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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Working with Data Using Python Libraries | 30% | - Pandas Library
|
| Topic 2: Data Analysis Fundamentals | 20% | - Data Collection and Preparation
|
| Topic 3: Applied Data Analysis Projects | 20% | - Exploratory Data Analysis (EDA)
|
| Topic 4: Python Programming for Data Analysis | 30% | - Control Flow and Functions
|
1. What is the recommended Python library to connect and extract tabular data directly from an Excel file?
A) openpyxl
B) matplotlib
C) sqlite3
D) csv
2. What may occur if a model is evaluated using the same data it was trained on?
A) Overfitting
B) Data leakage
C) Overgeneralization
D) Underfitting
3. Which approaches help tailor data visualizations for non-technical stakeholders?
(Choose two)
A) Use jargon-rich annotations
B) Use raw code outputs for clarity
C) Add context through narrative or titles
D) Focus on trend and summary metrics
4. Which methods are typically used to assess relationships between variables in exploratory data analysis?
(Choose two)
A) Box plots
B) Correlation matrix
C) Histogram analysis
D) Scatter plots
5. What is a key assumption of linear regression that distinguishes it from logistic regression?
A) Output values must be binary
B) Predictors must be independent
C) The target variable is unordered categorical
D) The relationship between predictors and the outcome is linear
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: B,D | Question # 4 Answer: B,D | Question # 5 Answer: D |
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