Essay - Statistics-multivariate Analysis Research Data Collected Using the Quantitative Approach can...

Statistics-Multivariate Analysis

Research data collected using the quantitative approach can be analyzed and interpreted in different ways, using either the univariate, bivariate, or multivariate analysis.

***** analysis looks at the relationship between two variables. It is commonly analyzed and interpreted with ***** aid of the cross-tabulation or cross-tab, allowing the researcher to check the interaction ***** the two variables under study. The variables under study are called the independent (or predictor) variable and the dependent (or outcome) *****. The interaction between the two ***** reflected in the *****, and each ***** ***** be expressed ***** either frequencies (raw count) or percentages, or both. It is critical in bivariate analysis to establish whether the relationship observed is significant or not. Determining the significance ***** the relationship is important since it (significance) will determine whether percentage differences in the results ***** worth analyz*****g or not. (However, the researcher may opt ***** look into ***** differences even if the relationship ***** not significant, for directional or diagnostic use only.) Multivariate analysis, meanwhile, ***** at the relationship of more than two (2) variables. What makes this form ***** statistical ***** useful is that it provides both breadth and depth in *****ing at ***** rel*****ionship among the variables ***** study, which could not have been observed when ***** analysis is used. Analyzing more than two variables is a rigorous and complex process, ***** is why *****re are ***** techniques ***** under ***** analysis, such as multiple regression, discriminant *****, canonical correlation, factor analysis, and cluster *****, among others.

In multivariate analysis, dependence and interdependence techniques are used, ***** having *****s own objective. Under the dependence technique, multivariate analysis looks at the relationship between a variable or a set of *****s *****ssigned as ***** dependent variable(s), ***** the other set ***** ***** assigned as independent variable(s). That is, the relationship being analyzed is the ***** of ***** Xs, which will explain or predict the dependent variables Ys. An example of an application ***** this technique is *****, wherein ***** ***** ***** two sets of ***** is ***** only analyzed based on its nature and strength, but also inf*****ms the ***** about the predictive power ***** the ***** on the Ys. Through regressi*****, the researcher can also identify the contri*****ion of one or more variable in the independent variables set Xs in ***** model generated.

Interdependence technique in multivariate analys***** ***** at the relationship ***** ***** rather than looking at two different sets of variables categorized as dependent or independent variables. That is, interdependence technique treats ***** analyzes the variables ***** study ***** a single set. Most comm***** used analys***** using this ***** is fact***** analysis, which is mainly used for reducing and summarizing research ***** into a manageable manner. Factor analysis helps ***** ********** determine ***** explain the relationships, specifically correlations, extant among ***** variables tested. Application of this type of analysis is most useful in market research, ***** psychographic *****ors and attitude statements are often treated as one set of variables, factor analyzed to generate