FRM 2026 Part I Quantitative Analysis Data Analysis Free Quiz 2

Practice FRM 2026 Part I Quantitative Analysis MCQs from Data Analysis. Get instant results with Explanation.

General10 MCQs

1. What is classification in data analysis?

A. Classification assigns data to predefined categoriesB. Classification is an unsupervised techniqueC. Classification is used for grouping similar dataD. Classification is the same as clustering

2. What is logistic regression used for?

A. Logistic regression is used for continuous outcomesB. Logistic regression is an unsupervised algorithmC. Logistic regression assumes linearity in the logitD. Logistic regression models the probability of a binary outcome using a logistic function

3. What is a decision tree?

A. Decision trees are unsupervisedB. Decision trees partition data based on feature values for predictionC. Decision trees are not interpretableD. Decision trees always overfit

4. What is a random forest?

A. Random forest builds a single decision treeB. Random forest is a supervised learning method that builds one treeC. Random forest builds many decision trees and combines their predictionsD. Random forest is an unsupervised method

5. What is boosting in machine learning?

A. Boosting builds models sequentially, correcting errors of previous modelsB. Boosting builds models in parallelC. Boosting is the same as baggingD. Boosting is an unsupervised method

General10 MCQs

6. What is overfitting in machine learning?

A. Overfitting means the model generalizes wellB. Overfitting is not a problem in machine learningC. Overfitting occurs when a model underfits the dataD. Overfitting occurs when a model captures noise and fails to generalize

7. What is cross-validation?

A. Cross-validation is used only for trainingB. Cross-validation splits data into training and validation sets to assess model performanceC. Cross-validation is not used in practiceD. Cross-validation is a feature selection method

8. What is feature selection?

A. Feature selection is not importantB. Feature selection increases model complexityC. Feature selection selects a subset of variables to improve model performanceD. Feature selection is the same as feature extraction

9. What is regularization in machine learning?

A. Regularization adds a penalty to the loss function to prevent overfittingB. Regularization is used to increase model complexityC. Regularization is the same as cross-validationD. Regularization is not used in machine learning

10. What is data mining?

A. Data mining is only about data collectionB. Data mining is the same as data visualizationC. Data mining is not used in businessD. Data mining discovers patterns and knowledge from large datasets

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