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| Section | Weight | Objectives |
|---|
| Exploratory Data Analysis | | |
| Statistical Methods and Modeling | | |
| SQL and Data Management | | |
| Data Acquisition and Pre-Processing | 29.2% | |
| Data Visualization and Communication | | |
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q24-Q29):
NEW QUESTION # 24
Which metric is most appropriate for evaluating the accuracy of a classification model?
- A. Precision
- B. Mean squared error
- C. Confusion matrix
- D. R-squared
Answer: A
NEW QUESTION # 25
Which chart types are commonly used to represent relationships between two numerical variables in Python-based visualizations?
(choose two)
Response:
- A. Histogram
- B. Heatmap
- C. Scatter plot
- D. Line chart
Answer: B,C
NEW QUESTION # 26
What is one potential risk of dynamically constructing SQL queries using string concatenation in Python scripts?
- A. Increased memory usage
- B. Slower database performance
- C. Missing foreign key constraints
- D. Exposure to SQL injection attacks
Answer: D
NEW QUESTION # 27
Which method in the pandas library allows efficient loading of large datasets in chunks to conserve memory?
- A. import_csv()
- B. load_dataset()
- C. read_csv(chunksize=...)
- D. fetch_chunks()
Answer: C
NEW QUESTION # 28
What is a key assumption of linear regression that distinguishes it from logistic regression?
- A. Output values must be binary
- B. The relationship between predictors and the outcome is linear
- C. Predictors must be independent
- D. The target variable is unordered categorical
Answer: B
NEW QUESTION # 29
......
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