Describe how you can make the line of best fit. Write the approximate slope and y-intercept of the line of best fit. Show your work.
So, I know how to make a line of best fit-- how do I write the y-intercept or slope of it, though? Please, please help.
The coordinate (tell me if picture link doesn't work) : file://localhost/Users/kylebryant/Desktop/Screen%20shot%202016-04-15%20at%2012.00.41%20AM.png
To find the slope and y-intercept of a line of best fit, you will need to have a set of data points. The line of best fit is the line that passes through the average of the data points and minimizes the sum of the squared differences between the data points and the line.
Since I cannot access the picture you mentioned, I will provide you with a general explanation of how to find the slope and y-intercept of a line of best fit.
Here are the steps to calculate the slope and y-intercept of a line of best fit:
1. Gather your data points. You should have a set of data points that consists of pairs of x and y values.
2. Calculate the average of the x and y values. Add up all the x values and divide by the total number of data points to get the average x value. Similarly, add up all the y values and divide by the total number of data points to get the average y value.
3. Calculate the slope. The slope (m) of the line of best fit represents the change in y divided by the change in x. You can calculate the slope using the formula: m = (Σ(xy) - n * x̄ * ȳ) / (Σ(x^2) - n * x̄^2), where Σ represents the sum of the values, n is the total number of data points, x̄ is the average x value, ȳ is the average y value, and x^2 represents the squared x values.
4. Calculate the y-intercept. The y-intercept (b) is the value of y when x is zero. You can calculate the y-intercept using the formula: b = ȳ - m * x̄, where ȳ is the average y value and x̄ is the average x value.
By following these steps, you should be able to calculate the slope and y-intercept of the line of best fit for your given set of data points.