CompTIA DataX Exam
Last Update 4 days ago
Total Questions : 85
Dive into our fully updated and stable DY0-001 practice test platform, featuring all the latest CompTIA Data+ exam questions added this week. Our preparation tool is more than just a CompTIA study aid; it's a strategic advantage.
Our CompTIA Data+ practice questions crafted to reflect the domains and difficulty of the actual exam. The detailed rationales explain the 'why' behind each answer, reinforcing key concepts about DY0-001. Use this test to pinpoint which areas you need to focus your study on.
A data scientist is developing a model to predict the outcome of a vote for a national mascot. The choice is between tigers and lions. The full data set represents feedback from individuals representing 17 professions and 12 different locations. The following rank aggregation represents 80% of the data set:
(Screenshot shows survey rankings for just two professions and a few locations, all voting for "Tigers")
Which of the following is the most likely concern about the model's ability to predict the outcome of the vote?
A data scientist wants to digitize historical hard copies of documents. Which of the following is the best method for this task?
A data scientist is creating a responsive model that will update a product's daily pricing based on the previous day's sales volume. Which of the following resource constraints is the data scientist's greatest concern?
Which of the following best describes the minimization of the residual term in a ridge linear regression?
A data analyst is examining the correlation matrix of a new data set to identify issues that could adversely impact model performance. Which of the following is the analyst most likely checking for?
A data scientist is performing a linear regression and wants to construct a model that explains the most variation in the data. Which of the following should the data scientist maximize when evaluating the regression performance metrics?
A data scientist is designing a real-time machine-learning model that classifies a user based on initial behavior. The run times of these models are provided in the following table:
Which of the following models should the data scientist recommend for deployment?
A data scientist wants to predict a person's travel destination. The options are:
Branson, Missouri, United States
Mount Kilimanjaro, Tanzania
Disneyland Paris, Paris, France
Sydney Opera House, Sydney, Australia
Which of the following models would best fit this use case?
TESTED 30 Nov 2025
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