Description

Book 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 six parts, the textbook covers introductory topics, data collection and presentation, basic and advanced data analytics techniques, special issues in data analysis, and data analysis in the digital world. By integrating mind maps with practical applications and real-world case studies, the textbook equips students with the analytical acumen necessary to navigate 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 stimulate the brain, activating long-term memory, and enhancing 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 practical skills and critical thinking.

With extensive online resources, including PowerPoint slides, an instructor's manual, a quiz bank, and tutorial questions, as well as instructional videos on creating your own mind maps, Data Analysis for Business Students: A Mind-Mapping Approach offers a fresh and invigorating look at the subject which will be highly valued by business students at advanced undergraduate and postgraduate level.

Data Analysis for Business Students

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    £37.99

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    RRP £39.99 – you save £2.00 (5%)

    Order before 4pm today for delivery by Tue 9 Jun 2026.

    A Paperback by Michael Xin Guo

    1 in stock


      View other formats and editions of Data Analysis for Business Students by Michael Xin Guo

      Publisher: Taylor & Francis
      Publication Date: 7/31/2025
      ISBN13: 9781032796987, 978-1032796987
      ISBN10: 1032796987

      Description

      Book 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 six parts, the textbook covers introductory topics, data collection and presentation, basic and advanced data analytics techniques, special issues in data analysis, and data analysis in the digital world. By integrating mind maps with practical applications and real-world case studies, the textbook equips students with the analytical acumen necessary to navigate 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 stimulate the brain, activating long-term memory, and enhancing 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 practical skills and critical thinking.

      With extensive online resources, including PowerPoint slides, an instructor's manual, a quiz bank, and tutorial questions, as well as instructional videos on creating your own mind maps, Data Analysis for Business Students: A Mind-Mapping Approach offers a fresh and invigorating look at the subject which will be highly valued by business students at advanced undergraduate and postgraduate level.

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