Question

points) 2. kiran collects data about the number of trees on property of different schools and the average standardized test scores for those schools. kiran says, \the scatter plot between the number of trees on a school property and student standardized tests scores shows a strong and positive correlation. an increase in the number of trees on school property causes the students to score better on standardized tests.\ a. what does having a strong correlation mean for the relationship between the variables in this situation? b. what does having a positive correlation mean for the relationship between the variables in this situation? c. what is wrong with the last sentence of kirans statement? explain your reasoning.

Explanation:

• a. A strong correlation means that the data points in the scatter - plot are closely clustered around an imaginary line (either a straight line in the case of linear correlation). In this situation, it means that there is a consistent pattern between the number of trees on school property and student standardized test scores.
• b. A positive correlation means that as one variable (the number of trees on school property) increases, the other variable (student standardized test scores) also tends to increase. So, schools with more trees on their property tend to have higher average standardized test scores.
• c. Correlation does not imply causation. Just because there is a strong and positive correlation between the number of trees on school property and student standardized test scores does not mean that the trees cause the better scores. There could be other confounding variables. For example, schools with more resources (which could be used to plant more trees) might also be able to afford better teaching materials, more qualified teachers, or smaller class sizes, which could be the real reasons for higher test scores.

Answer:

a. The data points are closely clustered around an imaginary line (showing a consistent pattern).
b. As the number of trees increases, test scores tend to increase.
c. Correlation does not imply causation. There could be confounding variables (e.g., school resources).