1. The problem is to understand the relationship between employment growth rate (E) and productivity growth rate (P) using the given data points for six countries. 2. We have the points: Austria (2.0, 4.0), Belgium (1.7, 3.9), Canada (2.0, 1.5), Denmark (2.4, 3.0), Italy (4.0, 2.0), Japan (5.9, 9.6). 3. To analyze the relationship, we can consider plotting these points on a scatter plot with E on the x-axis and P on the y-axis. 4. The scatter plot helps visualize correlation: if points trend upward, E and P are positively correlated; if downward, negatively correlated; if scattered randomly, no correlation. 5. Observing the points, Japan (5.9, 9.6) stands out with much higher values, which may influence correlation. 6. To quantify correlation, one could calculate the Pearson correlation coefficient $r$ using the formula: $$r = \frac{n\sum xy - \sum x \sum y}{\sqrt{(n\sum x^2 - (\sum x)^2)(n\sum y^2 - (\sum y)^2)}}$$ where $x$ and $y$ are the E and P values respectively, and $n=6$. 7. This formula measures linear correlation between E and P. 8. In summary, the scatter plot visually shows the relationship, and the correlation coefficient quantifies it. Final answer: The scatter plot of the points (E, P) for the six countries shows the relationship between employment growth and productivity growth, with Japan notably higher. Calculating the correlation coefficient would provide a precise measure of their linear relationship.