# Question

A 2 4-1 design has been used to investigate the effect of four factors on the resistivity of a silicon wafer. The data from this experiment are shown in Table 13E.4.

Enter the factor levels and resist data into a Minitab worksheet, including a column indicating whether a run is a center point run (1 = not center point, 0 = center point). Then define the experiment using Stat > DOE > Factorial > Define Custom Factorial Design. The design and data are in the Minitab worksheet Ex13-17.MTW.

(a) Estimate the factor effects. Plot the effect estimates on a normal probability scale.

(b) Identify a tentative model for this process. Fit the model and test for curvature.

(c) Plot the residuals from the model in part (b) versus the predicted resistivity. Is there any indication on this plot of model inadequacy?

(d) Construct a normal probability plot of the residuals. Is there any reason to doubt the validity of the normality assumption?

Enter the factor levels and resist data into a Minitab worksheet, including a column indicating whether a run is a center point run (1 = not center point, 0 = center point). Then define the experiment using Stat > DOE > Factorial > Define Custom Factorial Design. The design and data are in the Minitab worksheet Ex13-17.MTW.

(a) Estimate the factor effects. Plot the effect estimates on a normal probability scale.

(b) Identify a tentative model for this process. Fit the model and test for curvature.

(c) Plot the residuals from the model in part (b) versus the predicted resistivity. Is there any indication on this plot of model inadequacy?

(d) Construct a normal probability plot of the residuals. Is there any reason to doubt the validity of the normality assumption?

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