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The course builds on prior mathematical statistics and actuarial preparation, covering SRM Exam Topic 1 (Basics of Statistical Learning) and Topic 2 (Linear Models). Students learn tools for constructing and evaluating predictive models, with emphasis on linear regression and generalized linear models, including fitting, variable selection, diagnostics, and prediction. Practical implementations are demonstrated using R. 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Questions about the course material, as far as possible, should be discussed during office hours.)  \n􀀃 Personal homepage: [https://sites](https://sites). google. com/site/ambroseloyp  \n(Feel free to visit it from time to time for latest updates on my courses and books!)  \n􀀃 Office hours:  \nWednesday and Friday : 3:30 p.m.– 4:30 p.m.  \nThursday : 2:30 p.m.– 3:30 p.m.  \n(Students are free to drop by during these hours to discuss questions about the course material or concerns. I am also available by appointment if you are unable to attend my office hours. Unless otherwise announced, office hours are held in person.)  \n􀀏 Grader: Mr. Yikai Zhang  \n􀀃 Office: 266 SH  \n􀀃 Email: [yikai-zhang@uiowa.edu](yikai-zhang@uiowa.edu)  \n􀀏 Departmental Executive Officer (Chair): Professor Kung-Sik Chan, Department of Statistics and Actuarial Science  \n􀀃 Office: 241 SH  \n􀀃 Email: [kung-sik-chan@uiowa.edu](kung-sik-chan@uiowa.edu)  \nSTAT:4560 – Fall 2022 – 1– Ambrose Lo, U. of Iowa  \nCourse Syllabus  \n2 Course Description and Objectives  \nPrerequisite: C+ or above in STAT:4101 (Mathematical Statistics II) or STAT:5101 (Statistical Inference II)  \nBuilding upon your prior exposure to actuarial science and preparation in mathematical statistics, this applied statistics course for B.S. and M.S. in Actuarial Science students covers the material of the first half of the Statistics for Risk Modeling (SRM) Exam offered by the Society of Actuaries (SOA) . Specifically, it covers the following two exam topics:  \n􀀏 Topic 1: Basics of Statistical Learning (7.5-12.5% of SRM)  \n􀀏 Topic 2: Linear Models (40-50% of SRM)  \nIn this course, you will learn the general tools available for constructing and evaluating predictive models and the technical details of specific types of model, linear regression models and generalized linear models in particular (fitting, variable selection, diagnostics, prediction, etc.) . Practical implementations of these models on real data by means of the R programming language will be demonstrated to give you some hands-on data analysis experience. This is an important way to put the theory we learn in the course into practice. Although the use of R is not strictly required for Exam SRM, it is essential for the Predictive Analytics (PA) Exam, which is, to a large extent, a follow-up exam of SRM (see Section 3).  \nThe second half of Exam SRM will be covered in STAT:4561 Statistics for Risk Modeling II, which will be offered in Spring 2023 .  \n3 Actuarial Exams related to SRM  \nExam PA. As noted earlier, Exam SRM is an important stepping stone to Exam PA, which is a five hour and fifteen minutei computer-based exam offered twice a year, in April and in October. In essence, Exams SRM and PA are about the same subject, but test it differently. While Exam SRM emphasizes the theory underlying different predictive analytic techniques, Exam PA applies and illustrates the theory you learned in Exam SRM to real data by means of computer-based implementations using R. Some practical considerations are also presented. You will be given a business project with a series of exam tasks and asked to write your responses in Microsoft Word addressing those tasks. After taking Exam PA, you will see the predictive models you learned in Exam SRM in action and gain a much more thorough understanding.  \nExam MAS-I. Students who aspire to specialize in property and casualty insurance will take the Modern Actuarial Statistics-I (MAS-I) Exam of the Casualty Actuarial Society (CAS), Section C (Extended Linear Models; 30-50% of the exam syllabus) of which overlaps substantially with  \nExam","cbCaivFdK8wVlb0e","https://ap.wps.com/l/cbCaivFdK8wVlb0e","pdf",385362,"English","# Course Description and Objectives\n## Actuarial Exams related to SRM\n## University-Earned Credit Program\n## Textbook","[{\"question\":\"What prerequisites are required for STAT:4560?\",\"answer\":\"Students need a C+ or above in STAT:4101 (Mathematical Statistics II) or STAT:5101 (Statistical Inference II).\"},{\"question\":\"Which SRM Exam topics does STAT:4560 cover?\",\"answer\":\"STAT:4560 covers Topic 1: Basics of Statistical Learning (7.5–12.5%) and Topic 2: Linear Models (40–50%) of the SRM syllabus.\"},{\"question\":\"How does STAT:4560 relate to Exam PA and SRM?\",\"answer\":\"Exam SRM is a stepping stone to Exam PA, which applies SRM theory to real data using R-based, computer-based implementations. STAT:4561 covers the second half of SRM in Spring 2023.\"}]","STAT:4560 Statistics for Risk Modeling I Course Syllabus - Fall 2022 | PDF",1790271468]