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Exam (elaborations)

ISYE 6414 Midterm Prep Questions and Answers

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  • ISYE 6414
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  • ISYE 6414

We can assess the constant variance assumption in linear regression by plotting the residuals vs. fitted values. - Answer️️ -True If one confidence interval in the pairwise comparison in ANOVA includes zero, we conclude that the two corresponding means are plausibly equal. - Answer️️ -Tr...

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  • September 13, 2024
  • 10
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • ISYE 6414
  • ISYE 6414
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SophiaBennett
ISYE 6414 Midterm Prep Questions and Answers




©SOPHIABENNETT 9/2/24 2024/2025 ACADEMIC YEAR

, We can assess the constant variance assumption in linear regression by plotting the

residuals vs. fitted values. - Answer✔️✔️-True

If one confidence interval in the pairwise comparison in ANOVA includes zero, we

conclude that the two corresponding means are plausibly equal. - Answer✔️✔️-True

The assumption of normality is not required in linear regression to make inference on

the regression coefficients. - Answer✔️✔️-False (Explanation: is required)

We cannot estimate a multiple linear regression model if the predicting variables are

linearly independent. - Answer✔️✔️-False (Explanation: linearly dependent)

If a predicting variable is a categorical variable with 5 categories in a linear regression

model without intercept, we will include 5 dummy variables. - Answer✔️✔️-True

If the normality assumption does not hold for a regression, we may use a transformation

on the response variable. - Answer✔️✔️-True

The prediction of the response variable has higher uncertainty than the estimation of the

mean response. - Answer✔️✔️-True

Statistical inference for linear regression under normality relies on large sample size. -

Answer✔️✔️-False (Explanation: small sample size is fine)

A nonlinear relationship between the response variable and a predicting variable cannot

be modeled using regression. - Answer✔️✔️-False (Explanation: Nonlinear relationships

can often be modeled using linear regression by including polynomial terms of the

predicting variable, for example.)

Assumption of normality in linear regression is required for confidence intervals,

prediction intervals, and hypothesis testing. - Answer✔️✔️-True


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