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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Analysis Fundamentals	20%	- Data Collection and Preparation 1. Data import/export operations 2. Data cleaning and preprocessing basics 3. Data sources and acquisition methods - Introduction to Data Analysis 1. Types of data (structured, unstructured, semi-structured) 2. Data analysis process lifecycle 3. Data analysis concepts and terminology
Topic 2: Python Programming for Data Analysis	30%	- Control Flow and Functions 1. Loops (for, while) 2. Conditional statements (if, elif, else) 3. Return values and scope 4. Function definitions and parameters - Python Data Types and Structures 1. Lists, tuples, dictionaries, sets 2. Numbers, strings, booleans 3. Data type conversions - File Operations 1. Reading from files (text, CSV) 2. Context managers (with statement) 3. Writing to files
Topic 3: Applied Data Analysis Projects	20%	- Exploratory Data Analysis (EDA) 1. Correlation analysis 2. Pattern identification 3. Data distribution analysis 4. Descriptive statistics computation - Data Analysis Workflow 1. Analysis and modeling 2. Problem definition 3. Data exploration and cleaning 4. Results interpretation and presentation
Topic 4: Working with Data Using Python Libraries	30%	- Pandas Library 1. Data selection and filtering 2. DataFrame operations (merge, join, concat) 3. Series and DataFrame structures 4. Handling missing data 5. GroupBy operations - Data Visualization 1. Matplotlib basics 2. Creating basic charts (line, bar, scatter, histogram) 3. Customizing plots 4. Seaborn introduction - NumPy Fundamentals 1. NumPy arrays and operations 2. Basic statistical functions 3. Array indexing and slicing 4. Vectorized operations

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q118-Q123):

NEW QUESTION # 118
What is the correct SQL statement to permanently remove a table named customers from a database?

A. DELETE TABLE customers;
B. TRUNCATE TABLE customers;
C. REMOVE TABLE customers;
D. DROP TABLE customers;

Answer: D

NEW QUESTION # 119
What is a key assumption of linear regression that distinguishes it from logistic regression?

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

Answer: A

NEW QUESTION # 120
Which conditions typically necessitate data normalization or scaling before analysis?
(choose two)

A. Presence of duplicate data
B. Distance-based modeling algorithms
C. Features with different units and scales
D. Boolean feature encoding

Answer: B,C

NEW QUESTION # 121
Which type of chart is most appropriate when comparing the distribution of a numerical variable across multiple categories?

A. Line chart
B. Box plot
C. Pie chart
D. Scatter plot

Answer: B

NEW QUESTION # 122
What is the primary advantage of using web scraping as a data collection method in business analytics?

A. It ensures compliance with privacy laws
B. It eliminates the need for data cleaning
C. It guarantees real-time data accuracy
D. It allows automation of data collection from public sources

Answer: D

NEW QUESTION # 123
......

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