Titlebook: Conducting Quantitative Research in Education; Saiyidi Mat Roni,Margaret Kristin Merga,Julia Eliz Book 2020 The Editor(s) (if applicable)

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R. S. Milton,V. Uma Maheswari,Arul Siromoneyone phenomenon be explained by a given variable or a set of variables. Say for example, we hypothesise that access to reading materials (.) can increase reading frequency (.) among young people. Using regression, we can analyse how much variability in reading frequency is “shaped” by the level of access to reading materials.

Rinne-Test

Roman W. ?winiarski,Andrzej Skowronemporary research environments conduct research with the sole aim of producing a thesis; most of us want our findings to get out into schools, homes and communities and lead to change. An academic thesis is not always the most effective vehicle for achieving this!

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Getting Started: What, Where, Why,titative research? This chapter will provide a basic introduction into planning for educational research using quantitative methods, from thinking about what quantitative methods are about, considerations for where it is appropriate to use quantitative methods and why they may be useful in achieving your research aims.

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Conducting Research with Children and Students,qualitative approaches, such as semi-structured interviews, where we can exercise a degree of flexibility to probe the areas of our inquiry, we do not have the same wriggle room in survey-based quantitative data collection.

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Conclusion and Further Reading,d that suits the research aims, even if it can be a bit daunting at first (and yes, imagine us as fairly stereotypical visual arts and English teachers/researchers who thought it would be a good challenge to learn statistics – naturally, we were terrified).

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ts in quantitative research.Provides educational researchersThis 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-parametr

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https://doi.org/10.1007/978-3-662-65303-6e normally referred to in statistics: ratio, interval, ordinal, and nominal data. Further discussions on the data types can be found in Sect. 4.1. It is very important to determine the data types as these (and the nature of our sample) determine the statistical tests suitable for a given research objective.

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Hanin Abdulrahman,Jason Steggless found that the correlation is statistically significant and strong, we can conclude that both items move together. This finding allows the store owner to manage the inventory level of sunglasses based on the trend in the sale of balls, or vice versa.

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Data Types and Samples,e normally referred to in statistics: ratio, interval, ordinal, and nominal data. Further discussions on the data types can be found in Sect. 4.1. It is very important to determine the data types as these (and the nature of our sample) determine the statistical tests suitable for a given research objective.