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d. The effect of sealer plate temperature (x₁) and sealer plate clearance (x2) on soap wrapping machine quality (y, as % sealed properly) was studied. The following linear regression model was produced: ŷ= 65 +0.1 x₁ + 1.2 x2. If two machines have the same plate temperature, but their plate clearances differ by 1 unit, the % sealed properly is expected to differ by ________ units (fill in the blank). e. True or False? The variance of ŷ, should be the same for each different value of x₁. f. In a multiple regression what is the common effect of adding an irrelevant (non-significant) variable to the model? (Circle the correct answer.) i. SSE goes up. ii. Total variation of the response variable increases. iii. Parameter estimates become biased. iv. R² goes up. g. Consider a simple linear regression, = B+ Bx. In testing the null hypothesis of significance of regression Ho: P = 0 with a t-statistic, we find that t = 3. The value of the F- statistic in the ANOVA would be: i. 3 iii. 9 ii. 6 iv. None of the above, they are different statistics.

d. The effect of sealer plate temperature (x₁) and sealer plate clearance (x2) on soap wrapping machine quality (y, as % sealed properly) was studied. The following linear regression model was produced: ŷ= 65 +0.1 x₁ + 1.2 x2. If two machines have the same plate temperature, but their plate clearances differ by 1 unit, the % sealed properly is expected to differ by ________ units (fill in the blank). e. True or False? The variance of ŷ, should be the same for each different value of x₁. f. In a multiple regression what is the common effect of adding an irrelevant (non-significant) variable to the model? (Circle the correct answer.) i. SSE goes up. ii. Total variation of the response variable increases. iii. Parameter estimates become biased. iv. R² goes up. g. Consider a simple linear regression, = B+ Bx. In testing the null hypothesis of significance of regression Ho: P = 0 with a t-statistic, we find that t = 3. The value of the F- statistic in the ANOVA would be: i. 3 iii. 9 ii. 6 iv. None of the above, they are different statistics.

MATLAB: An Introduction with Applications
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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do d,e,f,g  please

Problem 2 (no need to show details of your work) Miscellaneous short-answer questions. Answer the following questions (circle the correct answer or fill in the blanks whenever asked). Please refer to the following information for questions (a)-(c). Normal Probability Plot Percent 99 90 50 10 ....you ool.49. -500 -250 6 Residual 250 500 Residual 500 250 -250 -500 · 0 1000 Versus Fits 2000 Fitted Value 3000 4000 Mean StDev N AD P-Value -2.96574E-14 a. True or False ? According to the Anderson-Darling test result, the normality assumption is violated, because the p-value = 0.410 > AD=0.364. i. SSE goes up. ii. Total variation of the response variable increases. iii. Parameter estimates become biased. iv. R² goes up. 271.4 23 0.364 0.410 b. True or False ? Since the Residual vs Fitted value plot depicts an obvious severe pattern, we reject that the error terms have a constant variance. c. True or False? We cannot tell whether the assumption E(&) = 0 is violated or not, because we do not have the residuals available to take their average. d. The effect of sealer plate temperature (x₁) and sealer plate clearance (x2) on soap wrapping machine quality (y, as % sealed properly) was studied. The following linear regression model was produced: y = 65 +0.1 x₁ + 1.2 x2. If two machines have the same plate temperature, but their plate clearances differ by 1 unit, the % sealed properly is expected to differ by (fill in the blank). units e. True or False? The variance of ŷ, should be the same for each different value of xi. f. In a multiple regression what is the common effect of adding an irrelevant (non-significant) variable to the model? (Circle the correct answer.) iii. 9 iv. None of the above, they are different statistics. y= g. Consider a simple linear regression, y = + ₁ x. In testing the null hypothesis of significance of regression Ho: P = 0 with a t-statistic, we find that t = 3. The value of the F- statistic in the ANOVA would be: i. 3 ii. 6 h. True or False? Based on census data for the 50 states in the United States, the correlation between the number of churches per state and the number of crimes per state was 0.85. A reasonable conclusion would be: The correlation is partly spurious because of the hidden variable of population size, that is to say, both the number of churches and the number of crimes are related to the population size.
Transcribed Image Text:Problem 2 (no need to show details of your work) Miscellaneous short-answer questions. Answer the following questions (circle the correct answer or fill in the blanks whenever asked). Please refer to the following information for questions (a)-(c). Normal Probability Plot Percent 99 90 50 10 ....you ool.49. -500 -250 6 Residual 250 500 Residual 500 250 -250 -500 · 0 1000 Versus Fits 2000 Fitted Value 3000 4000 Mean StDev N AD P-Value -2.96574E-14 a. True or False ? According to the Anderson-Darling test result, the normality assumption is violated, because the p-value = 0.410 > AD=0.364. i. SSE goes up. ii. Total variation of the response variable increases. iii. Parameter estimates become biased. iv. R² goes up. 271.4 23 0.364 0.410 b. True or False ? Since the Residual vs Fitted value plot depicts an obvious severe pattern, we reject that the error terms have a constant variance. c. True or False? We cannot tell whether the assumption E(&) = 0 is violated or not, because we do not have the residuals available to take their average. d. The effect of sealer plate temperature (x₁) and sealer plate clearance (x2) on soap wrapping machine quality (y, as % sealed properly) was studied. The following linear regression model was produced: y = 65 +0.1 x₁ + 1.2 x2. If two machines have the same plate temperature, but their plate clearances differ by 1 unit, the % sealed properly is expected to differ by (fill in the blank). units e. True or False? The variance of ŷ, should be the same for each different value of xi. f. In a multiple regression what is the common effect of adding an irrelevant (non-significant) variable to the model? (Circle the correct answer.) iii. 9 iv. None of the above, they are different statistics. y= g. Consider a simple linear regression, y = + ₁ x. In testing the null hypothesis of significance of regression Ho: P = 0 with a t-statistic, we find that t = 3. The value of the F- statistic in the ANOVA would be: i. 3 ii. 6 h. True or False? Based on census data for the 50 states in the United States, the correlation between the number of churches per state and the number of crimes per state was 0.85. A reasonable conclusion would be: The correlation is partly spurious because of the hidden variable of population size, that is to say, both the number of churches and the number of crimes are related to the population size.
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