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[General] 100% Pass 2026 Fantastic CompTIA Vce DY0-001 Files

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【General】 100% Pass 2026 Fantastic CompTIA Vce DY0-001 Files

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CompTIA DataX Certification Exam Sample Questions (Q32-Q37):NEW QUESTION # 32
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. Accuracy
  • B. AUC
  • C. R²
  • D. p value
Answer: C
Explanation:
# R² (coefficient of determination) quantifies how much of the variance in the dependent variable is explained by the model. A higher R² means a better fit to the data, making it the metric to maximize for explanatory power in regression analysis.
Why the other options are incorrect:
* A: Accuracy is used in classification, not regression.
* C: p-values test statistical significance of coefficients, not overall model fit.
* D: AUC (Area Under the Curve) applies to classification models, not regression.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 3.2:"R² is a regression performance metric indicating the proportion of variance explained by the independent variables."

NEW QUESTION # 33
A data scientist is presenting the recommendations from a monthslong modeling and experiment process to the company's Chief Executive Officer. Which of the following is the best set of artifacts to include in the presentation?
  • A. Methodology, code snippets, findings, data tables, and p-values
  • B. Methods, data overview, results, recommendations, and charts
  • C. Results, recommendations, justifications, and clear charts
  • D. Recommendation, charts, justifications, code reviews, and results
Answer: C
Explanation:
# For executive-level presentations, the focus should be on strategic outcomes. Therefore, concise results, clear actionable recommendations, visual summaries (charts), and minimal justifications are best. Technical details such as p-values, code, or full methods are too granular.
Why the other options are incorrect:
* A: Too method-heavy for executive audiences.
* C: Includes code reviews - not suitable for a CEO.
* D: Overly technical for high-level stakeholders.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 5.5:"Executive communication should focus on outcome-driven recommendations, high-level insights, and actionable visuals."
* Harvard Business Review - Communicating Data to Executives:"Avoid technical detail. Use visuals and clearly stated recommendations supported by business-focused justifications."

NEW QUESTION # 34
Which of the following types of layers is used to downsample feature detection when using a convolutional neural network?
  • A. Input
  • B. Pooling
  • C. Output
  • D. Hidden
Answer: B
Explanation:
# Pooling layers are used in Convolutional Neural Networks (CNNs) to reduce the spatial dimensions (width and height) of the feature maps. This helps in downsampling, reducing computational complexity, and controlling overfitting by summarizing the features (e.g., max pooling or average pooling).
Why the other options are incorrect:
* B: Input layers receive raw data and do not perform downsampling.
* C: Output layers generate the final prediction.
* D: Hidden layers process data but do not specifically perform downsampling unless designed to do so (e.g., convolutional or pooling sublayers).
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 4.3:"Pooling layers are used to downsample feature maps and are critical in CNNs for reducing dimensions."
-

NEW QUESTION # 35
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?
  • A. Development time
  • B. Data collection time
  • C. Deployment time
  • D. Training time
Answer: D
Explanation:
# Since the model must update daily based on new data, retraining must be fast enough to meet daily deadlines. Therefore, training time is the critical constraint - it determines whether pricing updates can be executed promptly.
Why the other options are incorrect:
* A: Deployment time is a one-time or infrequent process.
* C: Development time is less critical once the model is built.
* D: Data is already collected daily - assumed to be available.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 5.4:"Time-sensitive applications such as daily pricing require fast model retraining, making training time a critical factor."
* Real-Time ML Deployment Handbook, Chapter 6:"Retraining time is the bottleneck in time- constrained systems that adapt to fresh inputs regularly."
-

NEW QUESTION # 36
Which of the following layer sets includes the minimum three layers required to constitute an artificial neural network?
  • A. An input layer, a pooling layer, and an output layer
  • B. An input layer, a hidden layer, and an output layer
  • C. An input layer, a dropout layer, and a hidden layer
  • D. An input layer, a convolutional layer, and a hidden layer
Answer: B
Explanation:
# A basic artificial neural network (ANN) consists of:
* An input layer to receive data
* At least one hidden layer to process the data
* An output layer to produce predictions
These three layers form the minimal architecture required for learning and transformation.
Why the other options are incorrect:
* A: Pooling layers are used in CNNs, not core ANN structure.
* B: Convolutional layers are specific to CNNs.
* D: Dropout is a regularization technique, not a required component.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 4.3:"ANNs must include an input layer, hidden layer(s), and an output layer to form a complete learning structure."
* Deep Learning Fundamentals, Chapter 3:"At a minimum, a neural network includes input, hidden, and output layers to process and propagate data."
-

NEW QUESTION # 37
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