Isye 6414 Units 1 - 3 Review
78 Questions
| Total Attempts: 148
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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