1. C HAPTER 4: M ORE ON T WO - V ARIABLE D ATA Part 2

2. P OWER L AW M ODELS

3. E XAMPLE 2 – P REDICTING B RAIN W EIGHT By taking another look at the brain weight vs. body weight scatterplot from last class (without the 4 outliers) and comparing it to the power models, it appears to take on the shape of a power model more so than the logarithmic model we had initially said. This is why the book had transformed by taking the logarithm of both variables as opposed to just the response variable.

4. E XAMPLE 2 – P REDICTING B RAIN W EIGHT

5. Since the original weights were in kilograms, we need to substitute the 127 in for x: Based on the model, Bigfoot is expected to have a brain weight of 333.7 grams. E XAMPLE 2 – P REDICTING B RAIN W EIGHT

6. E XAMPLE 3 – F ISHING T OURNAMENT Imagine that you have been put in charge of organizing a large fishing tournament in which prizes will be given for the heaviest fish caught. The following table represents the ages, lengths, and weights of 20 fish caught. Type the values in your calculator and look at its scatterplot What type of graph does it appear to be? Exponential

7. E XAMPLE 3 – F ISHING T OURNAMENT