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| Section | Weight | Objectives |
|---|
| Topic 1: Data Acquisition and Pre-Processing | 29.2% | |
| Topic 2: Data Visualization and Communication | | |
| Topic 3: SQL and Data Management | | |
| Topic 4: Exploratory Data Analysis | | |
| Topic 5: Statistical Methods and Modeling | | |
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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q48-Q53):
NEW QUESTION # 48
Which of the following would most likely be classified as unstructured data?
- A. Normalized employee database in PostgreSQL
- B. Product ID and price list in a CSV
- C. Inventory levels in a spreadsheet
- D. Collection of customer service audio recordings
Answer: D
NEW QUESTION # 49
What does a Pearson correlation coefficient value of -0.9 imply about the relationship between two numerical variables?
- A. A strong negative linear relationship
- B. No correlation
- C. A weak positive relationship
- D. A moderate non-linear association
Answer: A
NEW QUESTION # 50
Which element is essential to justify a conclusion drawn from a dataset?
- A. File format of the source data
- B. Logical reasoning and supported metrics
- C. The use of color in plots
- D. The origin of the dataset
Answer: B
NEW QUESTION # 51
Which of the following practices contributes most to making Python scripts modular and maintainable?
- A. Writing all logic in the global scope
- B. Using global variables freely
- C. Hard-coding file paths in every function
- D. Structuring code with reusable functions and modules
Answer: D
NEW QUESTION # 52
What is a best practice when organizing data in a spreadsheet for analysis?
- A. Place charts in the middle of data tables
- B. Apply conditional formatting to entire rows only
- C. Use consistent column headers across all sheets
- D. Merge cells to reduce redundancy
Answer: C
NEW QUESTION # 53
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