Pemetaan Kesalahan Penelitian Kuantitatif pada Mahasiswa Pendidikan Agama Islam

Based on researcher’s observation on PAI undergraduate student’s thesis that used quatitative research method, there are many statistical calculation mistakes. Those mistakes happened in many students’thesis. Students’ habit who prefer copying the stage of statistics computation on he previous thesis than studying statistics book. In this research, it is mapped statistics mistakes in PAI students’ thesis using quantitative research in XXV until XXX graduation period. In six recent graduation period, PAI FITK IAIN Surakarta have passed 607 students. The result of this research is that generally there are two mistakes in statistics, as follows. One, the lack of understanding on statistics concept covering: (a) mistake in making frequency distribution as part of the stage of describing data, (b) mistake in processing the result of Chi Quadrate as normality test, (c) unit analysis that is used up till now is not sufficient, (d) mistake in choosing statistics analysis tool, (e) the existence of outlier and influential observation in data impact significnstly the result of correlation analysis and linie regression analysis. Two, the urgency of using calculation tool in the form of statistics program consisting of mistake in writing statistics formula and mistake in calculation process.Keywords: Quantitative Research, Thesis

Influence diagnostics for multivariate growth curve models

Research has shown that in mixed effect longitudinal models, influential observations can have a large effect on the estimates of subject-specific parameters. Furthermore, they cannot always be detected by the classical Cook’s distance due to potentially large between subject variation. Thus, influential observations should be approached by conditioning on the subjects. However, no rigorous approach has been developed for influential observation detection for multivariate longitudinal mixed models where more than one response is measured for each subject at each time point. We propose a multivariate conditional Cook’s distance for this more general situation. Examples are given to illustrate how the influential observation in one characteristic changes the effects of both characteristics.