39. What is the mean square regression?(a) 193.7248(b) none(c) 10,177.1674(d) 12.1078(e) 840.5463 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 theincomplete Linear Regression Analysis generated using Microsoft ExcelSUMMARY OUTPUTRegression StatisticsR SquareAdjusted RSquareObservations20ANOVAdfMSFeriticalRegression30531.5023ResidualTotal30725.2271Coefficients Standard Errort StatP-valueIntercept47.174049.58150.95140.35553Emitter-RS (x1)-9.73523.6916-2.63710.01793Base-RS (x2)0.42830.22391.91260.07388E-B-RS (x3)18.23751.311813.90260.00000

Formula : MSR = SSR/df_Regression

Answered: An engineer at a semiconductor company…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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39. What is the mean square regression? (a) 193.7248 (b) none (c) 10,177.1674 (d) 12.1078 (e) 840.5463

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

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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