Linear Regression DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is a common alternative to linear regression when the relationship between the dependent and independent variables is curved?

   • AK-means clustering
   • BLogistic regression
   • CPrincipal component analysis
   • DPolynomial regression
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2. 2foundation · easy

   How are categorical variables typically incorporated into a linear regression model?

   • ABy using the categorical variable as the dependent variable
   • BBy creating dummy variables (0/1 indicators) for each category except one reference category
   • CBy assigning numerical codes like 1, 2, 3 directly to the categories
   • DBy removing the categorical variable from the model
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4. 3expert · hard

   A data scientist fits a linear regression model with 5 predictors. The overall F-test is significant (p < 0.05), but none of the individual t-tests are significant (all p > 0.05). The data scientist suspects multicollinearity. Which diagnostic should she use to confirm this?

   • AQ-Q plot
   • BR-squared
   • CVariance Inflation Factor (VIF)
   • DResidual plot
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5. 4foundation · easy

   What is multicollinearity in linear regression?

   • ANon-constant variance of residuals
   • BThe presence of outliers in the data
   • CHigh correlation between the dependent and independent variables
   • DHigh correlation between independent variables
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6. 5foundation · easy

   What does the F-test in linear regression assess?

   • AThe overall significance of the regression model
   • BThe presence of multicollinearity
   • CThe significance of a single coefficient
   • DThe normality of the residuals
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