MINITAB Programs for 
Workshop Statistics:  Discovery with Data, A Bayesian Approach

Download zip file containing all seven MINITAB macros:

minitab_macros.zip

• TOPIC 16 - Learning About a Proportion

p_disc.mac: Computes the posterior distribution for a proportion p when there is a discrete set of models.

Macro p_disc.mac

Instructions and sample output for p_disc.mac.

• TOPIC 17 - Learning About a Proportion Using Continuous Models

p_beta.mac: Summarizes beta distribution for p.

Macro p_beta.mac

Instructions and sample output for p_beta.mac.

• TOPIC 18 - Learning About a Mean Using Discrete Models

 m_disc.mac: Computes the posterior distribution for a mean M when there is a discrete set of models (sampling standard deviation h known).

Macro m_disc.mac

Instructions and sample output for m_disc.mac.

• TOPIC 19 - Learning About a Mean Using Continuous Models

normal.mac: Summarizes normal distribution for the mean M.

Macro normal.mac

Instructions and sample output for normal.mac

• TOPIC 21 - Learning About Two Proportions

Macro pp_prior.mac: Constructs prior distribution for (p1, p2) using discrete models.

Macro pp_prior.mac

Instructions and sample output for pp_prior.mac

Macro pp_disc.mac: Finds posterior distribution for (p1, p2) when a uniform discrete prior is used.

Macro pp_disc.mac

Instructions and sample output for pp_disc.mac

Macro pp_beta.mac: Using simulation, summarizes distribution for p2-p1 when proportions have independent beta distributions.

Macro pp_beta.mac

Instructions and sample output for pp_beta.mac