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: Aug 18, 2026

Q & A: 146 Questions and Answers

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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Statistical Methods and Modeling
Topic 2: Exploratory Data Analysis
Topic 3: Data Visualization and Communication
Topic 4: SQL and Data Management
Topic 5: Data Acquisition and Pre-Processing29.2%

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

1. Which practices are essential to ensure a fair evaluation of a machine learning model's performance?
(Choose two)

A) Using cross-validation to assess generalizability
B) Training on the entire dataset including test records
C) Randomizing the test dataset labels
D) Splitting data into training and test sets


2. Which method is commonly used to handle missing numerical data in a dataset?

A) Replacing with text labels
B) Dropping all columns
C) Multiplying all missing values by zero
D) Filling with the mean or median


3. When analyzing a dataset of customer ages, you calculate the mean, median, and mode. What does it indicate if all three values are approximately equal?

A) The dataset is positively skewed
B) The dataset is uniformly distributed
C) The dataset has a normal distribution
D) The dataset contains outliers


4. What is a key assumption of linear regression that distinguishes it from logistic regression?

A) Output values must be binary
B) The target variable is unordered categorical
C) Predictors must be independent
D) The relationship between predictors and the outcome is linear


5. What is the purpose of using the groupby() function in a Pandas DataFrame when analyzing a dataset with multiple categories and numerical values?

A) To append new rows to the DataFrame
B) To sort the DataFrame by a specific column
C) To split the data into subgroups for aggregation
D) To filter rows based on index values


Solutions:

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

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