To interpret the slope and y-intercept in the context of the data given, we need to understand the linear model of the average weight of dogs as a function of age in months.
The slope represents the average weight gain of the dog per month, and the y-intercept represents the weight of the dog at birth (when age = 0 months).
Given the ordered pair (9,42), it indicates that at 9 months of age, the average weight of a dog is 42 pounds.
Now, let's calculate the slope using the data. Without the exact formula or data points used to determine the linear model, we can still interpret the response options provided.
Assuming the slope is given as 0.21 (as rounded in the first response), we would interpret it as follows:
- Every month, a dog averages a gain of 0.21 pounds.
- The y-intercept (0,0) means that a dog weighs 0 pounds at birth, which is not realistic but is the interpretation in the context of the model.
So the correct interpretation based on the response options would be: Every month, a dog averages a gain of 0.21 pounds and weighs 0 pounds at birth.