Challenge: Visualize Correlation Between Education and Employment
Scatter plots are a powerful way to visualize the relationship between two numerical variables. In policy evaluation, you often want to see if higher education attainment in a region is associated with higher employment rates. By plotting each region as a point with its education rate on the x-axis and its employment rate on the y-axis, you can visually assess whether there is a correlation—such as whether regions with more education tend to have higher employment.
12education_rates = [78.5, 82.3, 69.4, 91.2, 74.8, 88.1, 85.6] employment_rates = [65.2, 70.1, 58.7, 80.3, 60.5, 75.4, 73.2]
When creating a scatter plot, it is important to clearly label each axis so that viewers understand what each point represents. The x-axis should indicate education attainment rate, while the y-axis should show employment rate. A descriptive title helps communicate the purpose of the visualization. Once the plot is created, you can interpret patterns: if the points trend upward from left to right, this suggests a positive correlation between education and employment—meaning higher education rates are associated with higher employment rates.
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Write a function that creates and displays a scatter plot of education attainment rates versus employment rates for several regions.
- The function must plot the points using
education_rateson the x-axis andemployment_rateson the y-axis. - The x-axis must be labeled "Education Attainment Rate (%)".
- The y-axis must be labeled "Employment Rate (%)".
- The plot must have the title "Correlation Between Education and Employment Rates".
- The plot must be displayed.
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Scatter plots are a powerful way to visualize the relationship between two numerical variables. In policy evaluation, you often want to see if higher education attainment in a region is associated with higher employment rates. By plotting each region as a point with its education rate on the x-axis and its employment rate on the y-axis, you can visually assess whether there is a correlation—such as whether regions with more education tend to have higher employment.
12education_rates = [78.5, 82.3, 69.4, 91.2, 74.8, 88.1, 85.6] employment_rates = [65.2, 70.1, 58.7, 80.3, 60.5, 75.4, 73.2]
When creating a scatter plot, it is important to clearly label each axis so that viewers understand what each point represents. The x-axis should indicate education attainment rate, while the y-axis should show employment rate. A descriptive title helps communicate the purpose of the visualization. Once the plot is created, you can interpret patterns: if the points trend upward from left to right, this suggests a positive correlation between education and employment—meaning higher education rates are associated with higher employment rates.
Swipe to start coding
Write a function that creates and displays a scatter plot of education attainment rates versus employment rates for several regions.
- The function must plot the points using
education_rateson the x-axis andemployment_rateson the y-axis. - The x-axis must be labeled "Education Attainment Rate (%)".
- The y-axis must be labeled "Employment Rate (%)".
- The plot must have the title "Correlation Between Education and Employment Rates".
- The plot must be displayed.
Ratkaisu
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