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## 10th week of notes

by: Michelle Schmutz

11

0

4

# 10th week of notes 3341

Michelle Schmutz
UTD
GPA 3.3

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monday april 4th and wednesday april 6th. this doesn't include the half-answered exam solutions. those will be on the study guide (fully answered)
COURSE
Probability Theory and Statistics
PROF.
Dr. Mohammed Saquib
TYPE
Class Notes
PAGES
4
WORDS
CONCEPTS
Statistics, probability theory and statistics, Math
KARMA
25 ?

## Popular in General Engineering

This 4 page Class Notes was uploaded by Michelle Schmutz on Friday April 8, 2016. The Class Notes belongs to 3341 at University of Texas at Dallas taught by Dr. Mohammed Saquib in Winter 2016. Since its upload, it has received 11 views. For similar materials see Probability Theory and Statistics in General Engineering at University of Texas at Dallas.

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Date Created: 04/08/16
Weekly #H Notes Monday , April 4 it. ^ ) As) ( 3,5 e×)Giren: *&& was- Pcmaxlxykb dawarea =L ,y)={ okjfjEF interest y<w of cos't-law Find: IT Square -x<w , ?, where lPD㱺fw(w)= lottfxyk WtmeXG.yxqhmetobe1essthanwC0i07hdH9ow-maxk.y1CPDFtFwlw7PCwtwtPlmaXCx.pcw.l3YcwFwY-PCxew.yt4.c3id-fffx.yCX.ydXdyAw2BLwXEw_yIxSwYlsdxdy-ety.ff.wdxdy-Ytsi0ewe3rectangtf-yshapesahdifferew@CPDF3souaresowIndigydt.kE.neas-7FwlwtaSfx.ylx.ydxdytBfx.ytx.ydxdT0XfwiYtWCdifferentratioD-Ylsfdxdy3Lwcs-3Yg.ws-qo5fowtYot3fww.dtowwwXfoiEpYoEir3lowssYsj3LwESElHfYoowfwCwdweDGicniW-f3ow.Edwtf5w.YsdwXir.inarei.i.dindependeutly.idutiallydistributedCSameCDFlPDTtfx.CxD-fx.txD-fxtxDfxkD-gehxixzoWneedtnsubscriptOoO.w fxycx.gl#fx(x)fty)=fxWfx1y)o;o.w . indlp # ;y20 fy(y)={XehY . =fx* doesn'tates onlywuakoutth arguments FxiCxD-pCxiLxDFxCx-PCxcXeCDF-7FxtxD-PCxexijPKH-tpCxtlDFxsxzi.sxntx.Xa.i.xnji@ttFxIcCcDF-PCXfXy.i.Xn Ex) IPCX .kz#xPCXztXz)*...*P(XncXn)=Fxlx.)...Fxn(Xn) Etfx.x .. Fxtxn PCXN --Max(× , ...XnD±n P(w>w exxziven : &&& Fwlwtpcwc 4=1 - ) OK =hP( mink , ) , ..,XnȾiid , ...,×n)>w × =L - QW=min{ ,, ...n3 PK , >w,Xz>w ,... ,×n>w ) - Find : El PC x, >w)* . .*P(xn>w ) - Fw(w)&fw( w ) =L ( tFxCwD* .. .*(tF×n( WD Dense #lttFxfw).*.*(tF×fwD subscript onx 's - lnowthesame ' Fw4= .at#nthiTf9dwfww=th(tFx(wj)ht*tfxlw)- 6 Wednesday , April ex1y-tzxtS00TnmiIfy-axtb.thenPxiyt@IaaFo_p.iy-2dxuKY.gIxjDglg.sscor-dxdy-2xtt22x2y-Zjxz-ZJjwstusethisequationdiredlyIfY-axtb.aKx.yHaJxE-o-p-oindepnsooaoCov-o1-indepFmpliestfx.yCx.y-gkDh44yfxtD-g9oofx.yCXiDdy-gkfoohcx.ydgVHRewritirytheBivariakGaussia.nPDFfx.yCx.y ' )=y¥,÷¥ -004<+00 wh.IE#i.iTi*fxCx.p=*etT* joint,im{×yTvYjjk¥ > MA.fm niche .io#Cxa , gains 5.626 e) Given the X,..,Xnareiid㱺f× ;f×n(X .xn) Efx ,(×?fq(D ...fxnK) Etfxfx,)fxfk)...fxCXn Find :P(Xn=:\$×(x ,,. ,XP(Xn=minlKD±Yn , p(Xn=max(x , .,xnD ¥ .gs#9ofj....IonfoonfxtxDfxkd...fx(Xn-Dfx(xn)dx,dxz...dxntdxn xn.IM#ofxCxddxz)(foofxlx.)dx.)*fxtxn)dxnFxlH=gxoofx(u)du=f9oFxCxn)...FxKnHxKnldxn=f;fFxcxDmfxCxn)dx.FhYTntt X ddE¥n1=fx(Xn)㱺dy=fxCxn)dx . - too =§ymdy=Info=# xnȾoo xn .am#,a..s=Etotos=*aj ¥L

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