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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Visualization and Communication	20%	- Creating basic visualizations 1. Line charts, bar charts, histograms, pie charts 2. Using text and simple plotting tools - Principles of effective data visualization 1. Clarity, simplicity, and accuracy 2. Choosing appropriate chart types - Interpreting and presenting results 1. Reporting findings clearly and concisely 2. Deriving conclusions and insights
Topic 2: Working with Data and Performing Simple Analysis	25%	- Data aggregation and grouping 1. Summarizing and grouping datasets - Data acquisition and loading 1. Reading text, CSV, and structured files 2. Importing data from external sources - Exploratory data analysis 1. Calculating mean, median, mode, range, variance, standard deviation 2. Identifying patterns, trends, and outliers - Data cleaning and preparation 1. Handling missing values, duplicates, and errors 2. Filtering, sorting, transforming data 3. Formatting and standardizing values
Topic 3: Introduction to Data and Data Analysis Concepts	22.5%	- Definition and classification of data 1. Role of data in decision-making and business 2. Difference between data, information, and knowledge 3. Process of turning raw data into insights - Basic statistical concepts 1. Descriptive vs inferential statistics 2. Population, sample, variable, observation - Data types and measurement scales 1. Nominal, ordinal, interval, ratio scales 2. Qualitative vs quantitative data - Data lifecycle and ethical considerations 1. Data collection, storage, processing, usage, and sharing 2. Privacy, security, bias, and fairness in data
Topic 4: Python Basics for Data Analysis	32.5%	- Control flow and functions 1. Conditional statements, loops, iteration 2. Basic exception handling 3. Defining and calling functions, parameters, return values - Core Python syntax and data types 1. Lists, tuples, sets, dictionaries 2. Variables, numbers, strings, booleans - Built-in modules for data work 1. math, statistics, datetime, collections, csv - Introduction to NumPy 1. Arrays, basic operations, indexing, slicing

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q32-Q37):

NEW QUESTION # 32
A student writes a program using input() to collect user data, then tries to add 5 to the input value without conversion. The program crashes. What is the most likely cause of this behavior?

A. Syntax error
B. input returns string
C. input returns int
D. input returns float

Answer: B

Explanation:
The input() function always returns a string. Attempting to add an integer to a string causes a TypeError. The input must be explicitly converted using int() or float() before performing arithmetic operations.

NEW QUESTION # 33
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: A

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 # 34
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?

A. ytho
B. ythn
C. yth
D. tho

Answer: C

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 # 35
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.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))
B. import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
C. import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics
D. import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics

Answer: A

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 # 36
A teacher wants to compare the number of students in different school clubs:

Which type of chart would be most appropriate to show this comparison? Select the best answer.

A. Line chart
B. Bar chart
C. Bubble chart
D. Pie chart

Answer: B

Explanation:
A bar chart is best for comparing quantities across distinct categories, such as the number of students in each club, because it clearly shows differences in counts side by side.

NEW QUESTION # 37
......

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