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| Section | Weight | Objectives |
|---|
| Data Visualization and Communication | | |
| Statistical Methods and Modeling | | |
| Data Acquisition and Pre-Processing | 29.2% | |
| SQL and Data Management | | |
| Exploratory Data Analysis | | |
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PCAD-31-02 Official Study Guide | PCAD-31-02 Valid Exam Blueprint
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q79-Q84):
NEW QUESTION # 79
Which characteristics are typically associated with supervised learning algorithms?
(Choose two)
- A. They require labeled training data
- B. They are useful for regression and classification tasks
- C. They automatically detect outliers
- D. They work only with numerical features
Answer: A,B
NEW QUESTION # 80
What is the best approach when comparing SQL NULL values with Python data during conditional checks?
- A. Replace NULL with zero before importing
- B. Use Python's None and SQL's IS NULL clause
- C. Convert all NULL to string before comparison
- D. Use == None directly in SQL queries
Answer: B
NEW QUESTION # 81
Which statements correctly describe differences between linear and logistic regression?
(Choose two)
- A. Linear regression applies only to classification tasks
- B. Logistic regression uses the logit function to model relationships
- C. Linear regression requires target variables to be binary
- D. Logistic regression outputs probabilities, while linear regression predicts continuous values
Answer: B,D
NEW QUESTION # 82
Which method allows you to detect and remove rows with duplicate values across all columns in a Pandas DataFrame?
- A. DataFrame.drop_duplicates()
- B. DataFrame.remove_duplicates()
- C. DataFrame.nunique()
- D. DataFrame.unique()
Answer: B
NEW QUESTION # 83
Which packages are most commonly used together in a data science workflow for data manipulation and visualization?
(Choose two)
- A. pandas
- B. flask
- C. Pygame
- D. NumPy
Answer: A,D
NEW QUESTION # 84
......
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