In this exercise, we will assume a basic familiarity with
Microsoft^{®} Excel™ spreadsheet software. Some background
information about Microsoft Excel is provided at the link to the right. We will
briefly present the use of Microsoft Excel to perform **linear regression**, or
fitting a straight line to a set of data. The form of the equation of a straight
line is:

\[y = mx + b\] |
(1) |

In equation (1), *x* is the abscissa and *y* is the ordinate, while
*m* is the slope of the line, and *b* is the y-intercept.

The use of Microsoft Excel to fit a straight line to a set of data will be presented in the context of an example. We will assume that we have measured a set of five data points as follows:

- (1.3, 2.1), (2.4, 5.2), (3.1, 6.4), (4.2, 7.7), (5.6, 11.2)

In the above set of numbers, the data are presented in pairs of (x,y) points. Steps for using this data to create a straight-line curve fit using Microsoft Excel are presented below.

First, we need to enter the data into Microsoft Excel. We will input the
*x* data into the first column and the *y* data in the second
column. Our spreadsheet looks as shown below.

Select the data in the spreadsheet by clicking and dragging from cell A1 to cell
B5. Select the **Insert** tab and click on **Scatter** under the chart
options and select the option that displays data points, as shown below.

A chart should be added to your spreadsheet, similar to the one shown below.

Under the **Chart Tools**, click on the **Layout** tab. Click on the
**Trendline** button and select **More Trendline Options**, as shown below.

You should get a dialog box. Choose a **Linear** trendline and select **
Display Equation on Chart** and **Display R-squared value on chart**, as
shown below. Click on **Close**.

The equation of the best-fit straight line and the correlation coefficient are added to the chart. Your chart should look approximately as shown below.

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