Research Skills: Week 88

Limitations of Excel in Regression Analysis

Learn
Regression Analysis could be performed using Excel software.

Unlearn
There are limitations in using Excel to perform regression Analysis.

Relearn
We need to consider the following limitations when we are using Excel to perform regression analysis.

No standardised coefficients. It can be very difficult to interpret unstandardised coefficients. You could calculate the standardised coefficients using the unstandardised coefficients, if you really wanted to. But you could have done the regression on your own, if you really wanted to.
Lack of diagnostic graphs. The standard diagnostic graphs are not available in Excel, e.g. the normality plot of the residuals, the scatterplot or residuals against predicted values. Again, you can work them out, but it ain't easy.

Lack of Diagnostic statistics. There are no collinearity diagnostics, which would help you to understand what was happening in the data that we analysed above (highly significant R2, but no significant parameters in the model). You could calculate the skew statistics, but not if you have more than 30 cases.

Lack of features. There is no hierarchical regression, no weighting cases, etc, etc, etc...
Inflexibility. If you want to run a slightly different analysis, it is hard work, because you have to move your data around, a process which is prone to errors.
Excel will only permit up to 16 regressors.

Excel requires that all the regressor variables be in adjoining columns. You may need to move columns to ensure this. e.g. If the regressors are in columns b and d you need to copy at least one of columns b and d so that they are adjacent to each other.