MS-DS Master of Data science FREE Master of Data Science Questions and Answers 2 — Questions and Answers
Question 1: Which regularization technique adds the absolute value of coefficients as a penalty term to the loss function?
- L1 (Lasso) regularization (Correct answer)
- L2 (Ridge) regularization
- Elastic Net regularization
- Dropout regularization
Correct answer: L1 (Lasso) regularization
L1 regularization, also called Lasso, penalizes the sum of absolute values of model coefficients, which can drive some coefficients to exactly zero.
Question 2: In a Master of Data Science program, what does the term 'curse of dimensionality' refer to?
- Data becomes sparse as the number of features increases (Correct answer)
- Models train faster with more variables
- Clustering algorithms improve with higher dimensions
- Feature selection becomes unnecessary in high-dimensional spaces
Correct answer: Data becomes sparse as the number of features increases
The curse of dimensionality describes how data points become increasingly sparse as the number of dimensions grows, making distance-based methods less effective.
Question 3: Which evaluation metric is most appropriate for a highly imbalanced binary classification dataset?
- Area Under the Precision-Recall Curve (AUPRC) (Correct answer)
- Accuracy
- Mean Squared Error
- R-squared
Correct answer: Area Under the Precision-Recall Curve (AUPRC)
AUPRC is preferred for imbalanced datasets because it focuses on the performance of the minority class without being inflated by correct majority class predictions.
Question 4: What is the primary purpose of cross-validation in a data science workflow?
- To estimate how well a model generalizes to unseen data (Correct answer)
- To increase the size of the training dataset
- To select the best programming language for analysis
- To reduce the number of features in the dataset
Correct answer: To estimate how well a model generalizes to unseen data
Cross-validation partitions data into multiple train-test splits to provide a more reliable estimate of model performance on new, unseen data.
Question 5: Which SQL operation is used to combine rows from two tables based on a related column?
- JOIN (Correct answer)
- UNION
- GROUP BY
- HAVING
Correct answer: JOIN
JOIN combines rows from two or more tables by matching values in a shared column, which is fundamental to relational database querying in data science.
Question 6: What does a p-value less than 0.05 conventionally indicate in hypothesis testing?
- The result is statistically significant and the null hypothesis is rejected (Correct answer)
- The null hypothesis is accepted
- The sample size is too small
- The effect size is large
Correct answer: The result is statistically significant and the null hypothesis is rejected
A p-value below 0.05 suggests there is less than a 5% probability of observing the result if the null hypothesis were true, leading to its rejection by convention.
MS-DS Master of Data science FREE Master of Data Science Questions and Answers 2
Which regularization technique adds the absolute value of coefficients as a penalty term to the loss function?