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Descriptive and Inferential Statistics in Undergraduate Data Science Research Projects

In: Advances in Statistical Methodologies and Their Application to Real Problems

Author

Listed:
  • Malcolm J. D'Souza
  • Edward Brandenburg
  • Derald Wentzien
  • Riza Bautista
  • Agashi Nwogbaga
  • Rebecca Miller
  • Paul Olsen

Abstract

Undergraduate data science research projects form an integral component of the Wesley College science and mathematics curriculum. In this chapter, we provide examples for hypothesis testing, where statistical methods or strategies are coupled with methodologies using interpolating polynomials, probability and the expected value concept in statistics. These are areas where real-world critical thinking and decision analysis applications peak a student's interest.

Suggested Citation

  • Malcolm J. D'Souza & Edward Brandenburg & Derald Wentzien & Riza Bautista & Agashi Nwogbaga & Rebecca Miller & Paul Olsen, 2017. "Descriptive and Inferential Statistics in Undergraduate Data Science Research Projects," Chapters, in: Tsukasa Hokimoto (ed.), Advances in Statistical Methodologies and Their Application to Real Problems, IntechOpen.
    • Handle: RePEc:ito:pchaps:108034
    DOI: 10.5772/65721
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    Cited by:

    1. Malcolm J. D’Souza & Katelynn Fry & Lyndsey Koyanagi & Andrew Shepherd, 2020. "COVID-19 Impacts at a Small Mid-Atlantic Liberal-Arts College with Implications for STEM Education," Journal of Education and e-Learning Research, Asian Online Journal Publishing Group, vol. 7(4), pages 407-420.

    More about this item

    Keywords

    Wesley College; STEM; undergraduate research; solvolysis; phenyl chloroformate; benzoyl chloride; benzoyl fluoride; benzoyl cyanide; Grunwald-Winstein equation; transition-state; addition-elimination; multiple regression; time-series; Ebola; polynomial functions; probability; expected value;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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