Data Analysis for Business Students

Michael Xin Guo

ISBN 10: 1032796987 / ISBN 13: 9781032796987

Published by Taylor and Francis Ltd, GB, 2025

Data Analysis for Business Students: A Mind-Mapping Approach is an innovative educational resource that guides business students in mastering the essential concepts and methodologies of data analysis. This textbook's unique instructional design incorporates mind maps, a proven cognitive tool to streamline the learning experience, making complex data analysis concepts more digestible. Organised into five parts, the textbook covers an introduction to data analysis, data preparation and exploratory analysis, basic data analytics techniques, advanced data analytics techniques, and data analysis in a digital world. By integrating mind maps with practical applications and case studies, the textbook equips students with the analytical skills required to succeed in the data-rich business world.This unique pedagogical approach offers three key advantages:Simplifying complex information: Mind maps systematically organise information, making it easier for students to understand complex data analysis concepts.Improving memory retention: By linking pieces of information together, mind maps activate long-term memory and support better memory retention.Increasing student engagement: Mind maps can help students prepare for class activities, enabling a deeper understanding of the subject and allowing instructors to focus more on problem-solving skills and critical thinking.With extensive online resources, including PowerPoint slides, an instructor's manual, a quiz bank, tutorial questions, instructional videos on creating mind maps, and Python code for performing data analysis that students can access, use, and experiment with, Data Analysis for Business Students: A Mind-Mapping Approach offers a structured and accessible approach for advanced undergraduate and postgraduate business students. Seller Inventory # LU-9781032796987

Synopsis:

Data Analysis for Business Students: A Mind-Mapping Approach is an innovative educational resource that guides business students in mastering the essential concepts and methodologies of data analysis. This textbook's unique instructional design incorporates mind maps, a proven cognitive tool to streamline the learning experience, making complex data analysis concepts more digestible. Organised into five parts, the textbook covers an introduction to data analysis, data preparation and exploratory analysis, basic data analytics techniques, advanced data analytics techniques, and data analysis in a digital world. By integrating mind maps with practical applications and case studies, the textbook equips students with the analytical skills required to succeed in the data-rich business world.

This unique pedagogical approach offers three key advantages:

• Simplifying complex information: Mind maps systematically organise information, making it easier for students to understand complex data analysis concepts.
• Improving memory retention: By linking pieces of information together, mind maps activate long-term memory and support better memory retention.
• Increasing student engagement: Mind maps can help students prepare for class activities, enabling a deeper understanding of the subject and allowing instructors to focus more on problem-solving skills and critical thinking.

With extensive online resources, including PowerPoint slides, an instructor's manual, a quiz bank, tutorial questions, instructional videos on creating mind maps, and Python code for performing data analysis that students can access, use, and experiment with, Data Analysis for Business Students: A Mind-Mapping Approach offers a structured and accessible approach for advanced undergraduate and postgraduate business students.

About the Author:

Michael Xin Guo is a Senior Lecturer at the University of the West of Scotland and a Senior Fellow of the Higher Education Academy.

Bibliographic Details

Title: Data Analysis for Business Students
Publisher: Taylor and Francis Ltd, GB
Publication Date: 2025
Binding: Paperback
Condition: New