Loss Models: from Data to Decisions + (one Year Online): Preparation for Actuarial Exam C/4 Wrapper Set (Wiley Series in Probability and Statistics)

by Stuart A Klugman, Harry H Panjer, and Gordon E Willmot

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"eKlugman" "ExamPrep" is an exciting new online product designed to help actuaries improve their examination skills. "eKlugman" "ExamPrep" provides an interactive method for working most of the exercises in "Loss Models" including, as well as providing, hints and step-by-step solutions. Many of the questions have a feature that makes random changes so that the same question can be worked more than once. The questions cover simulations, log normal distributions, aggregate loss models and operational risks, among a host of other actuarial topics. "eKlugman" "ExamPrep" also includes multiple forms of simulated exams with questions specially written for exam C/4 practice. The product features a built-in record keeping system in order to reinforce further practice and promote customization of study skills. This online product presents useful tips in understanding the test material, and it aids users in achieving specific exam goals. The material is a 'must have' for all aspiring and practicing actuaries who desire a fast and efficient alternative to using the traditional coursebook approach. Price includes 6-month access/subscription. Once purchased, the product is nonreturnable.After ordering, customers will be mailed a card that contains their registration code which is needed to access the "eKlugman ExamPrep" website.Also, check out the NEW enhanced version, Loss Models Online 3e. This product serves the same needs as ExamPrep, but with updated content and enhanced functionality to further improve your knowledge when preparing the the Actuarial Exam.
  • ISBN10 111821028X
  • ISBN13 9781118210284
  • Publish Date 6 October 2011
  • Publish Status Out of Print
  • Out of Print 4 September 2012
  • Publish Country US
  • Imprint John Wiley & Sons Inc
  • Edition 3rd Revised edition
  • Pages 760
  • Language English