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Solution of Assignment_1 or Regression Analysis Course, Assignments of Statistics

This solution is based on assignment 1 of the regression analysis course. Used R to solve the questions.

Typology: Assignments

2021/2022

Uploaded on 03/22/2023

romyull-islam
romyull-islam 🇺🇸

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Download Solution of Assignment_1 or Regression Analysis Course and more Assignments Statistics in PDF only on Docsity! Aedes), AdeseM/ D.. L. Z=- Hr-~eM o S-b: We Var (z) = Vor (XB but Vee (es) = tb yaw &) v ob / ee a = a Vex (x,-) Yeeal\ Hat Ver (iE8) © Vaw CK) et Nee) vibes x aN (un, oa) = J-g" 2 a.| Rearersion med Pru = -lIS Age + 49-02 uw Ss SD ef E-&er = 1 a. Aye 2 4 - Bree = - IRIE (4-0)+ 194-63 = [4d ae ~Henee the predicted pete b. Ages 6° Pree -iis(cd + (4-93 = 75A4 GT, i he Prediction makes ne Sense a> 10 bells us. rant 4 boars old Wd Car: spl ott -524- 9 Hest 3 R nagedve md HonpsieSle We can ned be ate pou Of en “eem ts be vg ative. _ ] vi The cdl Gm only be used ts predict pric og used cos | bebusen Ayer cel UC yemrss bdyrom doer nok fall nile 4 ‘hc Went | | Zegryssi¥n » Boo £3 New regresyim moat? Price = 7 5.523 Oo Li New vy value tO. BACTSIS we Fa predirtingy Kee gees a ued Cars, | ws cory Ne origins (fF Is peter - Rentnfrally Spesknney , we Kaew +a LObbty dapreciates Witt fime whith the origin | vegves som bow has chum Ys - beste ak dhe need vequeryr line, He is fellny F- ys Haat _as Ha number tf —jeors 64 don used Gv muse! iE pte frie ncvecges as well: Thnk, ale svxel- (cee mage belad L }__ id. My Reortgut shows that apter adding Hae fre rfc oaee fon | fhe Stemdard errer_moreneat firm I6-0b (or Bdeqeee of Gremdon) +o S2-4 (om F degeas op feorlen) - ; Whe bor gniead “LE detimme pr is O'8209 for Dove nen Aate: Like | nsbed tn awe Cowse mefendl ,7O66 the Coxgeruen t of determing} ig _nst Necessary - a Sood Way te asert 4 moele!. We con have « Woh y* yeb she melt will not be ssel- Our O-2204 tells us Met we shonlel k shu ta peeked | pha proecp Useot corr from ore meded rh 22%, Level FE ef actutay, bub it net 9. Th shavs that there Gna _Comdlibens for ev sell om our weet ig not xsRtent. to wthen. $F | Show Hit He slope congrient je mdecck by = x: 5 Sy Posse. = . Reestt 3 ch Pht 2 (4% 73x) = b> (x i%) _ ’ UT cer ° ae yo 1 NUy vy - ney S ik Lb, Ss (xi -».%) a baer “Sx,) _ LG - bx : _ = SSE = > [de mh —bs) . z (uix: ~¥x,) = 121 — 7% = _ a ZZ x = xx) Ne mmmite SSE 4, get tha slspe b, vet Ab, lout ; S(52-x5) = s(xI- 2x) = 6 _ de | 4 $ (y-b%-b = — : . OEE soc) BETIS - x a> tt _ = “22 (uinb “b) Xi > Ss zt 2 OE ZR 7 ue S (a — bux - bm? Fog 1! a GO. -¥) OH 9 2 be = 9 - b,* yb, x: y+ 4.5): W; = 8 —bi x - 4x: +4) ze eT nD ant + bas ee 7 : be BRON han ; 13 54 ae “2 Loe t bee . Ea) Koy — - be per ass Soy -T) qd biGiw ae Se tr S = cs S GIT) / n f=, fy — Ae - W a 7. be tb So, Oi) t wr Se Sy n-t we _ ‘ sates bs ty>z 4% enw eS a n-b WS x a SI n = J : __ bt ys 1 Dba hy \ ri a b= Ss “fy — L, =v Sy _— - Sy —— OO — erence Recall pct yebi thn 2 Y-ctw. Girvan ory b= (le pe =m But bev Sy = Slope / qractient Df Ba reqyersitn bing. 7 Su The vero OL tee Stomel caved elewrt vr 1p He yesprmse vanabl te the standard avaher Ry Pu ery lecnatis Vem ale tells us sone In founsb abeut Ve slepe Te vabo iS Gye ste 1 Hem 4 When Sy 7 Sn) in Hous Cége Ye slope mill he Greater Han to. Siem leney tt wy < & the slope Wilt be less#o.th.. 4 A ne _ Trnconclursin the yatrs tells os FE thre slope will Le qrestey =r less fan 1. J wse(é) = LYE] + Ve(é) MSE [éJ = E((e- ay -e(e 16 =) rTre ‘ C01 L561 = tfe4 + Epes epee} Pe se (4) —{ecé)]" + fete] Into Pe equchn = &(6*J— fe(8)* > fece))'+ efe'] - e280] MSE Vo (E)= §(8*)= fecB)J (6) = Vad) + fecé)| * + 2(#)- e(2 be) = Vor(6) } peccsy- = 2&(ée) + Ee(é) = Vee (é)+ feces ay —&£(6) . eefS) + £/0’) = Veon( 6) +E(®)] €(6)-e | efe()_6] ~ Ver (8) -+ fe (6)- e|( e@-e) Me (&) = Var (©) + [E(6)- -e] Bias(®)< E(6)-o ese (Bb) = GLE) t+ hias(E) — see) = Vexe yr (e@)}$ — ———_=_— 2 7 = i eft S(a-3) ] = 1b E2Oits - 29% a oe yi n-\ con XK 7 7 — = \- ~t es urs - 2493 %) n-i Ve vt wt Zz ay 3 = Ye ny* ul | } v oma _ _ oe | els vl reg -29-n9 | n-! , e2 Poll | i _ 2 1 _efS 4 tng’ any” - | n—- vet ‘. aE Ta O- -) (> % -99 n-) Lis - law = Mi my _ \ , c _ —2 2 Nn . oye _ | Zz ee t 03] ~ n-t ex: } 7 at |e a (egy) - €(9*) n~ll : accent
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