```
# Assign the expected value of the posterior distribution to the variable `exp_value`
exp_value <- B*mu + (1-B)*Y
#> Error in eval(expr, envir, enclos): object 'B' not found
# Assign the standard error of the posterior distribution to the variable `se`
se <- sqrt( 1/ (1/sigma^2 + 1/tau^2))
#> Error in sigma^2: non-numeric argument to binary operator
# Using the `pnorm` function, calculate the probability that the actual spread was less than 0 (in Trump's favor). Print this value to the console.
1 - (pnorm(0, exp_value/se) - (pnorm(0, -exp_value/se)))
#> Error in pnorm(0, exp_value/se): object 'exp_value' not found
```

# Odds of winning Florida

What I am trying to do: Using the pnorm function, calculate the probability that the spread in Florida was less than 0.

My usage of pnorm() seems valid.