The equation of the least squares regression line shown in the image is:

$y = -0.393x + 994.19$

Interpretation:

This equation tells us how the data is changing over time. The slope is $-0.393$, which means that for every year that passes, the value of the data decreases by about 0.393 units. The y-intercept is 994.19, which is the estimated value of the data when $x = 0$ (which would be in the far past, outside the range of the data we see here).

The $R^2$ value is 0.7934, which means that about 79.34% of the variation in the data can be explained by the linear trend in this model. This indicates a fairly strong relationship between the time and the values shown in the plot.

Would you like more details or have any questions?

Here are 5 related questions to think about:

1. What does the y-intercept of 994.19 represent in this context?
2. Why does a negative slope indicate a decrease over time?
3. What does an $R^2$ value of 0.7934 suggest about the data?
4. How would the graph change if the slope were positive?
5. What happens if the slope becomes steeper, say -1 instead of -0.393?

Tip: The closer the $R^2$ value is to 1, the better the line fits the data!