Question
On today's episode of Science Time with Shelby, Shelby demonstrates that walking speed affects how wet a person will get in the rain. She simulates walking through the rain at various speeds.
Shelby keeps track of her walking speed (in meters per second), x. Next, she measures how wet she is by taking the difference of her weight before and after walking through the rain (in kilograms), y.
The least squares regression line of this data set is:
y=
–
2.762x+5.869
Complete the following sentence:
The least squares regression line predicts that a 1 meter per second increase in walking speed will cause a person to soak up
fewer kilograms of water.
Shelby keeps track of her walking speed (in meters per second), x. Next, she measures how wet she is by taking the difference of her weight before and after walking through the rain (in kilograms), y.
The least squares regression line of this data set is:
y=
–
2.762x+5.869
Complete the following sentence:
The least squares regression line predicts that a 1 meter per second increase in walking speed will cause a person to soak up
fewer kilograms of water.
Answers
GPT-4o mini
The least squares regression line predicts that a 1 meter per second increase in walking speed will cause a person to soak up **2.762** fewer kilograms of water.