Go to data Data Analysis regression
After pressing ok, you will be able to choose your input Y range and input X range. Your Y range is dependent variable or your output. Your X range is the independent variable or your input.
EX: Money spent on advertising is your X variable. Quantity sold (due to advertising) is your Y variable
You don’t have to have any of the check box checked, however, it is more convenient if you do.
Multiple R - is the coefficient of correlation. This tells you how related the variables are. A value close to 1 shows a STRONG and POSITIVE relationship. A value close to -1 shows a STRONG and NEGATIVE Relationship. A value close to 0 shows a WEAK relationship.
R-Square – tells you how much of the variability is accounted for. In example and R square of .90 says that 90% of the variability is accounted for by the coefficients it gives you in the summary output.
Adjusted R Square- The same as above, however it is adjusted since it is used when there is more than one independent variable.
Significance F and P-values
To check if your results are reliable (statistically significant), look at Significance F (0.001). If this value is less than 0.05, you're OK. If Significance F is greater than 0.05, it's probably better to stop using this set of independent variables. Delete a variable with a high P-value (greater than 0.05) and rerun the regression until Significance F drops below