Data Science Miscellaneous MCQ Questions and Answers | Data Science MCQs

A. Chi-squared test

B. ANOVA

C. t-test

D. Regression analysis

A. Creating new features

B. Filling in missing values in a dataset

C. Encoding categorical data

D. Creating new features

A. Data preprocessing

B. Model evaluation

C. Feature selection

D. Hyperparameter tuning

A. To visualize data

B. To build predictive models

C. To summarize data

D. To display the counts of true positive, true negative, false positive, and false negative predictions

A. To reduce the number of features while preserving important information

B. To add more features to the dataset

C. To normalize data

D. To visualize data

A. Encode, Tokenize, Leverage

B. Estimate, Test, Label

C. Explore, Train, Learn

D. Extract, Transform, Load

A. Text vectorization

B. Feature scaling

C. Part-of-speech tagging

D. One-hot encoding

A. Exploratory data analysis

B. Bootstrap resampling

C. Data preprocessing

D. Exploratory data analysis

A. To collect more data

B. To build predictive models

C. To assess a model's performance on unseen data by splitting the data into multiple subsets

D. To create visualizations

A. To perform regression analysis

B. To cluster data into groups

C. To reduce dimensionality

D. To classify data points based on the majority class among their K nearest neighbors