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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Python Basics for Data Analysis	32.5%	- Python Fundamentals 1. Use variables, data types, and basic operators 2. Implement control flow structures (loops, conditionals) 3. Define and use functions - File Handling 1. Use the csv module for basic CSV operations 2. Read from and write to files (text, CSV) - Data Structures 1. Apply common operations and methods to data structures 2. Work with lists, tuples, dictionaries, and sets
Topic 2: 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. Structure insights as a narrative 2. Present insights with visual and verbal techniques 3. Create clear and concise analytical reports
Topic 3: 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 Analysis with Python Libraries 1. Work with the datetime module for date/time data 2. Utilize the collections module for specialized containers 3. Use the math and statistics modules for basic calculations 4. Perform basic operations with NumPy arrays - Data Cleaning and Transformation 1. Handle missing and inconsistent data 2. Perform basic data transformation (filtering, sorting, grouping)
Topic 4: Introduction to Data and Data Analysis Concepts	22.5%	- 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 - Data Ethics and Privacy 1. Understand basic data privacy concepts 2. Recognize ethical considerations in data handling - Define and Classify Data 1. Differentiate structured, semi-structured, and unstructured data 2. Explain how data becomes meaningful 3. Classify data as quantitative or qualitative

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q29-Q34):

NEW QUESTION # 29
You are given the following list of daily step counts:
steps = [8230, 9020, 7640, 8760, 10020, 2546, 9817]
Your task is to calculate:
- the standard deviation of the step counts,
- the average rounded up to the nearest whole number, and
- the median of the step counts.
Which code snippet correctly performs all three tasks? Select the best answer.
import statistics

A. import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics
B. import math
print(statistics.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))
C. import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
D. import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics

Answer: B

Explanation:
It uses statistics.stdev() to compute the standard deviation, statistics.mean() to compute the average and math.ceil() to round it up to the nearest whole number, and statistics.median() to compute the median.

NEW QUESTION # 30
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 combines automated data collection with representative sampling, reducing the risk of bias.
B. It uses unstructured interviews to validate automated tracking, improving bias detection.
C. It limits sampling to one demographic, ensuring high-quality data within a specific group.
D. It relies on observational methods, which are more accurate than surveys or sensors.

Answer: A

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 # 31
A programmer writes a script to test operator precedence using the expression 3 + 4 * 2 ** 2. The goal is to evaluate the result correctly based on Python's operator hierarchy rules. What result should the script produce?

A. 0
B. 1
C. 2
D. 3

Answer: A

Explanation:
Exponentiation is evaluated first, so 2 ** 2 equals 4. Then multiplication 4 * 4 equals 16. Finally, addition is performed: 3 + 16 results in 19.

NEW QUESTION # 32
You have collected sales data and want to compute the average using the NumPy library.
Which option correctly shows how to install NumPy and use it in your code to perform this task?

A. To install NumPy:
from pip install numpy
Then run this code:
import numpy as np
data = np.array([10, 20, 30])
print(np.mean(data))
B. To install NumPy:
pip install numpy as np
Then run this code:
import np
data = np.array([10, 20, 30])
print(np.mean(data))
C. To install NumPy:
pip install numpy
Then run this code:
import numpy as np
data = numpy.arr([10, 20, 30])
print(numpy.mean(data))

Answer: A

Explanation:
NumPy is installed with pip install numpy, then imported with import numpy as np. After that, you can create an array and compute the mean using np.array(...) and np.mean(...).

NEW QUESTION # 33
You are writing a function named process_data()to read and process numerical input from a file. The function must:
- read the file data.txt,
- attempt to convert the first line into an integer,
- handle file, conversion, or index-related exceptions,
- print the value only if no error occurs,
- and always print a final message after execution.
Which implementation correctly and robustly meets all these conditions? Select the best answer.

Answer: A

Explanation:
It wraps file reading and integer conversion in a try block, catches the relevant file, conversion, and indexing exceptions, prints the value only in the no-error path using an else block, and uses a finally block to always print the final message.

NEW QUESTION # 34
......

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