Virtual Labs

What type of problem does Linear Regression solve?

a: Classification Explanation

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b: Regression Explanation

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c: Clustering Explanation

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d: Dimensionality Reduction Explanation

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In the equation Y = β₀ + β₁X, what represents the intercept?

a: Y Explanation

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b: β₁ Explanation

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c: X Explanation

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d: β₀ Explanation

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Which metric measures the average squared difference between actual and predicted values?

a: MAE Explanation

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b: RMSE Explanation

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c: MSE Explanation

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d: R² Explanation

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What is the range of the R² score?

a: 0 to 1 (usually) Explanation

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b: −1 to 1 Explanation

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c: 0 to infinity Explanation

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d: −infinity to 1 Explanation

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Which library in Python is commonly used for implementing Linear Regression models?

a: NumPy Explanation

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b: Pandas Explanation

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c: Scikit-learn Explanation

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d: Matplotlib Explanation

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Prior to training, why do we split data into training and testing sets?

a: To make the dataset smaller Explanation

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b: To evaluate model performance on unseen data Explanation

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c: To remove outliers Explanation

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d: To balance the classes Explanation

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What must be done to categorical variables before using them in Linear Regression?

a: Remove them Explanation

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b: Normalize them Explanation

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c: Encode them into numbers Explanation

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d: Leave them as text Explanation

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"Homoscedasticity" refers to:

a: Constant variance of residuals Explanation

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b: Linear relationship between variables Explanation

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c: Independence of errors Explanation

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d: Normal distribution of errors Explanation

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If the correlation coefficient (r) is 0.9, what does it indicate?

a: Strong negative linear relationship Explanation

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b: Weak positive linear relationship Explanation

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c: Strong positive linear relationship Explanation

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d: No relationship Explanation

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What is the purpose of the fit() method in Scikit-learn?

a: To make predictions Explanation

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b: To train the model Explanation

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c: To evaluate the model Explanation

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d: To load data Explanation

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