40. What is the residual for X1 = 14.620 x2 = 226.00 x3 = 7.000 with y = 128.40? (a) -6.7838 (b) 1.1423 (c) none (d) -0.9037 (e) 2.2931

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40. What is the residual for X1 = 14.620 x2 = 226.00 x3 = 7.000 with y = 128.40? (a) -6.7838 (b) 1.1423 (c) none (d) -0.9037 (e) 2.2931
An engineer ata semiconductor company wants to model the relationship between the device HFE (y) and three parameters: Emitter-RS (x-), Base-RS (x2 ), and Emitter-to- Base RS (xa). Twenty samples were evaluated where the following table is the
incomplete Linear Regression Analysis generated using Microsoft Excel
SUMMARY OUTPUT
Regression Statistics
R Square
Adjusted R
Square
Observations
20
ANOVA
df
MS
Feritical
Regression
30531.5023
Residual
Total
30725.2271
Coefficients Standard Error
t Stat
P-value
Intercept
47.1740
49.5815
0.9514
0.35553
Emitter-RS (x1)
-9.7352
3.6916
-2.6371
0.01793
Base-RS (x2)
0.4283
0.2239
1.9126
0.07388
E-B-RS (x3)
18.2375
1.3118
13.9026
0.00000
Transcribed Image Text:An engineer ata semiconductor company wants to model the relationship between the device HFE (y) and three parameters: Emitter-RS (x-), Base-RS (x2 ), and Emitter-to- Base RS (xa). Twenty samples were evaluated where the following table is the incomplete Linear Regression Analysis generated using Microsoft Excel SUMMARY OUTPUT Regression Statistics R Square Adjusted R Square Observations 20 ANOVA df MS Feritical Regression 30531.5023 Residual Total 30725.2271 Coefficients Standard Error t Stat P-value Intercept 47.1740 49.5815 0.9514 0.35553 Emitter-RS (x1) -9.7352 3.6916 -2.6371 0.01793 Base-RS (x2) 0.4283 0.2239 1.9126 0.07388 E-B-RS (x3) 18.2375 1.3118 13.9026 0.00000
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