Assignment chapter 2 Solution

Description

Single-parameter models

1. Estimating a probability from binomial data (2.1)

2. Posterior, data, and prior (2.2-2.3)

3. Informative prior: conjugate prior and non-conjugate prior (2.4)

4. Estimating normal mean with variance is known (2.5)

5. Normal distribution with known mean and unknown variance, Poisson distribution, Exponential distribution (2.6)

6. Example: cancer rate (2.7)

7. Noninformative prior (2.8)

R Examples:

1. R code for binomial data and normal data

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

Homework:

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

2. Programming: 2.11 (20 pts)

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