Category: Learning modules
Machine learning involves solutions to predict scenarios based on past data. Logistic regression offers probability functions based on inputs and their corresponding output.
regressions in supervised learning, Supervised learningThe Malmquist productivity index or more commonly malmquist Data Envelopment Analysis (DEA) was first incepted by the researcher Malmquist in 1953 as a quantity to be used in the analysis of consumption of inputs (Färe, Grosskopf, & Margaritis, 2011).
DEA module, malmquist deaThe purpose of this article is to explain the process of determining and creating stationarity in time series analysis. Creating a visual plot of data is the first step in time series analysis. Graphical representation of data helps understand it better.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, stationarity test, time series analysis, trend analysisPath analysis is a graphical representation of multiple regression models. In this analysis, the graphs represent the relationship between dependent and independent variables with the help of square and arrows.
regressions in supervised learning, Supervised learningThe present article takes up the datasheets for the unmatched post and pre or post design and illustrates the results with statistics. The present discussion will focus on the interpretation of the results.
CMA, CMA analysisThis is the continued article of the interpretations for variable returns to scale (VRS) from the last article. However, this article is about the summary of peers and the rest of the analysis conducted for VRS-DEA (Data envelopment analysis).
DEA module, measuring returns to scale with deaAcquaintance with different methods of entering data in the software makes the task simpler. The manual data entry included entering the raw data for the dichotomous category for the study investigating one group.
CMA, CMA analysisThe 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 interpretation