The scatterplot in the image represents the relationship between time spent playing a video game (in minutes) and the number of points scored. Based on the plotted points, we need to estimate the number of points scored by a student who spends 45 minutes playing.

From the scatterplot, the data points show a positive trend, meaning that as time increases, the number of points scored also increases. The points closest to the 30-minute mark are around 750 to 850 points, and the points around 35 minutes are approaching 900-1,000 points.

To estimate the score for 45 minutes, the points seem to follow an increasing pattern, and the line of best fit would likely land somewhere near 1,200 points.

Therefore, the best prediction of the number of points scored by a student who plays for 45 minutes is: A. 1,200

Would you like further details on the estimation process or how the scatterplot data works?

Related Questions:

1. What is a line of best fit, and how can it help in predicting future points?
2. How do scatterplots visually represent trends in data?
3. Why is it important to observe the trend in data to make predictions?
4. What role do outliers play in determining predictions from scatterplots?
5. How can we improve predictions from scatterplots using mathematical models?

Tip:

When interpreting scatterplots, drawing a trend line or "line of best fit" can help you predict values that aren't directly plotted.