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Learn how to perform logistic regression using R and Excel. Learn the most in-demand business, tech and creative skills from industry experts. Start my free month. Applying Logistic Regression Models on Business Cycle Prediction Ulf Hamberg and David VerstГ¤ndig The prediction of business cycles in the real economy is an important but challenging task. For this purpose we construct a logistic regression model that we вЂ¦

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Logistic Regression is the equivalent of linear regression to use when the target (or dependent) variable is discrete i.e. not continuous; Logistic Regression is ideally suited for business analytics applications where the target variable is a binary decision (fail-pass, response-no response, etc) The predictors can be either continuous or categorical Applications. Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score , which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression.

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