Scatter Plots & Correlation Examples

This is a scatter plot showing the amount of sleep needed per day by age.

As you can see, as you grow older, you need less sleep (but still probably more than you’re currently getting...).

What type of correlation is shown here?

This is a negative correlation. As we move along the x-axis toward the greater numbers, the points move down which means the y-values are decreasing, making this a negative correlation.

Estimate a line of best fit.

These two scatter plots show the average income for adults based on the number of years of education completed (2006 data). 16 years of education means graduating from college. 21 years means landing a Ph.D.

What type of correlation does each graph represent?

Both graphs are positively correlated. As years of education increase, so does income.

Draw a line of best fit for each graph. Then, estimate and compare the earnings for each gender with 11 years of education completed.

Based on these plots it looks like a female who completes 11 years of school can expect to earn around $14,000/year while a male can expect to earn around $23,000/year.

These graphs show two important things. First, higher education does lead to a higher income in general. Second, there is a gender gap in income. While women have begun to close this discrepancy, there is more work to do.

What if females with 23 years of education have an average income of $80,000? How does including this point on the scatter plot change the trend of the line of best fit?

The data point added is an outlier and increases the slope of the line of best fit. This will make all predictions based on the line of best fit skewed. They will be greater than the rest of the data suggests.