To determine which graph shows the best line of fit for the data, we look at how well each line approximates the general trend of the plotted points.

Analyzing each option:

1. Top Left: The line has a slight positive slope, suggesting a weak positive correlation.
2. Top Right: The line has a steep negative slope, indicating a strong negative correlation.
3. Bottom Left: This line also has a negative slope, but it is less steep than the top-right one.
4. Bottom Right: The line has a positive slope, suggesting a positive correlation.

To identify the correct line of best fit, we should match the general direction and trend of the points in the scatter plot. Observing the data points, it seems they are somewhat scattered but exhibit a slight positive trend overall. Therefore, the top left graph, which shows a line with a slight positive slope, is the best match for the data’s trend.

Answer:

The best line of fit for the data is shown in the top-left graph.

Would you like a detailed explanation on how to calculate a line of best fit?

Here are some related questions you might find helpful:

1. What is the purpose of a line of best fit in data analysis?
2. How do you calculate the slope and intercept of a line of best fit?
3. What is the difference between a positive and a negative correlation?
4. How can you use a line of best fit to make predictions?
5. Why might a data set not have a clear line of best fit?

Tip: When estimating a line of best fit, look for the general trend of the points rather than focusing on individual points.