ENGG 2780 A ESTR 2020 Statistics for Engineers

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ENGG 2780 A / ESTR 2020: Statistics for Engineers Spring 2021 2. Bayesian Estimation

ENGG 2780 A / ESTR 2020: Statistics for Engineers Spring 2021 2. Bayesian Estimation and Hypothesis Testing Andrej Bogdanov

Point estimation How to turn conditional PDF/PMF f. Q|X(q | x) estimate into one

Point estimation How to turn conditional PDF/PMF f. Q|X(q | x) estimate into one number? Conditional expectation (CE) estimator: E[q | X = x] Maximum a posteriori (MAP) estimator: argmax f. Q|X(q | x)

Point estimation for normals Xi = Normal(Q, 1) independent given Q Q is Normal(x

Point estimation for normals Xi = Normal(Q, 1) independent given Q Q is Normal(x 0, 1) (Q | X 1 = x 1, …, Xn = xn) is Normal(x, 1/√n) CE estimate: MAP estimate:

Romeo’s model X = Uniform(0, Q) Q = Uniform(0, 1) On her first date,

Romeo’s model X = Uniform(0, Q) Q = Uniform(0, 1) On her first date, Juliet arrives ½ hour late. CE estimate: MAP estimate:

Beta(1, 1) CE = a/(a + b) Beta(11, 21) Beta(2, 3) MAP = h/(h

Beta(1, 1) CE = a/(a + b) Beta(11, 21) Beta(2, 3) MAP = h/(h + t) Beta(51, 101)

Hypothesis testing Suppose Q takes two values (e. g. spam / legit) MAP =

Hypothesis testing Suppose Q takes two values (e. g. spam / legit) MAP = argmax f. Q|X(q | x) Choose the one for which f. Q|X(q | x) is larger

Q = 80% legit, 20% spam q P(X 1| q) P(X 2| q) legit

Q = 80% legit, 20% spam q P(X 1| q) P(X 2| q) legit 0. 03 spam 0. 1 0. 0001 0. 01 The Citibank concerning wire transfers of your fund. Your letter has been referred to the (JMCB) Legal Division for Funds (US$2. 8 Million Dollars)

Coin A is heads with probability 1/3. Coin B is tails with probability 1/3.

Coin A is heads with probability 1/3. Coin B is tails with probability 1/3. HHHT are 4 flips of a random coin. Which coin was it?

What is the probability you are wrong, given the outcome is HHHT? What is

What is the probability you are wrong, given the outcome is HHHT? What is the probability you are wrong on average?

Binary hypothesis testing error Q = 0 (null) or 1 (alternative) ^ = 0

Binary hypothesis testing error Q = 0 (null) or 1 (alternative) ^ = 0 (reject) or 1 (accept) Q ^ error = P(Q ≠ Q)

A car-jack detector X outputs Normal(0, 1) if there is no intruder and Normal(1,

A car-jack detector X outputs Normal(0, 1) if there is no intruder and Normal(1, 1) if there is. When should alarm activate?

MAP hypothesis testing error P(MAP ≠ Q) ≤ 50% Proof:

MAP hypothesis testing error P(MAP ≠ Q) ≤ 50% Proof:

You observe HH. Which coin was it? What is the probability you are wrong?

You observe HH. Which coin was it? What is the probability you are wrong? coin P(H) A B C 1 ¾ ½

Multiple hypotheses Q takes k possible values ^ ≠ Q) error = P(Q P(MAP

Multiple hypotheses Q takes k possible values ^ ≠ Q) error = P(Q P(MAP ≠ Q) ≤ 1 - 1/k