This procedure can generate three types of factorial plots to help you visualize the effects, namely the main effects, interactions and cube. They can be used to help you visualise how the response relates to one or more factors.
1. Choose ProcessMA > DOE > Factorial Plots.
2. Check Plot Main Effects, if you want to generate the Main Effects Plot.
· In Response, select the column containing the response data.
· In Factors, select the columns contain factor levels.
3. Check Plot Interactions, if you want to generate the Interactions Plot.
· In Response, select the column containing the response data.
· In Factors, select the columns contain factor levels.
4. Check Plot Cube, if you want to generate the Cube Plot.
· In Response, select the column containing the response data.
· In Factors, select the columns contain factor levels.
5. Click OK.
Note To select a column of data into a textbox, double-click on any of the column names shown in the list on the left of the dialog box while in the textbox.
You want to investigate how temperature, intensity of light and type of catalyst affect the growth of organisms. You created a full factorial design for three factors and with three replicates. You ran the experiments and recorded the data. You want to use Factorial Plots to visualise the effects.
1. Open worksheet ProcessMA > Tools > Data Files > DOE.xls.
2. Choose ProcessMA > DOE > Factorial Plots.
3. In Response, select H – Growth.
4. Check Plot Main Effects.
· In Response, select H – Growth.
· In Factors, select E – Temp, F – Light, G – Catalyst.
5. Check Plot Interactions.
· In Response, select H – Growth.
· In Factors, select E – Temp, F – Light, G – Catalyst.
6. Check Plot Cube.
· In Response, select H – Growth.
· In Factors, select E – Temp, F – Light, G – Catalyst.
7. Click OK.
Interpretation
The Main Effects Plot suggests that growth increases for the high levels of all three factors and the Catalyst effects are small. From the Interactions Plot, there seems to be no significant interactions among factors. The Cube Plot shows the mean response value for various combinations of factor levels.