Exercise

# Posterior inference for multivariate regression

The 10,000 iteration RJAGS simulation output, `rail_sim_2`

, is in your workspace along with a data frame of the Markov chain output:

```
> head(rail_chains_2, 2)
a b.1. b.2. c s
1 49.76954 0 -12.62112 4.999202 111.02247
2 30.22211 0 -3.16221 4.853491 98.11892
```

You will use these 10,000 unique sets of parameter values to summarize the posterior mean trend in the relationships between trail `volume`

, `weekday`

status, and `hightemp`

.

Instructions

**100 XP**

Construct a scatterplot of `volume`

by `hightemp`

.

- Use
`color`

to distinguish between weekdays & weekends. - Superimpose a
`red`

line that represents the posterior mean trend of the linear relationship between`volume`

and`hightemp`

for weekends:`m = a + c Z`

- Superimpose a
`turquoise3`

line that represents the posterior mean trend of the linear relationship between`volume`

and`hightemp`

for weekdays:`m = (a + b.2.) + c Z`