Until recently, Karl Pearson Correlation analysis was one of the most popular methods to measure linear association between two or more than two variables in a data set. For example, establishing the Karl Pearson Correlation between X variable and Y variable, where both variables belong to a single data set. Canonical Correlation Analysis (CCA), on the other hand, helps measure the correlation among variables which are in different datasets.
correlation, correlation in supervised learning, Supervised learning
Correlation analysis is conducted to examine the relationship between dependent and independent variables. There are two types of correlation analysis in STATA.
correlation, empirical analysis with econometrics, regression analysis, regression with stata, STATA for data analysis
This article explains the different correlation and regression analysis values that are generated after conducting the tests. Their meaning, importance and how to interpret them are explained here.
correlation, regression analysis, spss intermediate
Path analysis model is a statistical method used for establishing a causal relationship between variables. It is used when there are multiple variables in a study.
analysing with amos, SEM module
Confirmatory Composite Analysis (CCA) is a type of Structural Equation Modeling (SEM) analysis which develops composites to assess the relationship between variables.
analysing with amos, SEM module
This article demonstrates through a case study how to build a Confirmatory factor analysis model in SPSS Amos software.
analysing with amos, SEM module
Pearson correlation is popularly used for social sciences data like primary data but rarely used for secondary data in SPSS.
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