Analysis of Research Data Quantitative and Qualitative

Abstract

Data analysis is a useful part of research problems in order to provide data that has meaning and meaning as objective answer information.  The use of tools in the analysis is largely determined by sharpness and accurate accuracy in drawing conclusions.  For this reason, there needs to be insight and understanding in various analytical techniques.  Data analysis techniques are generally divided into two parts, namely quantifiable research data analysis and qualitative research data analysis.  Quantitative data analysis techniques consist of descriptive analysis and inferential analysis. Descriptive presentation can be presented in the form of diagrams, tables, modes, mean, median, standard intersections and ranges in a number value. For inferential analysis consists of correlation test, chi square test, linear regression and comparative testing.  While qualitative, namely interpretative approach, social anthropological approach and collaborative social research approach.  Testing the validity of data in qualitative research includes tests of credibility, transferability dependability and confirmability.