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Free CFA Quantitative Methods Practice Questions & Answers

1,200 exam-style Quantitative Methods questions. Pick your answer, hit Check answer, and see the worked solution — free to start, no signup.

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Question 601
A cluster that contains points with very different densities and shapes may be better handled by:
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Question 602
The main advantage of DBSCAN over K‑means is that DBSCAN:
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Question 603
Adjusted (R^2) is used instead of (R^2) because:
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Question 604
A model that fits the historical data extremely well but performs poorly on new data is likely:
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Question 605
A predicted probability from a logistic regression of 0.8 for default means:
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Question 606
Supervised learning involves:
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Question 607
Overfitting in machine learning means:
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Question 608
A common way to check for overfitting is to:
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Question 609
Penalized regression methods (like Lasso or Ridge) are used to:
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Question 610
A decision tree model:
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Question 611
A random forest is:
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Question 612
In supervised learning, a “training set” is:
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Question 613
A “test set” is used to:
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Question 614
Cross-validation is a technique to:
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Question 615
A neural network consists of:
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Question 616
Deep learning refers to neural networks with:
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Question 617
Feature selection aims to:
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Question 618
If two independent variables are uncorrelated, this means:
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Question 619
A model with too many variables may show:
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Question 620
A model with too few variables may show:
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Question 621
A model that fits the training data extremely well but fails on new data is:
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Question 622
A key difference between supervised and unsupervised learning is:
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Question 623
A model that memorizes training data but fails on new data is:
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Question 624
A validation set is used to:
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Question 625
A test set is used to:
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Question 626
Regularization methods help reduce:
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Question 627
A decision tree may overfit because:
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Question 628
A random forest reduces overfitting by:
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Question 629
Feature engineering involves:
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Question 630
ARCH behavior implies that variance is:
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