These books, as a whole, serve as a “one-stop-shop” or “all-in-one guide” in introducing those at the very beginning of research, beginner university students, distance education students and students in vocational higher education (polytechnics), to the world of basic research methodology – to both the basic qualitative and quantitative methodology. At the same time, the books suits for non-mathematician and non-statistician professional researchers, professors, and lecturers of varied disciplines by providing a practical understanding of tens of possibilities of analysing the dataset. These provide a step-by-step guidance on running of statistical analyses with SPSS dialogue boxes, interpretation of results.
The set is divided into three volumes:
Volume 1: Elementary Basics leads the beginners into the basics – of research as a process, test construction, qualitative research, statistical description and – inference as well as into the basics of futures studies.
Volume 2: Multivariate Analysis teaches analyzing the quantitative dataset with the classical multivariate methods, such as Regression analysis, Factor analysis, Analysis of Variance, and Discrimination – and Classification analysis. The practical part is illustrated by using SPSS software.
Volume 3: Advanced Analysis teaches advanced methods in analyzing a quantitative dataset, with Non-parametric statistics, Experimental studies, Multi-level modeling, Structural Equation Modeling (SEM) and Path Modeling as well as Survival analysis.
These are the FIRST English language editions of the original Finnish handbook (4th edition of which was published in 2011), which is used as a textbook in almost all universities in Finland and in 26 different domains including Education, Special Education, Psychology, Sociology, Nursing, Marketing, Statistics, Military, and Sports. It has served the Finnish readers as a “one-stop shop” guide for scholars at UG level, distance education and in vocational higher education; faculty and professional researchers of varied disciplines; and also to those seeking a practical understanding of analyzing the dataset.