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(4 points) 2. kiran collects data about the number of trees on property…

Question

(4 points)

  1. 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:

Brief Explanations
  • a. A strong correlation means that the data points in the scatter plot are closely clustered around a line (either a straight line for linear correlation or a curve for non - linear correlation). In this situation, it means that there is a consistent pattern in the relationship between the number of trees on school property and student standardized test scores.
  • b. A positive correlation means that as the number of trees on school property increases, the average standardized test scores also tend to increase. The two variables move in the same direction.
  • c. Correlation does not imply causation. Just because there is a strong and positive correlation between the number of trees and test scores does not mean that the trees directly cause the better test scores. There could be other confounding variables (e.g., schools with more resources might be able to afford more trees and also provide better educational support for students).

Answer:

a. The data points are closely clustered around a line (showing a consistent pattern in their relationship).
b. As the number of trees increases, test scores also tend to increase (variables move in the same direction).
c. Correlation does not imply causation. There could be other factors (confounding variables) affecting both the number of trees and test scores.