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Python Institute PCAD-31-02 : Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)

PCAD-31-02 real exams

Exam Code: PCAD-31-02

Exam Name: Python Institute Certified Associate Data Analyst with Python (PCAD-31-02)

Updated: Sep 18, 2026

Q & A: 146 Questions and Answers

PCAD-31-02 Free Demo download

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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Exploratory Data Analysis
SQL and Data Management
Data Acquisition and Pre-Processing29.2%
Data Visualization and Communication
Statistical Methods and Modeling

Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:

Question #1
What is the benefit of using the __name__ == "__main__" construct in Python scripts?

A. It allows access to all global variables
B. It allows selective execution of code when run as a script
C. It prevents modules from being imported
D. It defines the main function in Python


Question #2
What is the main reason to remove duplicate records before performing analysis?

A. It reduces redundancy that can skew statistical metrics
B. It helps increase sample size
C. It avoids converting data to JSON format
D. It ensures training data is intentionally overfitted


Question #3
In a scatter plot showing the relationship between advertising spend and sales revenue, the points form a tight upward-sloping pattern. What conclusion can be drawn?

A. There is a strong positive correlation
B. The data shows no apparent relationship
C. The correlation is weak and likely negative
D. Advertising has no effect on sales


Question #4
What is one potential risk of dynamically constructing SQL queries using string concatenation in Python scripts?

A. Missing foreign key constraints
B. Exposure to SQL injection attacks
C. Slower database performance
D. Increased memory usage


Question #5
Which of the following techniques are commonly used in the standardization of textual or categorical data during preprocessing?
(Choose two)

A. Trimming whitespace from string values
B. Scaling numeric features to a fixed range
C. Applying logarithmic transformation to skewed data
D. Replacing misspellings with a canonical category label


Solutions:

Question #1
Correct Answer: B
Question #2
Correct Answer: A
Question #3
Correct Answer: A
Question #4
Correct Answer: B
Question #5
Correct Answer: A,D

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