TECHNIQUES FOR COMPUTER INTERPRETATION FOR MEAN COMPARISON IN RESEARCH

Abstract

Means comparison is the inferential statistical summary of attributes of samples or subjects under study, this then can be used to refer to the characteristics of the population. Mean comparison is popular statistic, which is used in research, such as t-test and analysis of variance (One-way ANOVA). Using statistics for mean comparison are based on the principle of objective research, number of samples and variables must be interval scale or ratio scale. Principles for data interpreting for mean comparison are as follows: interpret data in accordance with objective research, use understandable language, interpret numeric result display, and translate only the key findings. The researcher should have knowledge and understanding of the assumption for the use of statistics and data interpretation correctly. Techniques for computer interpretation for mean comparison in research is very important because it will make the research accurate and reliable.