Free Questions › CFA › Quantitative Methods

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.

100% free · No login to start

Question 361

The elbow method helps identify:

Select an option first.

Question 362

A cluster with very high internal variance suggests:

Select an option first.

Question 363

A cluster with very low internal variance suggests:

Select an option first.

Question 364

K‑means++ improves K‑means by:

Select an option first.

Question 365

A cluster that contains only one point in K‑means likely indicates:

Select an option first.

Get the full CFA question bank — free

Drop your email and we'll send you fresh CFA practice questions, fully worked solutions and exam-deadline reminders. No spam — unsubscribe in one click.

Want to save your score and take a full mock exam? Create a free account →

Question 366

In hierarchical clustering, the choice of linkage method affects:

Select an option first.

Question 367

Complete linkage tends to produce clusters that are:

Select an option first.

Question 368

Single linkage tends to produce clusters that are:

Select an option first.

Question 369

Average linkage tends to produce clusters that are:

Select an option first.

Question 370

Clusters that are very close together but internally compact may indicate:

Select an option first.

Question 371

Clusters that are extremely compact but very close to each other may indicate:

Select an option first.

Question 372

Clusters that are very spread out but far apart may indicate:

Select an option first.

Question 373

A cluster that contains points with very high internal variance likely:

Select an option first.

Question 374

A cluster that contains points with extremely low internal variance likely:

Select an option first.

Question 375

A distance metric that works well for high‑dimensional sparse vectors is:

Select an option first.

Question 376

Clusters that change dramatically when features are rescaled indicate:

Select an option first.

Question 377

A cluster that contains points from multiple natural groups likely indicates:

Select an option first.

Question 378

A cluster that contains only one or two points in K‑means often indicates:

Select an option first.

Question 379

A cluster that contains points with very different scales across features suggests:

Select an option first.

Question 380

A cluster that is extremely elongated may be caused by:

Select an option first.

Question 381

A cluster that is extremely compact may be caused by:

Select an option first.

Question 382

A cluster that appears in a dendrogram but disappears when cutting at a certain height indicates:

Select an option first.

Question 383

A cluster that contains points with very high pairwise distances suggests:

Select an option first.

Question 384

A cluster that contains points with very low pairwise distances suggests:

Select an option first.

Question 385

A cluster that is extremely sensitive to small changes in initialization suggests:

Select an option first.

Question 386

A cluster that contains points with very different densities suggests:

Select an option first.

Question 387

A cluster that contains points with very different shapes suggests:

Select an option first.

Question 388

A cluster that contains points with very different orientations (e.g., diagonal vs horizontal) suggests:

Select an option first.

Question 389

A cluster that contains points with very different densities and shapes may be better handled by:

Select an option first.

Question 390

The main advantage of DBSCAN over K‑means is that DBSCAN:

Select an option first.

Before you go, can we ask you one thing?

Thank you

Free CFA Quantitative Methods Practice Questions & Answers

Privacy Preference

Before you go, can we ask you one thing?

Thank you