MCQsExam.com

Linear Regression

Which metric is NOT affected by multicollinearity?

1. A-R²
2. B-SER
3. C-Adjusted R²
4. D-VIF
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

Which plot detects heteroskedasticity in linear regression?

1. A-Q-Q
2. B-Residual vs Fitted
3. C-Scale-Location
4. D-DFBETAS
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

Which assumption makes OLS unbiased?

1. A-Normality
2. B-Heteroskedasticity
3. C-Zero conditional mean
4. D-No multicollinearity
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What does linear regression model?

1. A-Linear relationship between variables
2. B-Non-linear relationship
3. C-Categorical data
4. D-Time series data
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What is the purpose of regularization techniques in Linear Regression?

1. A-To increase bias and reduce variance
2. B-To decrease bias and increase variance
3. C-To penalize large coefficients and reduce overfitting
4. D-To penalize small coefficients and increase overfitting
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

Which of the following is NOT a method to handle overfitting in Linear Regression?

1. A-Ridge Regression
2. B-Lasso Regression
3. C-Elastic Net Regression
4. D-Decision Tree Regression
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What is multicollinearity in the context of Linear Regression?

1. A-The presence of outliers in the data
2. B-The relationship between the independent and dependent variables is not linear
3. C-The presence of strong correlations among independent variables
4. D-The assumption that the residuals are normally distributed
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

In a simple Linear Regression model with one independent variable, what does the slope coefficient represent?

1. A-The intercept of the regression line
2. B-The change in the dependent variable for a one-unit change in the independent variable
3. C-The average value of the dependent variable
4. D-The standard deviation of the dependent variable
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What does the coefficient of determination (R-squared) measure in Linear Regression?

1. A-The strength of the relationship between independent and dependent variables
2. B-The slope of the regression line
3. C-The proportion of variance in the dependent variable explained by the independent variables
4. D-The intercept of the regression line
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

Which algorithm is commonly used to optimize the parameters in Linear Regression?

1. A-Gradient Descent
2. B-K-means
3. C-Decision Tree
4. D-Support Vector Machine (SVM)
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What is the loss function typically used in Linear Regression?

1. A-Cross-entropy loss
2. B-Mean absolute error (MAE)
3. C-Mean squared error (MSE)
4. D-Hinge loss
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What does the term "line of best fit" refer to in Linear Regression?

1. A-The line that passes through the origin
2. B-The line with the maximum slope
3. C-The line that minimizes the sum of squared errors
4. D-The line that intersects the most data points
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

Which of the following is a assumption of Linear Regression?

1. A-The relationship between the independent and dependent variables is linear
2. B-The data is normally distributed
3. C-The data contains no outliers
4. D-The number of features is greater than the number of samples
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ

What is the primary objective of Linear Regression in machine learning?

1. A-Classification
2. B-Clustering
3. C-Prediction
4. D-Feature extraction
5. MCQ By: MCQSEXAM
6. Data Science / Linear Regression
7. More about this MCQ