ISYE 6414-REGRESSION ANALYSIS MODULES 1-4 ALL 250+ QUESTIONS WITH CORRECT DETAILED ANSWERS LATEST UPDATE THIS YEAR - JUST RELEASED.

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ISYE 6414-REGRESSION ANALYSIS MODULES 1-4 ALL
250+ QUESTIONS WITH CORRECT DETAILED ANSWERS
LATEST UPDATE THIS YEAR - JUST RELEASED


ISYE 6414 Regression Modules 1-2

QUESTION: We detect departure from the assumption of constant variance - ANSWER-when
the residuals vs fitted values are larger in the ends but smaller in the middle.




QUESTION: If a departure from normality is detected, we transform the predicting variable to
improve upon the normality assumption. - ANSWER-False




QUESTION: If a departure from the independence assumption is detected, we transform the
response variable to improve upon the independence assumption. - ANSWER-False




QUESTION: The Box-Cox transformation is commonly used to improve upon the linearity
assumption. - ANSWER-False




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QUESTION: In evaluating a simple linear model - ANSWER-there is a direct relationship between
the coefficient of determination and the correlation between the predicting and response
variables.




QUESTION: Goodness of fit assessment is done by - ANSWER-residual analysis




QUESTION: R-squared (the coefficient of variation) is interpreted as - ANSWER-the percentage
of variability in the response variable explained by the model.




QUESTION: The parameters of ANOVA are - ANSWER-the k sample means and the population
variance.




QUESTION: The pooled variance estimator is - ANSWER-the sample variance estimator
assuming equal variances.




QUESTION: In ANOVA, the mean sum of squares divided by N-1 is - ANSWER-the sample
variance estimator assuming equal means and equal variances.




QUESTION: MSE measures - ANSWER-the within-treatment variability.




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QUESTION: MSSTr measures - ANSWER-the between treatment variability.




QUESTION: If we reject the test of equal means, we conclude that at least one pair of means are
different. - ANSWER-True




QUESTION: If we do not reject the test of equal means, we conclude that means are definitely
all equal. - ANSWER-False

Assuming that the data are normally distributed, under the simple linear model, the estimated
variance has the following sampling distribution: - ANSWER-Chi-squared with n-2 degrees of
freedom.




QUESTION: The fitted values are defined as? - ANSWER-The regression line with parameters
replaced with the estimated regression coefficients.




QUESTION: The estimators fo the linear regression model are derived by? - ANSWER-Minimizing
the sum of squared differences between the observed and expected values of the response
variable.




QUESTION: The estimators for the regression coefficients are: - ANSWER-Unbiased regardless of
the distribution of the data.



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QUESTION: The assumption of normality: - ANSWER-Is needed for the sampling distribution of
the estimators of the regression coefficients and hence for inference.




QUESTION: The estimated versus predicted regression line for a given x* - ANSWER-have the
same expectation.




QUESTION: The variability in the prediction comes from - ANSWER-the variability due to a new
measurement and due to estimation.




QUESTION: Residual analysis can only be used to assess uncorrelated errors. - ANSWER-False




QUESTION: Independence assumption can be assess using the normal probability plot. -
ANSWER-False




QUESTION: Independence assumption can be assessed using the residuals vs fitted values. -
ANSWER-False




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