Techniques for Data Interpreting for Using Correlation and Regression in Research

Abstract

 Correlation and regression are inferential statistics for studying the correlation between 2 variables or more than 2 variables. Correlation analysis frequently used in social sciences research are simple correlation, multiple correlation, simple regression and multiple regression. Using statistics for the correlation analysis are based on principles of objective research and hypothesis, numbers of variables and data from measurement. Principles for data interpreting for correlation and regression analysis are as follows: the interpretation should be in accordance with research objective and hypothesis, the researcher should use simple and understandable language, interpreted the numeric appeared and focus only on key findings. The researcher should have knowledge and understanding basic assumptions for the use of statistics and data interpretation correctly. Using techniques for data interpreting for using correlation and regression in research is very important because it will make the research be accurate and reliable.