Assignment chapter 2 Solution

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Description

Single-parameter models

 

  • Estimating a probability from binomial data (2.1)

 

  • Posterior, data, and prior (2.2-2.3)

 

  • Informative prior: conjugate prior and non-conjugate prior (2.4)

 

  • Estimating normal mean with variance is known (2.5)

 

  • Normal distribution with known mean and unknown variance, Poisson distribution, Exponential distribution (2.6)
  • Example: cancer rate (2.7)

 

  • Noninformative prior (2.8)

 

 

 

R Examples:

 

  1. R code for binomial data and normal data

 

  1. Chapter 2—3, “Bayesian Computation with R”

 

 

 

Homework:

 

  1. Sec  Exercise: 2.1 (5 pts), 2.5 (20 pts), and 2.20 (15 pts)

 

  1. Programming: 2.11 (20 pts)

 

  1. Reading Assignment: Chapter 2 of textbook, Chapter 2—3 of “Bayesian Computation with R”.