Exercise

# CI using t-theory

In previous courses, you have created confidence intervals with the formula of statistic plus/minus some number of standard errors. With bootstrapping, we typically use two standard errors. With t-based theory, we use the specific t-multiplier.

Create a CI for the slope parameter using both the default `tidy()`

call as well as `mutate()`

to calculate the confidence interval bounds explicitly. Note that the two methods should give exactly the same CI values because they are using the same computations.

`alpha`

has been set to `0.05`

and the degrees of freedom of the `twins`

dataset is given to you.

Instructions 1/2

**undefined XP**

- Calculate the confidence level as one minus
`alpha`

. - Calculate the upper percentile cutoff from
`alpha`

. - Calculate the critical value from the inverse cumulative density function of the t-distribution,
`qt()`

. Pass it the upper percentile cutoff and the degrees of freedom.