Introduction to statistics in research

Abstract

As a researcher (or consumer of research) you will frequently come across statistical testing of data. This article aims to give an introductory outline to statistical methods to enable you to (i) choose appropriate statistics for your own study and (ii) offer critical comment on statistics used in journal articles or research papers.

This background knowledge will give you the ability to comment on research design adequacy, which can lead to you being able to know whether you can trust and use results in practice, or guide you in critical questioning of the validity and reliability of results, leading you to search for further evidence before implementing new suggestions into your practice.

This article is then aimed at exploring the use of statistics in quantitative studies, generally from data collected either through (i) survey data collection or (ii) criteria measurements. Criteria measurements in NLP might for example include measurement of anxiety or depression, pre and post an NLP intervention (ideally using a pre validated measurement tool which has been shown to be valid and reliable – i.e. has been shown to be accurate and repeatable over time). Another example would be looking at spelling test scores following work with pupils on the NLP Spelling Technique.