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Survival Analysis in Microsoft Excel without Add-ins
內容大綱
Survival analysis refers to a collection of statistical techniques used to analyze the occurrence and expected timing of events. Survival analysis can provide not only the probability of an event of interest occurring, but also the time at which the event is likely to occur. A particularly useful application of survival analysis is in the area of "customer churn"—the loss of clients or customers—which is a major concern in many industries. This note introduces survival analysis and discusses two approaches to examine customer churn: the Kaplan-Meier estimator and the Cox proportional hazards model. Instructions are provided on how to build these models in Microsoft Excel, without add-ins.
學習目標
This note is well suited for undergraduate and graduate courses dealing with data science, data mining, or analytics. The aim of this note is to:<ul><li>Introduce survival analysis to a business audience.</li><li>Inform readers of the applications of survival analysis in different contexts and industries. </li><li>Compare with classical techniques such as linear regression.</li><li>Guide readers through the construction of two popular survival models in Microsoft Excel in order to analyze and draw insights from customer churn data.</li><li>Demonstrate how statistical techniques can bolster management decision-making.</li><ul>