Exercise

# Visualizing the relationship

Now that we've gone over the effect on certain errors and calculated the necessary sample size for different power values, let's take a step back and **look at the relationship between power and sample size** with a useful plot.

In this exercise, we'll switch gears and look at a t-test rather than a z-test. In order to visualize this, use the `plot_power()`

function that shows sample size on the x-axis with power on the y-axis and different lines representing different minimum effect sizes.

Instructions

**100 XP**

- Assign a
`TTestIndPower()`

object to the`results`

variable. - Visualize the relationship between power and sample size using the
`plot_power()`

function with the appropriate parameter values; what do you notice?