# Evaluating and Improving Predictions

STAT 20: Introduction to Probability and Statistics

## Agenda

• Announcements
• Concept Questions
• Problem Set
• Lab

## Announcements

• Problem Sets:
• PS 16 (one-side) released Tuesday and due next Tuesday at 9am
• PS 17 (one-side) released today and due next Tuesday at 9am
• Extra Practice released Thursday (non-turn in)
• Lab 5:
• Lab 5.1 released Tuesday and due next Tuesday at 9am
• Lab 5.2 released Thursday and due next Tuesday at 9am
• Lab 5 Workshop next Monday

# Concept Questions

Which four models will exhibit the highest $R^2$?

01:00
# A tibble: 4 × 5
name    hours cuteness food_eaten is_indoor_cat
<chr>   <dbl>    <dbl>      <dbl> <lgl>
1 castiel    12      9          175 TRUE
2 frank      18     10          200 TRUE
3 luna       19      9.5        215 FALSE
4 luca       10      8          218 FALSE        
m1 <- lm(formula = hours ~ cuteness + food_eaten + is_indoor_cat,
data = cats)
      (Intercept)          cuteness        food_eaten is_indoor_catTRUE
-3.800000e+01      6.000000e+00      2.815002e-16     -4.000000e+00 

How many hours does the model predict Frank will sleep each day? Write out the linear equation of the model from the model output to help you.

03:00

Which is the most appropriate non-linear transformation to apply to time_being_pet?

01:00

# Problem Set

25:00

# Break

05:00

# Lab

45:00