Use the information below to answer the PULL STRENGTH questions that follow. Data from “Applied Statistics and Probability for Engineers", Fourth Edition, by Douglas C. Montgomery & George C. Runger. The Excel multiple regression output below is for predicting pull strength from wire length and die height. MULTIPLE REGRESSION EXCEL OUTPUT (PULL STRENGTH) SUMMARY OUTPUT Regression Statistics Multiple R 0.990523843 R Square 0.981137483 Adjusted R Square 0.979422709 Standard Error 2.288046833 Observations 25 ANOVA df SS MS Significance F Regression 5990.771221 2995.385611 572.1671503 1.07546E-19 Residual 22 115.1734828 5.235158308 Total 24 6105.944704 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 2.263791434 1.060066238 2.135518851 0.04409945 0.065348623 4.462234246 Wire Length 2.744269643 0.093523844 29.34299438 3.90691E-19 2.550313062 2.938226225 Die Height 0.012527811 0.002798419 4.476746229 0.000188266 0.006724246 0.018331377

Use the information below to answer the PULL STRENGTH questions that follow. Data from “Applied Statistics and Probability for Engineers", Fourth Edition, by Douglas C. Montgomery & George C. Runger. The Excel multiple regression output below is for predicting pull strength from wire length and die height. MULTIPLE REGRESSION EXCEL OUTPUT (PULL STRENGTH) SUMMARY OUTPUT Regression Statistics Multiple R 0.990523843 R Square 0.981137483 Adjusted R Square 0.979422709 Standard Error 2.288046833 Observations 25 ANOVA df SS MS Significance F Regression 5990.771221 2995.385611 572.1671503 1.07546E-19 Residual 22 115.1734828 5.235158308 Total 24 6105.944704 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 2.263791434 1.060066238 2.135518851 0.04409945 0.065348623 4.462234246 Wire Length 2.744269643 0.093523844 29.34299438 3.90691E-19 2.550313062 2.938226225 Die Height 0.012527811 0.002798419 4.476746229 0.000188266 0.006724246 0.018331377

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

PULL STRENGTH
Which of the following is a correct interpretation of the confidence interval
for the intercept?
The average pull strength is predicted to be between 0.065 and 4.463 units when
both wire length and die height are zero units.
O The average pull strength is predicted to increase by between 0.065 and 4.463
units when both wire length and die height are kept constant.
The average pull strength is predicted to be between 0.065 and 4.463 units when
both wire length and die height are kept constant.
The average pull strength is predicted to increase by between 0.065 and 4.463
units when both wire length and die height are increased by one unit.
The average pull strength is predicted increase by between 0.065 and 4.463 units
when both wire length and die height are zero units.
The average pull strength is predicted to be between 0.065 and 4.463 units when
both wire length and die height are increased by one unit.

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