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

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

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

2. What is the function of the melt() operation in Pandas when reshaping wide-format data?

A) Sorts the DataFrame based on a column
B) Transposes the DataFrame
C) Converts column values into rows
D) Combines multiple DataFrames

3. 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.unique()
C) DataFrame.remove_duplicates()
D) DataFrame.nunique()

4. Why is it important to use a test dataset separate from the training dataset when evaluating a machine learning model?

A) To optimize the model's training accuracy
B) To evaluate the model's performance on unseen data
C) To ensure the loss function is minimized
D) To reduce the number of iterations during training

5. Which practices are typically part of the data integration process?
(Choose two)

A) Format standardization
B) Neural network training
C) Data encryption
D) Schema alignment

Solutions: