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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

1. Which approaches help tailor data visualizations for non-technical stakeholders?
(Choose two)

A) Use jargon-rich annotations
B) Add context through narrative or titles
C) Focus on trend and summary metrics
D) Use raw code outputs for clarity

2. Which element is essential to justify a conclusion drawn from a dataset?

A) Logical reasoning and supported metrics
B) The use of color in plots
C) File format of the source data
D) The origin of the dataset

3. What is the main purpose of using the bootstrapping technique in inferential statistics?

A) To estimate the sampling distribution by resampling with replacement
B) To filter outliers from a dataset
C) To increase the number of features in a model
D) To validate the syntax of SQL queries in Python

4. Which technique would be most appropriate to handle missing numerical values in a dataset intended for machine learning?

A) Filling with random values
B) Imputation using mean or median
C) Replacing with NULL
D) Dropping all columns

5. Which method is typically used in Pandas to check if a column contains only values within an expected range?

A) df.sample()
B) df.isin()
C) df.clip()
D) df.sort_values()

Solutions: