Question
A veterinarian collected data on the average weight of dogs by age and months. Interpret the slope and the Y intercept (0,0) of the linear model, using the ordered pair (9,42) round the slope to the nearest hundredth
Every month, a dog averages a gain of 0.21 pounds and weighs 0 pounds at birth
Every month, a dog averages gain of 4.67 pounds
Every 4.67 months, a dog averages gain of 1 pound and weighs 0 pounds of birth
Every month averages of 4.3 pounds and weighs 0 pounds at birth
Every month, a dog averages a gain of 0.21 pounds and weighs 0 pounds at birth
Every month, a dog averages gain of 4.67 pounds
Every 4.67 months, a dog averages gain of 1 pound and weighs 0 pounds of birth
Every month averages of 4.3 pounds and weighs 0 pounds at birth
Answers
GPT 3.5
The slope of the linear model is the average weight gain per month, which is 0.21 pounds. This means that for every month that passes, a dog will gain an average of 0.21 pounds in weight.
The Y-intercept of the linear model is the weight of the dog at birth, which is 0 pounds. This makes sense because a dog weighs 0 pounds at birth.
Using the ordered pair (9,42), we can calculate the slope as follows:
Slope = (42-0)/(9-0) = 42/9 = 4.67
Therefore, the slope of the linear model, rounded to the nearest hundredth, is 4.67.
In summary, the slope of the linear model represents the average weight gain per month for a dog, while the Y-intercept represents the weight of the dog at birth.
The Y-intercept of the linear model is the weight of the dog at birth, which is 0 pounds. This makes sense because a dog weighs 0 pounds at birth.
Using the ordered pair (9,42), we can calculate the slope as follows:
Slope = (42-0)/(9-0) = 42/9 = 4.67
Therefore, the slope of the linear model, rounded to the nearest hundredth, is 4.67.
In summary, the slope of the linear model represents the average weight gain per month for a dog, while the Y-intercept represents the weight of the dog at birth.