tekijä: Tanja Tuulikki Välisalo Viimeisin muutos tiistai 03. toukokuuta 2022, 12.51


keha_analyysimenetelmat data collection Qualitative Analysis Quantitative Analysis Phenomenological Analysis Phenomenographical Analysis Hermeneutic Analysis Semiotic Analysis Narrative Analysis Discoursive Analysis Conversation Analysis Discipline-Specific methods Close Reading grounded theory Network Analysis Typification Thematic Analysis Classification Descriptive Statistical Analysis correlation analysis Causal Analysis Time-series Analysis he Delphi Method


You may use classification when the data consists of a large group of research objects. You outline and divide the group into classes of objects (sharing similar qualities or resemblances), so you can explain and describe the composition and essence of the group. Variations in classification exist as scientific methods, which obey a degree of logic sliding between exact and imprecise. Examples of classification based on imprecise logic are: principal components analysis, cluster analysis and typologicizing. Since statistical methods are necessary for effective classification, you need to know the basics of both quantitative and qualitative methods of analysis.

Read more on classification from the links below:

Routio, Pentti, 2007. Classification. Arteology, the science of products and professions. The Aalto University School of Art and Design. 

Statistical Classification. Wikipedia, The Free Encyclopedia.

Principal Components Analysis. Wikipedia, The Free Encyclopedia.

Cluster Analysis. Wikipedia, The Free Encyclopedia.

What is Cluster Analysis? Electronic Statistics Textbook. Statsoft.

Typology (archaeology). Wikipedia, The Free Encyclopedia.