North Carolina Predictive Analytics Exam
Question and correct answers (verified
answers 100%) Q&A 2026/2027 INSTANT
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1. What is the primary purpose of predictive analytics?
A. To store large amounts of data
B. To predict future outcomes using historical data
C. To replace database systems
D. To create only visual reports
Correct Answer: B
Rationale: Predictive analytics uses historical data, statistical models, and machine
learning techniques to forecast future events, behaviors, or trends.
2. Which type of analytics focuses on explaining why an event occurred?
A. Predictive analytics
B. Prescriptive analytics
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: C
Rationale: Diagnostic analytics examines historical information to identify causes
and relationships behind past outcomes.
3. Which algorithm is commonly used for binary classification problems?
,A. Linear regression
B. Logistic regression
C. K-means clustering
D. Principal component analysis
Correct Answer: B
Rationale: Logistic regression is designed for classification tasks where the
outcome has two possible categories.
4. In predictive modeling, what is the dependent variable called?
A. Feature
B. Predictor
C. Target variable
D. Dataset
Correct Answer: C
Rationale: The target variable is the outcome that the predictive model attempts
to predict.
5. What is the purpose of splitting data into training and testing datasets?
A. To increase database size
B. To evaluate model performance on unseen data
C. To remove all errors
D. To eliminate variables
Correct Answer: B
Rationale: Training data builds the model, while testing data measures how well
the model performs on new information.
,6. Which technique reduces the number of variables while preserving important
information?
A. Data duplication
B. Principal Component Analysis (PCA)
C. Data entry
D. Sampling bias
Correct Answer: B
Rationale: PCA transforms many variables into fewer components while retaining
the majority of important variation.
7. What does overfitting mean in predictive analytics?
A. The model performs poorly on training data
B. The model learns noise instead of patterns
C. The model has no variables
D. The dataset is too small
Correct Answer: B
Rationale: Overfitting occurs when a model captures random noise and performs
poorly on new data.
8. Which metric measures the average squared difference between predicted
and actual values?
A. Accuracy
B. Mean Squared Error (MSE)
C. Precision
D. Recall
Correct Answer: B
, Rationale: MSE calculates the average squared error between predicted values
and actual outcomes.
9. Which machine learning method is commonly used for grouping similar
customers?
A. Clustering
B. Regression
C. Classification
D. Forecasting
Correct Answer: A
Rationale: Clustering identifies groups of similar observations without predefined
categories.
10. What is a major advantage of predictive analytics in organizations?
A. Eliminating all human decisions
B. Supporting data-driven decision-making
C. Removing the need for data collection
D. Preventing every possible risk
Correct Answer: B
Rationale: Predictive analytics helps organizations make informed decisions by
identifying trends and future possibilities.
11. Which programming language is widely used for predictive analytics?
A. HTML
B. Python
C. CSS
D. XML
Question and correct answers (verified
answers 100%) Q&A 2026/2027 INSTANT
DOWNLOAD PDF
1. What is the primary purpose of predictive analytics?
A. To store large amounts of data
B. To predict future outcomes using historical data
C. To replace database systems
D. To create only visual reports
Correct Answer: B
Rationale: Predictive analytics uses historical data, statistical models, and machine
learning techniques to forecast future events, behaviors, or trends.
2. Which type of analytics focuses on explaining why an event occurred?
A. Predictive analytics
B. Prescriptive analytics
C. Diagnostic analytics
D. Descriptive analytics
Correct Answer: C
Rationale: Diagnostic analytics examines historical information to identify causes
and relationships behind past outcomes.
3. Which algorithm is commonly used for binary classification problems?
,A. Linear regression
B. Logistic regression
C. K-means clustering
D. Principal component analysis
Correct Answer: B
Rationale: Logistic regression is designed for classification tasks where the
outcome has two possible categories.
4. In predictive modeling, what is the dependent variable called?
A. Feature
B. Predictor
C. Target variable
D. Dataset
Correct Answer: C
Rationale: The target variable is the outcome that the predictive model attempts
to predict.
5. What is the purpose of splitting data into training and testing datasets?
A. To increase database size
B. To evaluate model performance on unseen data
C. To remove all errors
D. To eliminate variables
Correct Answer: B
Rationale: Training data builds the model, while testing data measures how well
the model performs on new information.
,6. Which technique reduces the number of variables while preserving important
information?
A. Data duplication
B. Principal Component Analysis (PCA)
C. Data entry
D. Sampling bias
Correct Answer: B
Rationale: PCA transforms many variables into fewer components while retaining
the majority of important variation.
7. What does overfitting mean in predictive analytics?
A. The model performs poorly on training data
B. The model learns noise instead of patterns
C. The model has no variables
D. The dataset is too small
Correct Answer: B
Rationale: Overfitting occurs when a model captures random noise and performs
poorly on new data.
8. Which metric measures the average squared difference between predicted
and actual values?
A. Accuracy
B. Mean Squared Error (MSE)
C. Precision
D. Recall
Correct Answer: B
, Rationale: MSE calculates the average squared error between predicted values
and actual outcomes.
9. Which machine learning method is commonly used for grouping similar
customers?
A. Clustering
B. Regression
C. Classification
D. Forecasting
Correct Answer: A
Rationale: Clustering identifies groups of similar observations without predefined
categories.
10. What is a major advantage of predictive analytics in organizations?
A. Eliminating all human decisions
B. Supporting data-driven decision-making
C. Removing the need for data collection
D. Preventing every possible risk
Correct Answer: B
Rationale: Predictive analytics helps organizations make informed decisions by
identifying trends and future possibilities.
11. Which programming language is widely used for predictive analytics?
A. HTML
B. Python
C. CSS
D. XML
