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| Section | Weight | Objectives |
|---|
| Topic 1: Exploratory Data Analysis | | |
| Topic 2: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 3: SQL and Data Management | | |
| Topic 4: Statistical Methods and Modeling | | |
| Topic 5: Data Visualization and Communication | | |
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q141-Q146):
NEW QUESTION # 141
What is the main purpose of using the bootstrapping technique in inferential statistics?
- A. To filter outliers from a dataset
- B. To increase the number of features in a model
- C. To estimate the sampling distribution by resampling with replacement
- D. To validate the syntax of SQL queries in Python
Answer: C
NEW QUESTION # 142
Which Pandas methods are commonly used to extract central tendency and dispersion insights from a DataFrame?
(Choose two)
- A. var()
- B. pivot_table()
- C. sort_values()
- D. median()
Answer: A,D
NEW QUESTION # 143
Which method is used after grouping a DataFrame to compute the average value for each group in a specific column?
- A. groupby().max()
- B. groupby().aggregate()
- C. groupby().mean()
- D. groupby().count()
Answer: C
NEW QUESTION # 144
Which operations are valid and commonly used on Python lists during data transformation tasks?
(Choose two)
- A. Slicing
- B. Append
- C. Key-value mapping
- D. Index-based iteration
Answer: A,B
NEW QUESTION # 145
What is the benefit of using the __name__ == "__main__" construct in Python scripts?
- A. It prevents modules from being imported
- B. It allows selective execution of code when run as a script
- C. It defines the main function in Python
- D. It allows access to all global variables
Answer: B
NEW QUESTION # 146
......
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