How to Find the Gradient of a Line of Best Fit in Matlab?

You can easily find the gradient (slope) of a line of best fit in Matlab using the Basic Fitting tool within the figure window.

Here's a step-by-step guide:

Create Your Plot: First, generate the scatter plot of your data that you want to fit a line to. This could involve using the plot function with your x and y data. For example:
```
x = [1 2 3 4 5];
y = [2.1 3.9 6.1 8.2 9.9];
plot(x, y, 'o'); % 'o' creates circular markers for the data points
```
Access Basic Fitting: Once the figure window is open and displaying your plot, navigate to the menu bar at the top of the figure window. Click on Tools, and then select Basic Fitting.
Choose Linear Fit: In the Basic Fitting window, select the type of fit you want to apply to your data. In this case, choose Linear. This will fit a straight line (y = mx + b) to your data using a least-squares method.
Display the Equation: The Basic Fitting tool will automatically overlay the line of best fit on your plot. The equation of the line, including the slope (gradient) and y-intercept, will be displayed in the Basic Fitting window. You may need to check the box to display the equation on the plot itself.

In summary, the Basic Fitting tool provides a straightforward way to visualize a line of best fit and obtain its gradient in Matlab.

askvity