x5 5 ee or 726. Non - Paramatie Alternavive en assempuiens | tron sformating Ee = Srandard deviation 2% deviation debinivion = icy “a4 (obser sorrion - mean) erm Sy ~ = Saenp Standard deviation Trevember _E (yi- #0 , %Y Fg (nor “epectd dve to © variebili¥y 5 hopefeily Wy clese) 2 Sernplin vanelyiey OF te estimate = USvatly enknown % ee So, Srordard ere ee espera, . Syme = SSRN variable of eres eats always numecica) oe" oF pararreree by pale ee Gy) = be B_mans slike re oats Drevember Normal disers dcenver = “My ay Prnormal popularion » eskmavion = poplatien Para ¥tec Soha eo Cea ae CONE - n CeT= 302” fer large enough > normality Bb formal tes = Shapiro - Wilks test) av on ela % r f te an AqD-covio > nox veavke in real wond at Y ay Hey) shane ni OF = yoho\ N= thy of paramestis ot) yin pweemal-(0,1) pv aise butionSTAT 952 Cond % e-bable = to the nghe wasically know es P has 10 0s RE nOvense 2 pe, > 2-30) € (0,02, #025) tebe 2. Ziv 90) 2 (oP Ce > 20) i the oxen WO aoe oo ee V0. Jo0 5 pha 3 EOS, 0-4 qo) of ees CP lug>v-20) £6210 port Be PG), 4-150) = Pap i-50) | E (0105 5 010) Cé\e ston, 4. PG ReaGay) 0d 00) CME are yes) lonvecen) Be Pee Sous)ipig-sas noc ol Pe, ore te BSG. <5 ) CPlas> 5 iso) © Plt, > 80) E (0.025, 0.05) G Nor on table ZS round down to Bs wares > Specific % Lt . +f. fur cramp! e® Je what isa” so that ° te L ny (ty > 4) = 0-005 + Fuvnd vsing ; 5 2-250 x» babe a valet fi +f , 0:00 y g. who is “a” so thar a cg ca ee oe ao ppli AT A cece Crue & wea” _ Poko £. i : 2, Yom=Normel andfr we Nowe alarge Sompe sie (n>3e) Aral iwervAs IM class one — two- Sided) 3 (ide) |007%/9 SHS vevee + mere are 0 vnkesverd cog er a ol = 49 /e confidene \nberval oo 2, 9a pecanreid0)=1-gt OF, feet wt Colas” 2) Des Gas Luppec bound I Vals, oFter Seannpling | 7 RG) avs geies xe Sampling BNR: We Will never know jf our calcvlared jntervel actually contains +e Paci ter - bdt i Tahio ie “29904 vk howe 7 upper lotic bovnd Go Jens)ok | ae cite & Tie je 2 3‘ to pore (as wif necenatiey 18 ie ‘ 2 singe Nayonmrecn) “4 ety Ae OO iin daar oie HCO ANS. — ime question’ eSAVmat= Sample MON i Ot _ Sy 2 sample atond ord Jeviction it { We OF parenwters in Ere mode) | ote A= \ «Act obser uation ~ for re wean x5 pone ~_esimat® a = SOQ a ay 2) SEC Estimate) * SEED) = Sim = centive pea Se as rib. 12 57S = 090 7h Gj ee )ioche* pee o sort = O- ome: QC G7s3 <4, |. £788) = 0:90) is _ fom 2 The CL. for +4 (aged 0 this aes eee essen Se (errs He 23 5.247 © 9). 753 40-0769 gcioty POISE a CHM, 5-23) mel ——éenterare—anre ae : one . ag We estimate wish 90% Conbidene rhe tree mean orhel conven Cas c percentage) Agia berwer-en Wack | and S.9ah. 3 a ee ate aT eae Faterpet rhe a d ‘ 1 const sok Celis Gok noe CSS Pain Gb = 2-6 an Bestia 2 ns oe ? > hort t mk = widte nee “a : = 5. 07 * (a.pe2n00764) > 5.091 % 0.2000 fe , ContgiittreHeutaratu re aie reeves Coe, 4) Pos PO ani Note 2 This d0es Not Mean Our Estmare is Ves Accurate 2) Svppow a observed Y°Si 017 and Sy = a sampe of N:QS. Condiser a 40% cL: oa Net a 2 = SN Qa O.0S 256 yoros — bee GH both lower SECI)= Wa = 0-076 Jags = 0-0 1894 4 $047 OC EY x OrOFISSAR w@ 5,097 % 0-052514 = (8-04) 5.15) Larote n (aly Clee she Same) 4 Narrower interval = More AcCorede Sti Mare What 19 a4 100% C1? : AW x=0 2 = 7 . es = t ° : yee He Fegtaowet Esti = fev as eles) BGs + 2 (30,36) 0F some exonpies > (0, ) Da odeestand eS