.2726006478	0.7106298213	0.1333455115
0.4395657633	0.01026038303	0.1174235796	0.5933779555	0.1728579147	0.1173823001	0.880834537	0.2224289809	0.3370988511	0.2230568178	0.7152428355	0.9710385502
0.590013664	0.2207849787	0.284231962	0.3833834916	0.1451323528	0.1595885173	0.9464849994	0.8482836726	0.6410137162	0.1634221546	0.9270243212	0.3906718167
0.3455572167	0.3595094252	0.2696603895	0.3850268856	0.3935530396	0.3870436698	0.4626478153	0.3662167207	0.6198792389	0.304766113	0.07192976574	0.06339086683
0.8212617365	0.6192535881	0.06498461	0.8890096164	0.956271802	0.7153179107	0.7631718538	0.3777908988	0.8762424149	0.1857404968	0.521606317	0.489301729
0.6690433649	0.4296348454	0.3029734368	0.2631164391	0.5931628774	0.417050879	0.2853306564	0.04690899547	0.8813004913	0.7020045901	0.5238227652	0.4055422402
0.4006850348	0.606937474	0.4723722621	0.8631621134	0.27158806	0.9986798951	0.863787996	0.8305000461	0.06601174912	0.2293135328	0.04536894038	0.4260326465
0.135287884	0.624897501	0.3719617923	0.4123420444	0.948332284	0.3708441806	0.669564873	0.137966861	0.06155665806	0.7647997906	0.09995310152	0.2002278082
0.4869482663	0.5862063665	0.9804314705	0.5259582984	0.7765848421	0.7662908416	0.2427077866	0.7047651856	0.09986078725	0.6330484856	0.2510077919	0.7033900946
0.9539576019	0.75285734	0.6419388526	0.5399372486	0.9186003882	0.7936808477	0.6972411854	0.1031790573	0.04289898893	0.8943865755	0.5154480559	0.06484588754
0.03508089553	0.740528577	0.9096099528	0.7517518027	0.4151807119	0.9190119113	0.5256196602	0.9198035302	0.1862583372	0.1523776797	0.1493087013	0.6033848836
0.3814766598	0.6980174198	0.5503679248	0.6013045152	0.05237644591	0.5384461058	0.4972781617	0.7044400058	0.8779446112	0.9858330102	0.7698194403	0.4704067599
0.5945797388	0.9773105823	0.09436035356	0.2070252576	0.8738160426	0.647150895	0.932011517	0.8390556461	0.1076755654	0.7277206635	0.9608605713	0.5016141606
0.8007756136	0.9531950582	0.9108880317	0.02888078468	0.9138263294	0.9183314376	0.1337973306	0.9881532332	0.5549114868	0.7791747436	0.9198737961	0.5469973544
0.8729530318	0.7733855694	0.1101215358	0.2551897329	0.8720176047	0.7849533188	0.9943088313	0.7733430539	0.1356317188	0.08137666092	0.8341862062	0.6865506662
0.1270292707	0.9109636484	0.6060238121	0.8040818034	0.8142635887	0.8637246775	0.7177477779	0.7651041413	0.8583733992	0.771401321	0.5233377293	0.3456058551
0.4983004975	0.4504947137	0.4307806684	0.5931347418	0.5680143735	0.7767270517	0.2797593414	0.8036670067	0.7893067282	0.4201907319	0.4513857263	0.3988637363
0.5979771674	0.0675092539	0.8646732909	0.9621687061	0.2816385333	0.1106549755	0.6130744981	0.0486456749	0.1341286162	0.5916383637	0.4992925833	0.8961498675
0.6645225766	0.6581047863	0.1377100473	0.834372329	0.637998278	0.9069438279	0.6111581634	0.01349202956	0.8713145375	0.7713378177	0.8923857738	0.05561568172
0.2574201347	0.5412453309	0.3704672789	0.3698805953	0.4517191443	0.6981369045	0.8585235703	0.1660406955	0.01677625402	0.9918692702	0.4015117007	0.6515521337
0.5927529099	0.09090597624	0.05147237101	0.5036193618	0.8376239087	0.6966617193	0.5325069324	0.4703581629	0.4642307372	0.7285681178	0.3788884211	0.874177482
0.6904870265	0.5585295353	0.6970939466	0.8656773419	0.8145577943	0.3017571117	0.1761786723	0.5078049782	0.4285936984	0.8555401284	0.35079438	0.1577070654
0.9926076878	0.7183336488	0.4072882674	0.157661353	0.1043404796	0.6186119757	0.01570073175	0.5466655018	0.8214684271	0.6362576233	0.7691135726	0.3607073876
0.8192652297	0.8088262833	0.8166825799	0.102435612	0.9998372489	0.1808474077	0.1878219951	0.1298943329	0.4083092351	0.8763919908	0.1223901884	0.03918251024
0.9568456517	0.05345782953	0.4453596802	0.5973419429	0.5091504443	0.5332943085	0.6543367056	0.419474908	0.3360958207	0.4886076345	0.9244285709	0.3780364348
0.817388533	0.8216590905	0.67734029	0.6824424405	0.5346898013	0.7665881636	0.7102138275	0.6735797616	0.5783632825	0.809863421	0.1346073115	0.6404996687
0.9730324449	0.2385839188	0.5371431278	0.3855214822	0.61638765	0.4984242196	0.8407378678	0.8391685514	0.02118976143	0.07133688511	0.3189587779	0.7578042061
0.4521764555	0.7676958874	0.09593500957	0.4245299165	0.7575834542	0.168385381	0.250384281	0.3178543078	0.3092522958	0.4494082153	0.334698727	0.9128358844
0.9858032672	0.9749088811	0.7186661676	0.1358486553	0.06010964641	0.8540760428	0.6722861746	0.5068140477	0.1853183284	0.1232101402	0.5132727865	0.6716890711
0.4129184868	0.336311569	0.4622190757	0.8531948161	0.3218684702	0.1258656994	0.0720308377	0.7292154575	0.8895488794	0.7300708571	0.2281200114	0.3859931262
0.6933171232	0.5735760787	0.7519813846	0.2871889079	0.3956974126	0.7358655745	0.5831582179	0.6500759761	0.2367468282	0.5447469853	0.363236177	0.2265762205
0.4338971092	0.591971429	0.0003868728821	0.2495465014	0.9725787039	0.1838327141	0.4541158675	0.2236667427	0.2601917797	0.6116644088	0.54725241	0.3154765813
0.511497057	0.6554729862	0.08585098968	0.3285532517	0.5352562022	0.4185159975	0.9475577181	0.6375185488	0.7999604919	0.931454487	0.08512746612	0.998507509
0.2707433426	0.9617788667	0.5841600547	0.8539277043	0.530080569	0.1175284144	0.01275735908	0.6057823962	0.1216399586	0.6438940596	0.3056850293	0.3445267352
0.889649522	0.277115172	0.3367564602	0.689371382	0.3254116135	0.1421509836	0.1505381505	0.7211430774	0.578098003	0.9589275571	0.5481099314	0.4702568907
0.8387185867	0.756531708	0.3514947492	0.06005095526	0.264164477	0.8855436434	0.207507004	0.3996785396	0.4724838631	0.3657701486	0.234149927	0.2709488744
0.9110570329	0.5099605963	0.1613264041	0.7599527487	0.07609430701	0.3236583876	0.8725095883	0.2470041031	0.6448892714	0.3971607948	0.4151532493	0.5873749051
0.07151647985	0.8776303138	0.6150037366	0.6904951183	0.09217143048	0.6377212041	0.4031091966	0.4367351621	0.8881082145	0.9416547378	0.844203606	0.7585837968
0.3621376862	0.7504977542	0.6412766846	0.7569793739	0.0989073072	0.3054685598	0.5835232968	0.9237478585	0.09969142311	0.781415349	0.003498548751	0.8975462556
0.3091784353	0.6121817351	0.8141879527	0.6934055155	0.2847492708	0.5553953565	0.1078347414	0.01491209665	0.09799959187	0.686284877	0.615748979	0.08326303215
0.7037652905	0.2884514222	0.5519565774	0.3988741548	0.5636695117	0.04409111402	0.4934280046	0.9889168758	0.2692166674	0.01698491132	0.9857606463	0.988104171
0.273716881	0.6686431391	0.5055706427	0.8502413496	0.6128320764	0.5513115597	0.2594828958	0.0945031242	0.6702930359	0.3811169999	0.05449149671	0.253093216
0.6283439201	0.9104500656	0.1355945855	0.6058884508	0.2317292471	0.3907534861	0.4539913811	0.3628644468	0.8895457792	0.4452042698	0.3027612805	0.1865451385
0.9410395431	0.8553488497	0.6368282265	0.334414319	0.119436251	0.1065700648	0.6801459355	0.245171703	0.8621509088	0.5343356907	0.6154228273	0.09291231336
0.1362305824	0.5664981668	0.2503376471	0.6897525979	0.8746416083	0.8664855444	0.5590807259	0.1301225929	0.9520210293	0.1480442277	0.9091869858	0.7388879568
0.8677689859	0.05426411286	0.6010114623	0.2106620199	0.9498675188	0.7719371887	0.07082935702	0.3091123128	0.9445682909	0.9868708348	0.7384263851	0.1327622411
0.3150998509	0.3765976276	0.01617769785	0.7477331419	0.4368033514	0.08399356391	0.4389963632	0.9380676448	0.14661225	0.5186368172	0.223165535	0.9307207815
0.7815506949	0.3923099537	0.8169506785	0.2149999788	0.9239321518	0.1108681195	0.1670218658	0.9951809176	0.5601980812	0.5167666689	0.492098087	0.3902213961
0.2558440703	0.5048617819	0.328858971	0.2259406487	0.2506389361	0.2186675963	0.4950517537	0.1527266655	0.08634978462	0.3750744708	0.4008544933	0.8657798362
0.4934438505	0.7626024219	0.8319388176	0.4050961276	0.7837463387	0.1115847808	0.9263090031	0.8688384705	0.9227902542	0.3442469326	0.5718762113	0.3864404984
0.7886029501	0.6784658671	0.8628603034	0.8667317127	0.8629317491	0.1810658813	0.5704937807	0.8615689144	0.7464180173	0.144826656	0.8071357165	0.8669036906
0.4409882939	0.09795015214	0.1927860839	0.5209112404	0.3007375521	0.3455526253	0.8691236733	0.452751209	0.9168382536	0.689819193	0.6485739524	0.9857261137
0.9725164276	0.3787777048	0.4345455855	0.5050489089	0.2808939186	0.3932200113	0.80385726	0.06312584609	0.8015034325	0.8971181789	0.303509732	0.714206714
0.4205414821	0.0489539768	0.5813399763	0.1454494537	0.6754314419	0.3997002369	0.9437279691	0.4028913454	0.4060269392	0.7877627784	0.3134088972	0.8985151517

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282360&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282360&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net


Figures (Output of Computation)

Input Parameters & R Code

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')
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')