From the provided image, the task is to determine how many outliers are present in the data. Outliers are defined as data points that lie outside the ±2 standard deviation (±2σ) range from the line of best fit (indicated by the dashed lines).

To count the outliers:

1. Examine all the data points plotted on the graph.
2. Identify the points that fall outside the dashed boundary lines (±2σ range).
3. Count these points.

Based on the visual inspection of the graph:

• There seem to be 2 points that fall outside the dashed lines, which means there are 2 outliers.

If you have further questions or want details clarified, let me know!

Follow-up questions:

1. What are standard deviations, and how are they used to identify outliers?
2. How is a line of best fit determined in a regression model?
3. Why are ±2σ boundaries significant in analyzing data?
4. What happens if there are too many outliers in a dataset?
5. Can outliers impact the slope of the line of best fit? Why or why not?

Tip:

Always double-check the dataset's points visually when identifying outliers, as mistakes in interpretation can alter results.