@inproceedings{GrabingerMottok, author = {Grabinger, Lisa and Mottok, J{\"u}rgen}, title = {On selecting hypothesis tests for group differences}, series = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, booktitle = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, publisher = {IATED}, doi = {10.21125/iceri.2024.0272}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-78200}, pages = {702 -- 712}, abstract = {Deciding on the right method of analyzing empirical research data can be difficult - especially when it comes to choosing specific methods of inferential statistics, where there is often not one right way, but a variety of valid options (e.g., using an ANOVA or its non-parametric alternative for data that is not perfectly normally distributed). Novice researchers not only lack the experience to know when a particular hypothesis test is appropriate, but struggle to find suitable literature to familiarize themselves (i.e., literature that is not too superficial, yet comprehensible). With the present article we provide a remedy following the didactic method of scaffolding: We present a systematization of the most elementary inferential statistical methods, namely hypothesis tests for group differences. We start by explaining basic terms (e.g., independent variable) and then give step-by-step instructions for choosing a proper hypothesis test based on data properties, implementing it from scratch, and reporting or interpreting its results. With these practical cookbook-like guidelines, this article serves as a concise starting point for young researchers entering the field of empirical research, as a valuable resource for their instructors, and as a basis for automating statistical procedures in a software system.}, language = {en} }