To determine which statements regarding the scatter plot and line of best fit are correct, we'd ideally need to visualize the actual scatter plot. However, I can provide guidance on how to evaluate each statement based on typical characteristics of scatter plots and lines of best fit.
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A reasonable prediction SAT score of 1700 is a GPA of 3.0. - This could be correct or incorrect, depending on the actual data point’s position on the scatter plot.
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This is not an accurate line of best fit because it doesn't hit the lowest point. - This is likely incorrect. A line of best fit (or trend line) does not have to pass through all points, especially the lowest point. Its purpose is to represent the overall trend in the data.
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The line of best fit gives the best approximation of the association between SAT score and GPA. - This is generally correct. The line of best fit is intended to provide an approximation of the relationship between the two variables.
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The line of best fit can be used to make predictions of GPA based on SAT score. - This is correct. Once we have a line of best fit, it can be used for making predictions about one variable based on another.
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The line of best fit shows that the combined SAT Score and first semester SAT have a negative correlation. - This is likely incorrect. Typically, we would expect a positive correlation; as SAT scores increase, GPA tends to increase.
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A reasonable prediction SAT score of 2100 is a GPA of 3.5. - This could also be correct or incorrect, depending on the line of best fit in relation to the data points on the scatter plot.
Summary of likely correct statements:
- The line of best fit gives the best approximation of the association between SAT score and GPA.
- The line of best fit can be used to make predictions of GPA based on SAT score.
Without seeing the actual scatter plot, the validity of the other statements can't be definitively determined.