Why “excel” is a good software tool to create a line of best fit?

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In statistics, a line of best fit is the line that best “fits” or describes the relationship between a predictor variable and a .

The following step-by-step example shows how to create a line of best fit in Excel.

Step 1: Enter the Data

First, let’s enter the following dataset that shows the number of hours spent practicing and the total points scored by eight different basketball players:

 

Step 2: Create a Scatter Plot

Next, let’s create a scatter plot to visualize the relationship between the two variables.

To do so, highlight the cells in the range A2:B9, then click the Insert tab along the top ribbon, then click the option titled Scatter in the Charts group:

The following scatter plot will automatically be created:

Step 3: Add the Line of Best Fit

To add a line of best fit to the scatter plot, click anywhere on the chart, then click the green plus (+) sign that appears in the top right corner of the chart.

Then click the arrow next to Trendline, then click More Options:

In the Format Trendline panel that appears, click the button next to Linear as the trendline option, then check the box next to Display Equation on chart:

Step 4: Interpret the Line of Best Fit

From the chart we can see that the line of best fit has the following equation:

y = 2.3095x – 0.8929

Here is how to interpret this equation:

• For each additional hour spent practicing, average points scored increases by 2.3095.
• For a player who practices zero hours, average points scored is expected to be -0.8929.

Note that it doesn’t always make sense to interpret the intercept value in a regression equation.

For example, it’s not possible for a player to score negative points.

In this particular example, we’re mostly interested in the value for the slope of the regression line which is 2.3095.