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Interdisciplinary Statistics in Mexico

Posted By: AvaxGenius
Interdisciplinary Statistics in Mexico

Interdisciplinary Statistics in Mexico: AME Virtual Meeting, September 10–11, 2020, and 34 FNE, Acatlán, Mexico, September 22–24, 2021 by Isadora Antoniano-Villalobos, Ruth Fuentes-García, Lizbeth Naranjo, Luis E. Nieto-Barajas, Silvia Ruiz-Velasco Acosta
English | PDF,EPUB | 2022 | 234 Pages | ISBN : 3031127773 | 75.5 MB

​The volume includes a collection of peer-reviewed contributions from among those presented at the FNE, the main conference organized every two years by the Mexican Statistical Society (AME), and the 2020 AME Virtual Meeting. Statistical research in Latin America is prolific and research networks span both within and outside the region. As much of the work is typically carried out and published in Spanish, a large portion of the interested public is denied access to interesting findings, and the goal of this volume is therefore to provide access to selected works from Mexican collaborators and their international research networks to a wider audience. It may be especially attractive to academics interested in the latest methodological advances, while professionals from other disciplines may also find value in these new tools for data analysis. In 2021, the conference broadly focused on the interdisciplinary aspects of Statistics.

Conducting Quantitative Research in Education

Posted By: AvaxGenius
Conducting Quantitative Research in Education

Conducting Quantitative Research in Education by Saiyidi Mat Roni
English | EPUB | 2020 | 206 Pages | ISBN : 9811391319 | 72.45 MB

This book provides a clear and straightforward guide for all those seeking to conduct quantitative research in the field of education, using primary research data samples. While positioned as less powerful and somehow inferior, non-parametric tests can be very useful where the research can only be designed to accommodate data structure which is ordinal, or scale but violates a normality assumption, which is required for parametric tests. Non-parametric data are a staple of educational research, and as such, it is essential that educational researchers learn how to work with these data with confidence and rigour.