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Python Institute PCAD-31-02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploratory Data Analysis | ||
| Topic 2: Statistical Methods and Modeling | ||
| Topic 3: SQL and Data Management | ||
| Topic 4: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 5: Data Visualization and Communication |
Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions:
1. Which Pandas methods are commonly used to extract central tendency and dispersion insights from a DataFrame?
(Choose two)
A) pivot_table()
B) median()
C) sort_values()
D) var()
2. Which techniques can be used to select a subset of rows and columns from a DataFrame using labels?
(Choose two)
A) df.iloc[0:5, 'col2']
B) df['col1', 'col2']
C) df.loc[2:7, ['col1', 'col2']]
D) df.loc[:, 'col1']
3. What is the main purpose of using the bootstrapping technique in inferential statistics?
A) To increase the number of features in a model
B) To validate the syntax of SQL queries in Python
C) To estimate the sampling distribution by resampling with replacement
D) To filter outliers from a dataset
4. What is a best practice when organizing data in a spreadsheet for analysis?
A) Place charts in the middle of data tables
B) Use consistent column headers across all sheets
C) Apply conditional formatting to entire rows only
D) Merge cells to reduce redundancy
5. What does the describe() method in Pandas provide when applied to a numerical DataFrame column?
A) A histogram of the data distribution
B) Only the standard deviation of the data
C) A normalized version of the data column
D) Basic descriptive statistics such as count, mean, and quartiles
Solutions:
| Question # 1 Answer: B,D | Question # 2 Answer: C,D | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: D |


