1. What is the primary goal of predictive analytics?
a) To describe past data trends
b) To forecast future outcomes based on historical data
c) To visualize data in charts and graphs
d) To clean and prepare data for analysis
Answer: b) To forecast future outcomes based on historical data
2. Which of the following techniques is commonly used in predictive analytics?
a) Descriptive statistics
b) Regression analysis
c) Data mining
d) Cluster analysis
Answer: b) Regression analysis
3. What is “machine learning” in the context of predictive analytics?
a) The process of manually analyzing data
b) The use of algorithms that learn from data to make predictions
c) The creation of static reports from historical data
d) The visualization of data trends
Answer: b) The use of algorithms that learn from data to make predictions
4. In predictive analytics, what does “model training” refer to?
a) The process of preparing data for analysis
b) The process of developing and refining a predictive model using historical data
c) The process of presenting model results to stakeholders
d) The process of cleaning and formatting data
Answer: b) The process of developing and refining a predictive model using historical data
5. What is “overfitting” in predictive modeling?
a) When a model is too simple to capture the underlying patterns in the data
b) When a model is too complex and captures noise rather than patterns
c) When a model fails to predict any outcomes
d) When a model is unable to process data
Answer: b) When a model is too complex and captures noise rather than patterns
6. Which metric is commonly used to evaluate the performance of a predictive model?
a) Mean absolute error (MAE)
b) Data variance
c) Frequency distribution
d) Data standard deviation
Answer: a) Mean absolute error (MAE)
7. What is “feature selection” in predictive analytics?
a) The process of choosing the most relevant variables for the model
b) The process of collecting data
c) The process of cleaning data
d) The process of visualizing data
Answer: a) The process of choosing the most relevant variables for the model
8. Which type of predictive model is used for classifying data into categories?
a) Linear regression
b) Decision tree
c) Time series analysis
d) Principal component analysis
Answer: b) Decision tree
9. What is “time series analysis” in predictive analytics?
a) Analyzing data at a single point in time
b) Analyzing data collected over regular intervals to identify trends and patterns
c) Analyzing qualitative data
d) Analyzing data without considering the time component
Answer: b) Analyzing data collected over regular intervals to identify trends and patterns
10. What is the purpose of “cross-validation” in predictive analytics?
a) To ensure the model is trained on the entire dataset
b) To evaluate the model’s performance by splitting the data into training and testing sets
c) To visualize the model’s output
d) To clean the dataset before analysis
Answer: b) To evaluate the model’s performance by splitting the data into training and testing sets