Chapter 1 Introduction
Having a basic understanding of the vocabulary, notation, and ideas of matrix algebra, is important for all educational scientists who use quantitative methods in their work. The statistical and psychometric models underlying many quantitative methodologies employed in educational research rely on matrix algebra. Subsequently, educational scientists use the language and notation of matrix algebra to communicate in the scientific literature. Moreover, matrix algebra forms the bedrock of statistical computation. Having fundamental knowledge of matrix algebra can often help an educational scientist troubleshoot problems that arise in their own work, and devise solutions for those issues.
For quantitative methodologists, it is important to have a much deeper understanding of matrix algebra, as it is foundational to the computational estimation and optimization used in methodological work. Statistical programming, formulating the mathematics of quantitative methods, and even back-of-the-napkin calculations are all made easier (and more efficient) through matrix algebra.