Web= E(uiuj) −E(ui)E(uj) = cov(ui,uj). 1.3. Note: We will use “Xx” to indicate all heterozygotes (written as “Xx or xX” in the Exercise). Pr(child is Xx child has brown eyes&parents have brown eyes) = 0· (1−p)4 + 1 2· 4p(1−p)3 + 1 ·4p2(1−p)2 1· (1−p)4 +1·4p(1−p)3 + 3 4 ·4p2(1−p)2 = 2p(1−p)+2p2 (1 −p)2 +4p(1−p)+3p2 ...
EE363 homework 4 solutions - Stanford University
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Web∂µ J µ = 0 , (6.2) where ∂µ ≡ ∂ ∂xµ. Because it is the contraction of 2 tensor indices, and because we already know that ∂µ transforms as a covariant 4-vector), we see that Eq. 6.1 would be manifestly Lorentz invariant if Jµ were a contravariant 4-vector (more precisely, a vector density; but we shall leave this det ail for a WebJ‚—‚ œyth ®1 X¯x È ˆ €„ ‰ ˜è œir helpl†h°3qri´òŠÈ†üwe±`«Q›{rifl€ €Ykn„ ²N revol•X‰X Ò jèful €gu‰£”x¢èž`p ‚Aoug b… no‡˜r¸€o‰pp·â’Œme… – m“ i’8rm±2n„ò‡ ‹@ ð¨Âindef’ˆguŒa–‘ 9s Ø… •0•ß »·0³Ìš¾ ‰mŠÀ†Ð‡ ®Èš°; r¡:CºÊ ... Webn −µ)/σ has a limiting standard normal distribution. The proof is almost identical to that of Theorem 5.5.14, except that characteristic functions are used instead of mgfs. Example (Normal approximation to the negative binomial) Suppose X1,...,Xn are a random sample from a negative binomial(r,p) distribution. Recall that EX = r(1−p) p ... bipper pines screenshot forks