1. **State the problem:** We are given a least squares regression line: $$\text{Predicted Hats} = 4 + 0.2 \times (\text{Pairs of Shoes})$$ and asked which statement about this line is true. 2. **Understand the regression line:** The equation is in the form $$y = b_0 + b_1 x$$ where: - $$b_0 = 4$$ is the y-intercept (predicted hats when pairs of shoes = 0) - $$b_1 = 0.2$$ is the slope (change in hats per additional pair of shoes) 3. **Evaluate each statement:** - **A.** "Jen predicts that a person who does not own any shoes will own 4 hats." - When pairs of shoes = 0, predicted hats = $$4 + 0.2 \times 0 = 4$$. This is true. - **B.** "Sally owns 8 pairs of shoes. It is predicted that Sally will also own 20 hats." - Predicted hats = $$4 + 0.2 \times 8 = 4 + 1.6 = 5.6$$, not 20. So false. - **C.** "The slope of the data represents 4 pairs of shoes owned for every hat owned." - The slope 0.2 means for each additional pair of shoes, hats increase by 0.2, or 1 hat per 5 pairs of shoes, not 4 pairs per hat. So false. - **D.** "There is a negative correlation between number of pairs of shoes owned and number of hats owned." - The slope is positive (0.2), so correlation is positive, not negative. False. 4. **Conclusion:** Only statement A is true. Final answer: **A**