Suppose you're working as a demographerat the census bureau of the United States. Your supervisor collects a random sample of 500 people living in New York City and measures their height (in inches), weight (in pounds), and age (in years). Your supervisor runs a simple linear regression model predicting height (the outcome variable) using weight (the predictor variable). The slope is 1.50 and the intercept is 50.The average weight is 180 pounds and the median weight is 125 pounds. The average age is 45 years and the median age is 42 years.

Based on these results, your supervisor concludes: "For every a one-pound increase in weight, we expect the height to decrease by 1.50 inches. This shows that older people are more likely to experience weight gain than younger people. However, we may want to be careful interpreting our results since the distribution of weight is right-skewed. The 50th percentile for weight is much larger than the mean weight in our sample."

What is not wrong with your supervisor's interpretation of the results?

Group of answer choices

The 50th percentile is larger than the mean.

The regression model predicts weight using age as a predictor variable.

The slope from the regression model is negative.

The distribution of weight is right-skewed.