Creating the best fit straight line through a set of points on a graph is called

1. slope-intercept method.
2. connecting the dots.
3. linear regression.
4. the straight edge method.
5. the equation of a straight line.

linear regression

The correct answer is 3. linear regression.

Linear regression is a statistical technique used to find the best fit straight line that represents the relationship between a dependent variable and one or more independent variables. In this case, the dependent variable would be the points on the graph, and the independent variable would be the corresponding x-values.

To find the best fit straight line using linear regression, you can follow these steps:

1. Gather the data: Collect the set of points with their x and y coordinates from the graph.

2. Calculate the means: Find the mean of the x-values and the mean of the y-values.

3. Calculate the differences: Subtract the mean of the x-values from each x-value, and subtract the mean of the y-values from each y-value.

4. Calculate the products: Multiply the differences obtained in step 3 for each point (x, y). This will give you the products of the differences for each point.

5. Calculate the squared differences: Square each difference obtained in step 3 for each x-value.

6. Calculate the sum of squared differences: Add up all the squared differences obtained in step 5.

7. Calculate the sum of the products: Add up all the products obtained in step 4.

8. Calculate the slope (m): Divide the sum of the products obtained in step 7 by the sum of squared differences obtained in step 6.

9. Calculate the y-intercept (b): Substitute the slope (m), the mean of x-values, and the mean of y-values into the equation y = mx + b, and solve for b.

10. Write the equation of the straight line: Once you have the values for the slope (m) and the y-intercept (b), you can write the equation for the best fit straight line through the points as y = mx + b.

Therefore, the correct answer is option 3. linear regression.