How to Interpret the Linear Regression Summary in Microsoft Excel 2003

1. Right-click on the regression line in your chart, and choose Properties. Check 'Display equation on chart' and 'Display R-squared value on chart'. Click OK.
2. Look at the R-squared value displayed next to the regression line. The R-squared value represents the amount of variability in the data that is explained by the linear regression analysis. If all the data lies exactly on the regression line, the R-squared value will be 1. If the R-squared value is 0, that means there is no correlation between the two datasets.
3. Turn your attention to the equation listed above the R-squared value. It will be of the form 'y = m x b', where m and b have been replaced by numbers. This equation describes the linear regression line. The 'm' value is the slope of the line, and the 'b' value is the location where the line crosses the vertical axis. You can use this equation to predict values in the dataset based on their value on the horizontal axis; just multiply their horizontal location by the 'm' value and then add the 'b' value to the result; this will give you the best estimate of the location of that point based on the linear regression analysis.
4. Look at the slope of the line. If it slopes downwards to the right, the data is 'negatively correlated,' if it slopes upward, the data is 'positively correlated.' Positive correlation means that the datasets tend to agree with or reinforce each other; negative correlation means that they tend to be at odds or mutually exclusive.