The test found the presence of correlation, with most significant independent variables being education and promotion of illegal activities. Now, the next step is to perform a regression test.
analyse with SPSS, exploratory model analysis, result interpretation, spss intermediateCorrelation is a statistical measure that helps in determining the extent of the relationship between two or more variables or factors.
correlation, data analysis and conclusion, result interpretation, spss intermediate, spss procedureThis article, discusses and interprets the rest of the results from Malmquist DEA. Furthermore, the analysis of Malmquist index summaries for both output and input frontiers are interpreted.
DEA module, malmquist dea, result interpretationMalmquist productivity index evaluates the efficiency change over time as mentioned by Färe, Grosskopf, & Margaritis, (2011). However, Malmquist productivity index literature has been uneven with some authors assuming constant returns to scale and others allowing for variable returns to scale.
DEA module, malmquist dea, result interpretationThe previous article illustrated the manual data entry procedure to facilitate data analysis for performing meta-analysis in comprehensive meta analysis (CMA) application.
CMA, CMA analysis, result interpretationThe meta-analysis results involve basic summary statistics, forest plots and model statistics. Besides these, also funnel plot can be obtained to study publication bias amongst the studies in the analysis.
CMA, CMA analysis, result interpretationIn the previous article on Linear Regression using STATA, a simple linear regression model was used to test the hypothesis. However the linear regression will not be effective if the relation between the dependent and independent variable is non linear.
regression analysis, result interpretation, STATA for data analysisLinear regression analysis is conducted to predict the dependent variable based on one or more independent variables.
regression analysis, result interpretation, STATA for data analysis