It takes the average reader to read Business Analytics in Practice by Nitin Kumar Saxena
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Today, many businesses are innovating through digital disruptions resulting in more methodical and systematic approaches toward business decisions. The technology integrations are leading to the capturing of zettabytes of data which was not happening earlier. This has given rise to business analytics through which big data are analyzed leading to data-driven decision-making. For understanding the right variables, organizations develop scorecards and dashboards, though the metrics or variables included in such scorecards and dashboards may not be statistically significant. There are few statistical methods to develop models with the most significant predictor variables. Among the methods available, stepwise regression is one of the preferred methods by social science researchers as it is a step-by-step method, which includes the addition of the variables (Forward selection), removal of variables (backward elimination), or a combination of both. The principal benefit of using this statistical technique is that it considers all the available variable in the given business problem and statistically test them for inclusion or exclusion resulting in the most significant model to arrive at the solution to the given business problem. Stepwise regression is used where the theory formulated is not clearly defined or there is an ambiguity in understanding the potential predictor variables for an event or case. The stepwise regression has a few drawbacks also, including bias in parameter estimation, inconsistencies among model selection algorithms, an inherent (but often overlooked) problem of multiple hypothesis testing, and an inappropriate focus or reliance on a single best model.This guide discusses what is stepwise regression, its types, application, advantages, and also demonstrate a step-by-step process to undertake the stepwise regression in SPSS. Developing an understanding of the stepwise regression from this guide will help you to apply the stepwise regression and create the best-fit model of regression for theory formulation or for further studies.
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