To find the slope of the least-squares regression line for the given data, we can use the formula:

$m = \frac{n\sum xy - \sum x \sum y}{n\sum x^2 - (\sum x)^2}$

where:

• $n$ is the number of data points,
• $\sum xy$ is the sum of the products of each $x$ and $y$,
• $\sum x$ is the sum of all the $x$ values,
• $\sum y$ is the sum of all the $y$ values,
• $\sum x^2$ is the sum of the squares of each $x$ value.

Let's extract the data from the image and calculate the necessary values. I'll start by noting down the values and performing the calculations.The slope of the least-squares regression line for the given data is approximately $-0.40$, rounded to two decimal places.

Would you like any further details or have any additional questions?

Here are 8 related questions:

1. What does the negative slope indicate about the relationship between birthrate and female life expectancy?
2. How would you interpret the y-intercept of this regression line?
3. Can you calculate the correlation coefficient for this data?
4. How would the slope change if the birthrate increased uniformly across all countries?
5. What is the equation of the least-squares regression line using the slope?
6. How would you predict female life expectancy for a country with a specific birthrate using this line?
7. What are the limitations of using this regression model for predictions?
8. How would you calculate the residuals for each data point using this regression line?

Tip: When interpreting a regression line, always consider the context of the data and the implications of the slope and intercept values.