PCED-30-02 Exam Answers - Guaranteed PCED-30-02 Passing

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Introduction to Data and Data Analysis Concepts22.5%- Data lifecycle and ethical considerations
  • 1. Privacy, security, bias, and fairness in data
  • 2. Data collection, storage, processing, usage, and sharing
- Basic statistical concepts
  • 1. Descriptive vs inferential statistics
  • 2. Population, sample, variable, observation
- Definition and classification of data
  • 1. Process of turning raw data into insights
  • 2. Difference between data, information, and knowledge
  • 3. Role of data in decision-making and business
- Data types and measurement scales
  • 1. Nominal, ordinal, interval, ratio scales
  • 2. Qualitative vs quantitative data
Topic 2: Data Visualization and Communication20%- Interpreting and presenting results
  • 1. Reporting findings clearly and concisely
  • 2. Deriving conclusions and insights
- Creating basic visualizations
  • 1. Line charts, bar charts, histograms, pie charts
  • 2. Using text and simple plotting tools
- Principles of effective data visualization
  • 1. Choosing appropriate chart types
  • 2. Clarity, simplicity, and accuracy
Topic 3: Working with Data and Performing Simple Analysis25%- Data acquisition and loading
  • 1. Reading text, CSV, and structured files
  • 2. Importing data from external sources
- Data cleaning and preparation
  • 1. Formatting and standardizing values
  • 2. Filtering, sorting, transforming data
  • 3. Handling missing values, duplicates, and errors
- Exploratory data analysis
  • 1. Identifying patterns, trends, and outliers
  • 2. Calculating mean, median, mode, range, variance, standard deviation
- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
Topic 4: Python Basics for Data Analysis32.5%- Built-in modules for data work
  • 1. math, statistics, datetime, collections, csv
- Core Python syntax and data types
  • 1. Variables, numbers, strings, booleans
  • 2. Lists, tuples, sets, dictionaries
- Control flow and functions
  • 1. Conditional statements, loops, iteration
  • 2. Basic exception handling
  • 3. Defining and calling functions, parameters, return values
- 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 (Q48-Q53):

NEW QUESTION # 48
A Python developer is testing truth values of different data types using the bool() function. The expression bool([0]) is evaluated in the script. What result should be expected when this expression is printed?

Answer: B

Explanation:
In Python, any non-empty list evaluates to True in a Boolean context. Even though the element inside the list is zero, the list itself is not empty, so the result is True.


NEW QUESTION # 49
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

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 # 50
You are developing a temperature control module for a laboratory incubator. Your objectives are to:
- generate timestamps every 10 minutes over a 3-hour span (i.e., 0 to 180 minutes), and
- simulate five evenly spaced target temperatures between 35.0°C and 37.0°C for system calibration.
Which code snippet correctly produces both sequences using NumPy? Select the best answer.
import numpy as np

Answer: A

Explanation:
np.arange(0, 181, 10) generates timestamps from 0 through 180 in 10-minute steps (end is excluded, so using 181 includes 180). np.linspace(35.0, 37.0, 5) generates five evenly spaced temperatures including both 35.0°C and 37.0°C.


NEW QUESTION # 51
You have a list of test scores, where each entry includes a student name and a score. Some students appear more than once. You want to compute the average score for each student and store the results in a dictionary. Here's the partial code block:

Which code correctly replaces the # MISSING CODE comment to calculate the average score for each student? Select the best answer.

Answer: B

Explanation:
It iterates through each record, extracts the name and score, and uses dictionary .get() to accumulate total scores and counts per student safely, initializing missing keys to zero. This correctly enables calculation of each student's average afterward.


NEW QUESTION # 52
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: B

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 # 53
......

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