Q5 For this question, use data from only restaurants with between 50 and 60 items in the data set. Predict total fat from cholesterol, total carbs, vitamin a, and restaurant. Remove any nonsignificant predictors and run again. - Assign the strongest standardized regression coefficient to Q5. Your output should look something like this: ``` [variable name] [value]

Q5 <- fastfood |> group_by(restaurant) |> filter(n() >= 50 & n() <= 60) |> select(total_fat, cholesterol, total_carb, vit_a, restaurant) |> drop_na() |> lm(total_fat ~ cholesterol + total_carb + vit_a + restaurant, data = fastfood) |> step(glm, direction = "backward") |> lm.beta() |> max()

When I submit this code, I get the following error:

Error in xj[i] : invalid subscript type 'language'