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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Communicating Insights and Reporting	12.5%	- Data Visualization 1. Recognize common visualization types (bar, line, pie charts) 2. Interpret simple data visualizations 3. Select appropriate visuals for different data types - Data Storytelling and Reporting 1. Present insights with visual and verbal techniques 2. Create clear and concise analytical reports 3. Structure insights as a narrative
Introduction to Data and Data Analysis Concepts	22.5%	- Define and Classify Data 1. Explain how data becomes meaningful 2. Differentiate structured, semi-structured, and unstructured data 3. Classify data as quantitative or qualitative - Data Ethics and Privacy 1. Recognize ethical considerations in data handling 2. Understand basic data privacy concepts - Data Analysis Process and Workflow 1. Identify common data sources and collection methods 2. Explain the role of data cleaning and preparation 3. Describe the steps of the data analysis process
Python Basics for Data Analysis	32.5%	- Data Structures 1. Work with lists, tuples, dictionaries, and sets 2. Apply common operations and methods to data structures - Python Fundamentals 1. Use variables, data types, and basic operators 2. Define and use functions 3. Implement control flow structures (loops, conditionals) - File Handling 1. Use the csv module for basic CSV operations 2. Read from and write to files (text, CSV)
Working with Data and Performing Simple Analyses	32.5%	- Data Cleaning and Transformation 1. Perform basic data transformation (filtering, sorting, grouping) 2. Handle missing and inconsistent data - Simple Analytical Techniques 1. Calculate descriptive statistics (mean, median, mode) 2. Identify basic patterns and trends in data - Data Analysis with Python Libraries 1. Work with the datetime module for date/time data 2. Utilize the collections module for specialized containers 3. Perform basic operations with NumPy arrays 4. Use the math and statistics modules for basic calculations

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q13-Q18):

NEW QUESTION # 13
A health researcher uses wearable devices to record physical activity and sends a survey to randomly selected participants across age groups.
Why can this approach be effective? Select the best answer.

A. It uses unstructured interviews to validate automated tracking, improving bias detection.
B. It relies on observational methods, which are more accurate than surveys or sensors.
C. It limits sampling to one demographic, ensuring high-quality data within a specific group.
D. It combines automated data collection with representative sampling, reducing the risk of bias.

Answer: D

Explanation:
Combining automated wearable data with a randomly selected survey sample integrates objective measurements with representative participant input, which helps reduce bias and improves the reliability and generalizability of the findings.

NEW QUESTION # 14
You are writing a function to validate battery voltage readings. The rules are:
- If the reading is "MISSING"or None, return "Missing".
- If the value is below 2.5or above 4.2, return "Outlier".
Otherwise, return "Normal".
Which version correctly implements this logic using the most robust conditional and nested structures? Select the best answer.

Answer: D

Explanation:
It first handles the non-numeric cases ("MISSING" and None) in a single condition, preventing invalid comparisons, and then cleanly checks the numeric outlier bounds using an or condition (<
2.5 or > 4.2) before defaulting to "Normal".

NEW QUESTION # 15
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

A. Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.
B. Sleep and school take up the majority of time in a day.
C. Commuting is the second most time-consuming activity.
D. School and homework together take up half of the day's time.
E. Leisure and meals combined equal the time spent at school.
F. More time is spent commuting than on leisure.

Answer: A,B

Explanation:
The largest portions of the chart are sleep and school, and together they clearly make up more than half of the day. Leisure appears as a mid-sized segment that is larger than commuting but smaller than school, fitting the description of a moderate portion.

NEW QUESTION # 16
A Python script includes the expression not False and True. The developer is unsure how logical operators are evaluated in terms of precedence. What will be the final Boolean result of this expression?

A. True
B. False
C. None
D. Error

Answer: A

Explanation:
The not operator has higher precedence than and, so not False becomes True first. Then True and True is evaluated, resulting in True as the final Boolean value.

NEW QUESTION # 17
You are given two lists representing daily page views and sign-ups on a website:
views = [120, 130, 128, 700, 115, 123, 119, 680, 122]
signups = [12, 15, 13, 50, 11, 14, 10, 55, 13]
You want to:
- remove outliers (views > 600), and
- calculate correlation between the cleaned lists.
Which code accomplishes this correctly? Select the best answer.

Answer: D

Explanation:
It converts the lists to NumPy arrays, builds a boolean mask based on the views threshold to remove outliers, applies the same mask to both arrays so they stay aligned, and then computes the correlation on the cleaned pairs using np.corrcoef.

NEW QUESTION # 18
......

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