Homework Help is Here – Start Your Trial Now!
Math
Statistics
Q2 The following data is the pull strength of a wire bond in a semiconductor manufacturing process, wire length, and die height. Observation number Pull strength (Y) Wire length (X1) Die Height (X2) 1 9.95 2 50 24.45 110 3 31.75 11 120 4 35.00 10 550 5 25.02 295 6. 16.86 4 200 7 14. 375 8. 9.60 52 24.35 9. 100 10 27.50 8 300 a i) Fit a regression line using pull strength as Y and wire length as X. Use calculator to find the a and b to do so. ii) Find the coefficient of correlation in this regression model. Interpret its meaning. iii) Find the coefficient of determination in this regression model. Interpret its meaning. b) Now the rescarcher wanted to include one more variable, Die Height, in the regression model. Thus he obtaincd the following Excel output using both wire length and die height as independent variables: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.994525658 0.989081284 Standard Error 1.043637866 Observations 10 ANOVA of MS Significonce F Regression 2 690.65018 Residual 7.624259961 Total 698.27444 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.544350574 0.774648328 Wire length (X1) 2.215835576 0.101913929 Die Height (XQ) 0.014685417 0.002211316

Q2 The following data is the pull strength of a wire bond in a semiconductor manufacturing process, wire length, and die height. Observation number Pull strength (Y) Wire length (X1) Die Height (X2) 1 9.95 2 50 24.45 110 3 31.75 11 120 4 35.00 10 550 5 25.02 295 6. 16.86 4 200 7 14. 375 8. 9.60 52 24.35 9. 100 10 27.50 8 300 a i) Fit a regression line using pull strength as Y and wire length as X. Use calculator to find the a and b to do so. ii) Find the coefficient of correlation in this regression model. Interpret its meaning. iii) Find the coefficient of determination in this regression model. Interpret its meaning. b) Now the rescarcher wanted to include one more variable, Die Height, in the regression model. Thus he obtaincd the following Excel output using both wire length and die height as independent variables: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.994525658 0.989081284 Standard Error 1.043637866 Observations 10 ANOVA of MS Significonce F Regression 2 690.65018 Residual 7.624259961 Total 698.27444 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.544350574 0.774648328 Wire length (X1) 2.215835576 0.101913929 Die Height (XQ) 0.014685417 0.002211316

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 91E
See similar textbooks
icon
Related questions
Question
Q2 The following data is the pull strength of a wire bond in a semiconductor manufacturing process, wire length, and die height. Observation number Pull strength (Y) Wire length (X1) Die Height (X2) 1 9.95 2 50 24.45 110 3 31.75 11 120 4 35.00 10 550 5 25.02 295 6. 16.86 4 200 7 14. 375 8. 9.60 52 24.35 9. 100 10 27.50 8 300 a i) Fit a regression line using pull strength as Y and wire length as X. Use calculator to find the a and b to do so. ii) Find the coefficient of correlation in this regression model. Interpret its meaning. iii) Find the coefficient of determination in this regression model. Interpret its meaning. b) Now the rescarcher wanted to include one more variable, Die Height, in the regression model. Thus he obtaincd the following Excel output using both wire length and die height as independent variables: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.994525658 0.989081284 Standard Error 1.043637866 Observations 10 ANOVA of MS Significonce F Regression 2 690.65018 Residual 7.624259961 Total 698.27444 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.544350574 0.774648328 Wire length (X1) 2.215835576 0.101913929 Die Height (XQ) 0.014685417 0.002211316
Transcribed Image Text:Q2 The following data is the pull strength of a wire bond in a semiconductor manufacturing process, wire length, and die height. Observation number Pull strength (Y) Wire length (X1) Die Height (X2) 1 9.95 2 50 24.45 110 3 31.75 11 120 4 35.00 10 550 5 25.02 295 6. 16.86 4 200 7 14. 375 8. 9.60 52 24.35 9. 100 10 27.50 8 300 a i) Fit a regression line using pull strength as Y and wire length as X. Use calculator to find the a and b to do so. ii) Find the coefficient of correlation in this regression model. Interpret its meaning. iii) Find the coefficient of determination in this regression model. Interpret its meaning. b) Now the rescarcher wanted to include one more variable, Die Height, in the regression model. Thus he obtaincd the following Excel output using both wire length and die height as independent variables: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.994525658 0.989081284 Standard Error 1.043637866 Observations 10 ANOVA of MS Significonce F Regression 2 690.65018 Residual 7.624259961 Total 698.27444 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.544350574 0.774648328 Wire length (X1) 2.215835576 0.101913929 Die Height (XQ) 0.014685417 0.002211316
i) From the Excel output, fit a regression model using wire length as X1 and die height as X2. ii) Interpret the coefficient of X1 and X2. iii) Calculate the adjusted R square for this regression model. iv) Test the overall significance of this regression model at a = 0.05 v) Test the significance of XI (wire length) and X2 (die height) respectively in the regression model at a = 0.05 vi) Estimate the pull strength of a wire bond with wire length is 3 and die height is 250. c) Comparing regression model in (a) and (b), which regression model should be used by the researcher?
Transcribed Image Text:i) From the Excel output, fit a regression model using wire length as X1 and die height as X2. ii) Interpret the coefficient of X1 and X2. iii) Calculate the adjusted R square for this regression model. iv) Test the overall significance of this regression model at a = 0.05 v) Test the significance of XI (wire length) and X2 (die height) respectively in the regression model at a = 0.05 vi) Estimate the pull strength of a wire bond with wire length is 3 and die height is 250. c) Comparing regression model in (a) and (b), which regression model should be used by the researcher?
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps with 3 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:
9781133382119
Author:
Swokowski
Publisher:
Cengage
College Algebra
College Algebra
Algebra
ISBN:
9781337282291
Author:
Ron Larson
Publisher:
Cengage Learning
Trigonometry (MindTap Course List)
Trigonometry (MindTap Course List)
Trigonometry
ISBN:
9781337278461
Author:
Ron Larson
Publisher:
Cengage Learning
Functions and Change: A Modeling Approach to Coll…
Functions and Change: A Modeling Approach to Coll…
Algebra
ISBN:
9781337111348
Author:
Bruce Crauder, Benny Evans, Alan Noell
Publisher:
Cengage Learning
SEE MORE TEXTBOOKS