Expanded explanation on time complexity and Big O notation

[Barnab1]

Hi everyone 👋,
I'm happy to contribute to this project!

Proposed changes

This PR expands and clarifies the “Time Complexity” section to make the content more accessible for beginners.
This makes the section more approachable for readers who are new to algorithm analysis.
It introduces a more intuitive explanation of how time complexity is measured (in steps, not time units) and provides a smoother transition to Big O notation.

It also adds a brief reference to logarithms to help readers understand why they often appear in algorithm analysis.

Types of changes

• Proofreading (fix spelling, grammar, punctuation, accuracy) Proofreading
• New content (new section, new readme, etc.)
• Modifications (modifying existing content)
• Other (please describe)

Checklist

• Tested any code that was added/modified in this PR
• Added external links (book reference)
• Added internal links
• Added images
• Added videos
• Added code snippets

Further comments

This change enhances the educational value of the “Time Complexity” section by explaining it in simple, conceptual terms before introducing mathematical notation.

The explanation was adapted from “A Common-Sense Guide to Data Structures and Algorithms” by Jay Wengrow, to ensure accuracy and clarity for beginners.

Adding your name to the contributor's list

After this PR is merged, I'll comment:
@all-contributors please add @Barnab1 for content

Reviewers:

• @username