Respuesta :
Answer:
The correlation coefficient measures the strength and direction of the linear relationship between two variables. A correlation coefficient of r = 0.829 indicates a strong positive linear relationship between the final exam score and the midterm score for the students in the introductory statistics course.
If you were to create a scatterplot of the final exam score versus the midterm score for all individual students in the course, the correlation coefficient would likely be similar or slightly weaker. This is because the correlation coefficient represents the overall relationship between the two variables, and adding more data points (students) to the scatterplot may slightly influence the strength of the correlation.
To better understand this, let's consider an example. Imagine you have a scatterplot with only a few data points, and these data points show a strong positive linear relationship. Now, if you were to add more data points to the scatterplot, it is possible that some of these new points might not perfectly align with the existing trend, leading to a slightly weaker correlation coefficient. However, since the given correlation coefficient is already quite strong (0.829), any potential weakening of the correlation would likely be minimal.
In summary, if you were to create a scatterplot of the final exam score versus the midterm score for all individual students in the introductory statistics course, the correlation coefficient would be either about the same or slightly weaker.
