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| Section | Weight | Objectives |
|---|
| Communicating Insights and Reporting | 12.5% | - Data Storytelling and Reporting
- 1. Structure insights as a narrative
- 2. Present insights with visual and verbal techniques
- 3. Create clear and concise analytical reports
- Data Visualization
- 1. Interpret simple data visualizations
- 2. Select appropriate visuals for different data types
- 3. Recognize common visualization types (bar, line, pie charts)
|
| Introduction to Data and Data Analysis Concepts | 22.5% | - Define and Classify Data
- 1. Differentiate structured, semi-structured, and unstructured data
- 2. Classify data as quantitative or qualitative
- 3. Explain how data becomes meaningful
- Data Analysis Process and Workflow
- 1. Explain the role of data cleaning and preparation
- 2. Describe the steps of the data analysis process
- 3. Identify common data sources and collection methods
- Data Ethics and Privacy
- 1. Understand basic data privacy concepts
- 2. Recognize ethical considerations in data handling
|
| Python Basics for Data Analysis | 32.5% | - Data Structures
- 1. Apply common operations and methods to data structures
- 2. Work with lists, tuples, dictionaries, and sets
- File Handling
- 1. Use the csv module for basic CSV operations
- 2. Read from and write to files (text, CSV)
- Python Fundamentals
- 1. Use variables, data types, and basic operators
- 2. Define and use functions
- 3. Implement control flow structures (loops, conditionals)
|
| Working with Data and Performing Simple Analyses | 32.5% | - Simple Analytical Techniques
- 1. Calculate descriptive statistics (mean, median, mode)
- 2. Identify basic patterns and trends in data
- Data Cleaning and Transformation
- 1. Handle missing and inconsistent data
- 2. Perform basic data transformation (filtering, sorting, grouping)
- Data Analysis with Python Libraries
- 1. Use the math and statistics modules for basic calculations
- 2. Work with the datetime module for date/time data
- 3. Perform basic operations with NumPy arrays
- 4. Utilize the collections module for specialized containers
|
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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q26-Q31):
NEW QUESTION # 26
A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?
- A. True
- B. None
- C. Error
- D. False
Answer: A
Explanation:
The in operator checks for substring presence. Since the character "a" exists in "apple", the expression evaluates to True, demonstrating how membership works for strings in Python.
NEW QUESTION # 27
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?
- A. ytho
- B. yth
- C. tho
- D. ythn
Answer: B
Explanation:
Slicing includes the start index but excludes the end index. Characters at indices 1, 2, and 3 are selected, producing the substring "yth".
NEW QUESTION # 28
You are creating a presentation slide to communicate findings about student stress levels across four categories over a six-month period. You include the following line graph in your presentation:

Your goal is to help your audience clearly understand trends in stress levels over time.
What is the highest problem with this visual presentation? Select the best answer.
- A. The lines are too light and similar in color, making it difficult to distinguish between trends.
- B. The font used in the chart is hard to read; using larger, uppercase text would improve clarity.
- C. The graph doesn't explain what each stress level means or show exact values for each month, which limits interpretation.
- D. The months should be replaced with week numbers to provide more detailed insight.
- E. The chart should be in 3D format to show depth and highlight differences more clearly.
Answer: A
Explanation:
The lines are very light and visually similar, making it difficult to clearly distinguish between the different stress level trends, which directly reduces the effectiveness of the visualization in communicating patterns over time.
NEW QUESTION # 29
A dictionary is defined as d = {"a":1, "b":2}. The programmer accesses d["c"]. What happens when this line executes?
- A. Adds key automatically
- B. Returns None
- C. Raises KeyError
- D. Returns 0
Answer: C
Explanation:
Accessing a non-existent key using square brackets raises a KeyError. Python does not automatically create missing keys, so the program will terminate unless the exception is handled.
NEW QUESTION # 30
Which of the following statements about Python functions are correct? (Choose two.)
- A. A function cannot call itself or be passed as an argument to itself.
- B. If a function does not contain a returnstatement, it returns Noneby default.
- C. Default parameters must always come before required ones in the parameter list.
- D. passexecutes the function body and returns its result.
- E. Functions can only return numeric values or strings.
- F. Positional arguments must be passed in the order defined, while keyword arguments can be passed in any order using their parameter names.
Answer: B,F
Explanation:
Positional arguments are matched to parameters by their position, so they must follow the defined order, while keyword arguments are matched by name and can be provided in any order. If a function completes without an explicit return statement, Python returns None automatically.
NEW QUESTION # 31
......
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