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Plasma etching is essential to the fine-line pattern transfer in current semicon

ID: 3225848 • Letter: P

Question

Plasma etching is essential to the fine-line pattern transfer in current semiconductor processes. An article gives the accompanying data (read from a graph) on chlorine flow (x, in SCCM) through a nozzle used in the etching mechanism and etch rate (y, in 100 A/min).

x 1.5 1.5 2.0 2.5 2.5 3.0 3.5 3.5 4.0

y 22.5 24.5 25.0 31.0 33.5 39.0 40.5 46.5 49.0

(A)Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)

(B)Estimate the true average change in etch rate associated with a 1-SCCM increase in flow rate using a 95% confidence interval. (Round your answers to three decimal places.)

(C)Calculate a 95% CI for Y · 3.0,the true average etch rate when flow = 3.0. (Round your answers to three decimal places.)

(D)Calculate a 95% PI for a single future observation on etch rate to be made when flow = 3.0. (Round your answers to three decimal places.)

Explanation / Answer

Using Minitab:

Regression Analysis: y versus x

Method

Rows unused 4


Analysis of Variance

Source         DF Adj SS   Adj MS F-Value P-Value
Regression      1 723.64 723.642   147.91    0.000
x             1 723.64 723.642   147.91    0.000
Error           7   34.25    4.892
Lack-of-Fit   4   11.12    2.780     0.36    0.825
Pure Error    3   23.13    7.708
Total           8 757.89


Model Summary

      S    R-sq R-sq(adj) R-sq(pred)
2.21188 95.48%     94.84%      92.60%


Coefficients

Term        Coef SE Coef T-Value P-Value   VIF
Constant    6.47     2.43     2.67    0.032
x         10.551    0.868    12.16    0.000 1.00


Regression Equation

y = 6.47 + 10.551 x

(A)Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.)

Answer:

From above output: test statistic: 2.67   P-value 0.032

(B)Estimate the true average change in etch rate associated with a 1-SCCM increase in flow rate using a 95% confidence interval.

Prediction for y

Regression Equation

y = 6.47 + 10.551 x


Variable Setting
x               1


    Fit   SE Fit        95% CI              95% PI
17.0256 1.62307 (13.1877, 20.8636) (10.5383, 23.5130)

C and D :

Prediction for y

Regression Equation

y = 6.47 + 10.551 x


Variable Setting
x               3


    Fit    SE Fit        95% CI              95% PI
38.1282 0.791979 (36.2555, 40.0009) (32.5728, 43.6836)

Hope this will be helpful. Thanks and god Bless You :-)