or
Bibliography for:
Approved 27 Feb 2026

Thesis for Master Degree in Micro data analysis (MI4001)

V3NZF (Spring 2026, 75%, Day, Normal, Borlänge, Round 1, ORD)

Literature

  • Yu, B., & Barter, R. L. (2024). Veridical data science : the practice of responsible data analysis and decision making (1st ed.). Cambridge, Massachusetts: The MIT Press. ISBN: 9780262049191
    Book / Anthology
  • Bruce, P. C., Bruce, A., & Gedeck, P. (2020). Practical statistics for data scientists : 50+ essential concepts using R and Python (Second edition.). Sebastopol, CA: O'Reilly Media, Inc.. ISBN: 9781492072942
    Book / Anthology
  • Creswell, J. W., & Creswell, J. D. (2018). Research Design:Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.
    Book / Anthology
  • Provost, F., & Fawcett, T. (2013). Data Science for Business: WhatYou Need to Know About Data Mining and Data-AnalyticThinking (1st ed.). O’Reilly Media.
    Book / Anthology
  • Swales, J. M., & Feak, C. B. (2012). Academic Writing for GraduateStudents: Essential Tasks and Skills (3rd ed.). University ofMichigan Press.
    Book / Anthology