options: Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

Distinguish between correlation and causation.

Compute (using technology) and interpret the correlation coefficient of a linear fit.
problem_activity: Problem 1
The scatterplot below displays the elevation and mean number of clear days per year of  U.S. cities. Two lines are shown on the scatterplot. Which represents the least squares line? Explain your choice.
[IMG]
Problem 2
Below is a scatter plot of foal birth weight and mare’s weight.
[IMG]
The equation of the least squares line for the data is
$${y=-19.6+0.248x}$$
, where
$$x$$
= mare’s weight (in kg) and
$$y$$
= foal’s birth weight (in kg).  What foal birth weight would you predict for a mare that weighs 520 kg?
How would you interpret the value of the slope in the least squares line?


correct_option_index: 0