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Confidence Intervals and Hypothesis Testing Formulas, Study Guides, Projects, Research of Statics

Confidence IntervalsInferential StatisticsProbability DistributionsHypothesis Testing

Formulas for calculating confidence intervals and hypothesis testing in statistics, including z-scores, t-scores, chi-square, F-distribution, and various probability distributions. It also includes formulas for Mann-Whitney U test, Wilcoxon rank-sum test, sign test, and Kruskal-Wallis test.

What you will learn

  • How is the t-score calculated for a hypothesis test?
  • What is the formula for the Mann-Whitney U test?
  • How is the Kruskal-Wallis test used in hypothesis testing?
  • What is the formula for calculating a confidence interval for a population mean?
  • How is the F-distribution used in hypothesis testing?
  • What is the formula for the chi-square distribution?

Typology: Study Guides, Projects, Research

2013/2014

Uploaded on 08/19/2021

gbry-tellez
gbry-tellez 🇰🇭

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Download Confidence Intervals and Hypothesis Testing Formulas and more Study Guides, Projects, Research Statics in PDF only on Docsity! INTERVALOS DE CONFIANZA Estimacion Condiciones Intervalo de Confianza Bilateral x OC ep<z 2 . Ze) SS ¥4+2(x)—= Lu o? (Conocida) (3) vn H @) vn 2 2 (% — X2) of <(% —%)+ of 22 Ha B2 of,0z (Conocidas) 41 ~ Xa 78) mh ny Hy ~ Ha Sa ~%2 *8) Ny Ng . Ss s o? (desconocida) ¥- {Ena Susxt ‘ena G H Poblacién Normal 2 n 2 n ¢ )-t, +—< <(%—-*%)+t 1 + 1 (€y — X, &\Sy _—+— S by — Ue S (% — Xz Sy [—+— ; ; 1 2. ( ) rin th Hy — Ha 1 2. (Ev) ‘Dp mm of = of 14 — be Desconocidas Sp 2 2 2 62 _ _ St Sz _ — St, 52 (% — X%)) — tye.) JH + < Wy — by S (% — 2) + te) J F# id () Jn ng Ha ~ Ha me (S) Jn ne of # oF by =I Desconocidas Sp + sp 2 Poblaciones 1 72 2 v= normales ‘sf 2 3 2 ny Ng mt+1ong+1 n—1)s? n—1)s? | =D oe =) o Poblacién Normal X(Sn-1) X(1-Sn-1) s} a Si 52F (1-Smaam-1) = G2 = 521 (Ena-1m.-1) o2 Poblaciones of normales _ 1 F(Sng-10,-1) “Ff 2 (1-$ni-1.n2-1) Poblaciones ~ D— 2% P normales (@) Pi — P2 Distribucién Binomial PRUEBAS DE HIPOTESIS Ho Condiciones Estadistico calculado _ X—Ho 2 . Zeal = —@F L=Lo ao” (Conocida) Va teal = v=n-1 L=Lo o* (Desconocida) ofy 0} zqh = EE 14 =e Conocidas oz G2 1402 nm N2 t= X1— X2 — Mo ; ; cal Tae 1 O71 = 03 Seng tng My = be Desconocidas Sp X1— X2 — Ho Coal = St, 82 nm Ng - of # oF Ma He Desconocidas (2 + st): 1 Ne v= pe 2 (i), (e) 1 2 ny+1 + Nz +1 to 2 _™- 1)s? = 1 = o* =0§ cal a PRUEBA DE RANGO CON SIGNO DE WILCONXON Tipo de Prueba | Para probar Hy | Contra H, Weal Wteo Dos colas Ly = Uo 1 # Uo min(w*,w7) Ween) Cola superior Ly = Uo Hy < Uo wt Ween) Cola inferior Ly S Uo Ly > Uo w- Ween) PRUEBA DE LA SUMA DE RANGOS DE WILCONXON Tipo de Prueba | Para probar Hy | Contra H, Weal Wteo Dos colas La = Uo Ly ¥ Uo W, OW2 Wenn) Cola superior Ly = Uo 1a < Lo Wy Wayne) Cola inferior La S Uo Ly > Ho W2 Wenn) PRUEBA DE SIGNO Tipo de Prueba | Para probar Hy | Contra H, Reat Rteo Dos colas Me, = Mey Me, # Mey min(r*,r7) Roan) Cola superior Me, > Mey Me, < Mey rt Ran) Cola inferior Me, < Mey Me, > Mey rT Ran) PRUEBA U DE MANN - WHITNEY ny(ny +1 U,= nn, +mintd_p, N2(Nz +1 Ur= nn, + FD _p, NyNz by = 2 N4N2 (Ny + nz +1) ou = 12 La prueba U Mann - Whitney se utiliza para probar hipdtesis acerca de la media de dos poblaciones: U-Hy Zeal = a Tipo de Prueba | Para probar Hy | Contra H, Zeal Zteo = min(U,,U,) — Dos colas Ha = He a # Ma | mina) ~ Hy 25) ou Cola superior Hy 2 be Hy Se pia Za) ou Cola inferior Ha S He Hy > He Ue Hy Z@) ou FORMULAS VALORES EXTREMOS 1. Distribucion Tipo | 1.1 Gumbel para valores maximos. F(x) = ene) f(x) =x enX GUE") gg < x < oo 05772 4 EQ@)=w=eto=ut q Var(x) =o "ea 1.2 Gumbel para valores minimos: F(x) =1-e78 Fe) =o eX Ve") <x <oo 0.5772 ,_ @ E(x) =p=U- Var(x) =o baa 2. Distribucion Tipo Il: Fréchet U k F(x) = eG) k U k+1 -(y foo =< (=) e \x x>0 2 1 2 1 ra-|g E(x) = =u r(a -;): Var (x) = 0? =u? [r(a -;) —r? (1 -z)h: v2 = (1-2) -1 k k k r2 (1 _ b k 3. Distribucion Tipo Ill: Weibull yk F(x) =1- ela) f= ka e x>0 E(x) =w=ur(1 +z): Var(x) = 0? =u? [r(a +7) —r? (1 +) V2= Nota: ran)= fo ttetdt 5; Tat 1=7T(r) 4. Distribucion Log Normal: 1 ae = Hi)" = 2 Finx 3 f(x) Tomvin © x>0; 12 Lint 50° 2 z Hy =e Binet 27 Im sg? = yy? fer nx — 1]; vy =Verm —1 —n@) = Minx Z=——__ nx DISTRIBUCION GAMMA 1 on * “| so — + (| x f(x) = (3) T(@) 0 en cualquier otro caso = = a. -f a EQ) =H=7Fi Var(x) =o = DISTRIBUCION EXPONENCIAL f(x) = { de~** x>0 } ~ 0 en cualquier otro caso 1 1 EQ) =H=73 Var(x) = 0? =>, DISTRIBUCION POISSON eYy* f(x) = PG at) =——, y=at; XS O23 eee cc even Ea=y; Var(x) =o? =y DISTRIBUCION BINOMIAL NEGATIVA F() = BC kD) = (FTF) = YE, 2B avr FQ) =u") Var(x) = 02 = C=?)
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