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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Lists, tuples, sets, dictionaries
  • 2. Variables, numbers, strings, booleans
- 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
Topic 2: Introduction to Data and Data Analysis Concepts22.5%- Data types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
- Basic statistical concepts
  • 1. Descriptive vs inferential statistics
  • 2. Population, sample, variable, observation
- Data lifecycle and ethical considerations
  • 1. Data collection, storage, processing, usage, and sharing
  • 2. Privacy, security, bias, and fairness in data
- Definition and classification of data
  • 1. Difference between data, information, and knowledge
  • 2. Role of data in decision-making and business
  • 3. Process of turning raw data into insights
Topic 3: 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. Clarity, simplicity, and accuracy
  • 2. Choosing appropriate chart types
Topic 4: Working with Data and Performing Simple Analysis25%- 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
- Data acquisition and loading
  • 1. Importing data from external sources
  • 2. Reading text, CSV, and structured files
- Data cleaning and preparation
  • 1. Filtering, sorting, transforming data
  • 2. Formatting and standardizing values
  • 3. Handling missing values, duplicates, and errors

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q21-Q26):

NEW QUESTION # 21
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?

Answer: C

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 # 22
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 # 23
A dictionary is defined as d = {"a":1, "b":2}. The programmer accesses d["c"]. What happens when this line executes?

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 # 24
A script attempts to divide two numbers using / and //. The values are 7 and 2. The developer wants to understand the difference between true division and floor division. What are the results respectively?

Answer: D

Explanation:
The / operator performs true division, returning a float result of 3.5. The // operator performs floor division, truncating the decimal part and returning the integer value 3.


NEW QUESTION # 25
A financial technology company is reviewing its data practices to ensure legal and ethical compliance.
Which of the following actions would support responsible data handling and align with regulations like GDPR, HIPAA, and CCPA? (Choose two.)

Answer: B,C

Explanation:
Encrypting stored and transmitted data protects sensitive information from unauthorized access and supports regulatory requirements for data security. Providing clear explanations of data usage and obtaining explicit consent ensures transparency and aligns with core principles of data protection regulations such as lawful processing and user rights.


NEW QUESTION # 26
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