Results

A scatter plot shows the sample points on the coordinate plane of two entities (variables, responses).

Restart the Viewer again and

Select Scatter Plots for this time.
Change the z-coordinate to No entity, since we want a two-dimensional plot. Choose YIELD as the x-coordinate. Choose prc_thick_red_max as the y-coordinate.	YIELD vs. prc_thick_red_max

 Change the entity to be shown on the x-coordinate.

Conclusion: The first plot (YIELD vs. prc_thick_red_max) shows the most linear correlativity among the plots, which means again that YIELD is the most important variable for the maximum thickness reduction.

• We can verify this fact in different ways (also see Correlation Bars and Correlation Matrix).

If we want to find out the most important variable for the maximum thickness reduction, we can just view the correlation of the maximum percent thickness reduction (prc_thick_red_max) with the variables.

Start the LS-OPT Viewer by selecting the Viewer panel and

1. Select Correlation Bars.

2. From the left side, select Response→prc_thick_red_max.
3. choose to show the Correlation.

• This bar diagram shows the correlation coefficients of the maximum percent reduction (prc_thick_red_max) with all the variables and gives the 95% confidence intervals of the estimation at the meantime. Obviously, the variable YIELD is most correlated with the maximum percent thickness reduction.

•  We can verify this fact in different ways (also see Correlation Matrix and Scatter Plots).

By viewing the correlation matrix of variables against responses, we can also find out the most correlated variable to the maximum percent thickness reduction.

Open a new Viewer:

1. Restart the LS-OPT Viewer by clicking on the first icon on the menu bar.
2. Select Correlation Matrix.

3. Disselect Response for Row entities.
4. Disselect Variable for Column entities.
5. Now we obtain a matrix showing all the correlation coeffients between variables and responses. From the first column we find that the variable YIELD has the largest absolute value of the correlation coffient with the maximum percent thickness reduction, whick coincides with the fact we've seen before.

•  We can verify this fact in different ways (also see Correlation Bars and Scatter Plots).