Exercise

# Comparing effect sizes

In the previous exercise, you calculated the effect sizes of `Age`

and `Sex`

on the cost of life insurance. Type these commands in the console to see the results again:

```
effect_size(model, ~ Age)
effect_size(model, ~ Sex)
```

In this exercise, you'll compare the two effect sizes.

You cannot do this just by comparing the numbers 3.35 and 10.23. Those numbers come with units, and the units are different for the two effect sizes. For `Age`

the units are USD/month per year, while for `Sex`

the units are USD/month. To do the comparison, you'll need to multiply the effect size for `Age`

by a number of years. Multiplying years times USD/month per year gives a result in USD/year --- the same units as the effect size for `Sex`

.

Using the console, find out what this multiplication factor needs to be to balance the two effect sizes. That is, find out how many years you would need to multiply the `Age`

effect size by in order to equal the effect size for `Sex`

.

(Aside: You might be interested to look at a life-expectancy table to see how different are the life expectancies for, say, a 55-year old male and female. Here's a link to an actuarial table. In the table, you'll see that a 55-year old male is expected to live approximately 25.3 more years, while a 55-year old female has an additional life expectancy of 28.7 years.)

Which is the correct statement?

Instructions

**50 XP**

##### Possible Answers

- The effect size for
`Sex`

corresponds to a change in`Age`

of about 3 years. - The effect size for
`Age`

corresponds to a change in`Sex`

from`M`

to`F`

. - The effect size for
`Sex`

is greater than that for`Age`

.