Isye 6414 Units 1 - 3 Review

78 Questions | Total Attempts: 90

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Isye 6414 Units 1 - 3 Review


Questions and Answers
  • 1. 
    Under the normality assumption, the estimator for β1 is a linear combination of normally distributed random variables.
    • A. 

      True

    • B. 

      False

  • 2. 
     In the regression model, the variable of interest for study is the response variable.
    • A. 

      True

    • B. 

      False

  • 3. 
    The constant variance is diagnos=ted using the quantile-quantile normal plot.
    • A. 

      True

    • B. 

      False

  • 4. 
     β1^ is an unbiased estimator for β0.
    • A. 

      True

    • B. 

      False

  • 5. 
    The estimator σ^2 is a fixed variable.
    • A. 

      True

    • B. 

      False

  • 6. 
    Only the log-transformation of the response variable can be used when the normality assumption does not hold.
    • A. 

      True

    • B. 

      False

  • 7. 
    The only assumptions for a linear regression model are linearity, constant variance, and normality.
    • A. 

      True

    • B. 

      False

  • 8. 
    A negative value of β1 is consistent with a direct relationship between x and Y.
    • A. 

      True

    • B. 

      False

  • 9. 
    In the simple linear regression model, we lose three degrees of freedom because of the estimation of the three model parameters, β0, β1, and σ^2.
    • A. 

      True

    • B. 

      False

  • 10. 
    The regression coefficient is used to measure the linear dependence between two variables.
    • A. 

      True

    • B. 

      False

  • 11. 
    If the constant variance assumption in ANOVA does not hold, the inference on the equality of the means will not be reliable.
    • A. 

      True

    • B. 

      False

  • 12. 
    If one confidence interval in the pairwise comparison includes zero, we conclude that the two means are plausibly equal.
    • A. 

      True

    • B. 

      False

  • 13. 
    The mean sum of square errors in ANOVA measures variability within groups.
    • A. 

      True

    • B. 

      False

  • 14. 
    The linear regression model with a qualitative predicting variable with k levels/classes will have k+1 parameters to estimate.
    • A. 

      True

    • B. 

      False

  • 15. 
    If one confidence interval in the pairwise comparison includes only positive values, we conclude that the difference in means is statistically significantly positive.
    • A. 

      True

    • B. 

      False

  • 16. 
    The number of degrees of freedom of the χ2 (chi-square) distribution for the variance estimator is N−k+1 where k is the number of samples.
    • A. 

      True

    • B. 

      False

  • 17. 
    For assessing the normality assumption of the ANOVA model, we can use the quantile-quantile normal plot and the historgram of the residuals.
    • A. 

      True

    • B. 

      False

  • 18. 
    We can assess the assumption of constant-variance by plotting the residuals against fitted values.
    • A. 

      True

    • B. 

      False

  • 19. 
    The ANOVA is a linear regression model with two qualitative predicting variables.
    • A. 

      True

    • B. 

      False

  • 20. 
    The sampling distribution for the variance estimator in ANOVA is χ2 (chi-square) regardless of the assumption of the data.
    • A. 

      True

    • B. 

      False

  • 21. 
    In a multiple linear regression model with 6 predicting variables but without intercept, there are 7 parameters to estimate.
    • A. 

      True

    • B. 

      False

  • 22. 
    The only objective of multiple linear regression is prediction.
    • A. 

      True

    • B. 

      False

  • 23. 
    We can make causal inference in observational studies.
    • A. 

      True

    • B. 

      False

  • 24. 
    In order to make statistical inference on the regression coefficients, we need to estimate the variance of the error terms.
    • A. 

      True

    • B. 

      False

  • 25. 
    We cannot estimate a multiple linear regression model if the predicting variables are linearly dependent.
    • A. 

      True

    • B. 

      False

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