Final answer:
Ann would use a scatter plot to display the relationship between the percentage of the population that smokes and the lung cancer rate. This graph would help identify any correlation between the two variables and could be complemented by calculating the correlation coefficient or performing regression analysis.
Step-by-step explanation:
If Ann wants to display the connection between the percentage of the population that smokes and the lung cancer rate in each of the fifty states, she would likely use a scatter plot. This type of graph is commonly used to show the relationship between two quantitative variables. Each state would be represented by a point on the graph, with the x-axis representing the percentage of smokers and the y-axis representing the lung cancer rate.
A scatter plot can help to identify any correlation between the variables. If there is a positive correlation, the points will trend upwards, indicating that a higher percentage of smokers is associated with a higher lung cancer rate. Conversely, a negative correlation would show an inverse relationship. Ann can also calculate the correlation coefficient to quantify the strength of the relationship.
Further analysis, such as performing a regression analysis, could help to understand the nature of the relationship further, and whether other variables might be influencing it. It's important to remember that correlation does not imply causation; additional research would be necessary to establish a causal link.