FBLA Data Science & AI practice test
Data Science & AI covers how organizations collect, analyze, and model data, and how artificial intelligence and machine learning systems are built, evaluated, and used responsibly.
Topics on the FBLA Data Science & AI test
- Data collection, cleaning, and data types
- Descriptive statistics and visualization
- Supervised and unsupervised machine learning
- Model evaluation, overfitting, and bias
- Generative AI and large language models
- AI ethics, privacy, and governance
Free FBLA Data Science & AI practice questions and answers
Try each question before opening the answer. Every AI practice test explains its answers the same way.
Question 1
A model performs very well on its training data but poorly on new data. This problem is called:
- AUnderfitting
- BOverfitting
- CNormalization
- DClustering
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Answer: B. Overfitting
An overfit model has memorized noise in the training data instead of learning patterns that generalize.
Question 2
Grouping customers into segments without any predefined labels is an example of:
- ASupervised learning
- BUnsupervised learning
- CReinforcement learning
- DData entry
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Answer: B. Unsupervised learning
Clustering finds structure in unlabeled data, which makes it unsupervised learning.
Question 3
What is the median of the data set 2, 4, 4, 5, 10?
- A4
- B4.5
- C5
- D10
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Answer: A. 4
The median is the middle value of the sorted list, which is 4. The mean is 5 because the outlier 10 pulls it up.
How to study for FBLA Data Science & AI
Tie each term to an example: be ready to say which learning type, metric, or chart fits a business scenario. Review basic statistics (mean, median, standard deviation) too.
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Start practicing freeFBLA Data Science & AI FAQ
How many questions are on the FBLA Data Science & AI test?
Data Science & AI is an objective test event. Under the current guidelines, FBLA objective tests are typically 100 multiple-choice questions in 50 minutes. Check the official FBLA competitive event guidelines for your season and conference.
What topics are on the FBLA Data Science & AI test?
Expect questions on data collection, cleaning, and data types; descriptive statistics and visualization; supervised and unsupervised machine learning; model evaluation, overfitting, and bias; generative AI and large language models; and aI ethics, privacy, and governance.
Are these official FBLA Data Science & AI questions?
No. The sample questions are original and written in the style of FBLA objective tests. TierOne is an independent study aid and is not affiliated with FBLA.