Data Science FREE Data Science MCQ Question and Answers 3

Question 1

What does the bias-variance tradeoff describe in machine learning?

Accepted Answer

The balance between model simplicity and model complexity

Answer

The bias-variance tradeoff describes how increasing model complexity reduces bias but increases variance, and finding the right balance minimizes total error.

Question 2

Which sampling method ensures that each subgroup of a population is proportionally represented in the sample?

Accepted Answer

Stratified Sampling

Answer

Stratified sampling divides the population into homogeneous subgroups and samples proportionally from each to ensure representative coverage.

Question 3

What is the main advantage of using ensemble methods like bagging and boosting?

Accepted Answer

They reduce prediction error by combining multiple models

Answer

Ensemble methods aggregate predictions from multiple models to reduce variance or bias, generally producing more accurate and robust results.

Question 4

In natural language processing, what does TF-IDF stand for?

Accepted Answer

Term Frequency-Inverse Document Frequency

Answer

TF-IDF weights words by how frequently they appear in a document relative to how common they are across all documents in the corpus.

Question 5

Which type of data visualization is best suited for showing the distribution of a single continuous variable?

Accepted Answer

Histogram

Answer

Histograms display the frequency distribution of continuous data by grouping values into bins and showing their counts.

Data Science Practice Test

Data Science Practice Test

Data Science FREE Data Science MCQ Question and Answers 3