the table and graph shows the relationship between height (cm), x, and weight (kg), y. which statements are…

Explanation:

Step1: Analyze scatter - plot pattern

By observing the scatter - plot of height and weight data, we can see that as height increases, weight generally increases. This indicates a positive relationship.

Step2: Evaluate correlation strength

A correlation coefficient (r) close to 1 represents a strong positive correlation. Just by looking at the scatter - plot, we can see that the points follow a somewhat linear upward - sloping trend, but not perfectly. A value of (r\approx0.67) is reasonable for this kind of moderately strong positive relationship.

Step3: Consider linear model

The general form of a linear regression model is (y = mx + b). If there is a linear relationship between two variables, a linear equation can be used to model the data. Given the upward - sloping trend of the scatter - plot, a linear model like (y=0.72539x + 53.05434) is a possible fit.

Step4: Confirm linear relationship

The scatter - plot shows that the points roughly form a linear pattern, so there is a linear relationship between height and weight.

Step5: Identify association

Since the points show an upward - sloping trend, high weights are associated with high heights.

Answer:

A. The value of (r) is about (0.67). B. This is a strong positive correlation. C. The equation (0.72539x + 53.05434) models the data. D. There is a linear relationship between height and weight. E. There is a tendency for high weights to be associated with high heights.