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The SRM exam overview describes its CBT structure and prerequisites, while the syllabus details weekly schedule, office hours, recommended/required study materials, and the homework/quizzes/midterm/final grading weights. 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It serves as a prerequisite for the Predictive Analytics exam and assumes knowledge from probability and mathematical statistics subjects.",{"name":70,"@type":61,"acceptedAnswer":71},"How is grading determined in this course?",{"text":72,"@type":64},"Homework accounts for 19% (lowest homework score dropped), participation for 1% via an actuarial science speaker series, quizzes for 10%, midterms for 40% (20% each), and the final exam for 30%. Plus-or-minus grading is used and exams are closed-book.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},398905,1790717203,{"code":4,"msg":82,"data":83},"success",[84,88,92,95,100,105,110,115,120,123,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":93,"slug":94},70,"exam",{"id":96,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},5,"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},8,"Research & Report",30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":55,"slug":125},"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":96,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":33,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":96,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},3985747870947,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","MATH 454 Statistics for Risk Modeling  \nSpring 2026  \nInstructor: ~~  ~~g Professor Siyang Tao, PhD, ASA  \nU Office Hours: TR 10:45am- 11:45am  \n½ Office: RB 429  \nT 765-285-8681  \n􀀀 [https://sites.google.com/](https://sites.google.com/)[ ](https://sites.google.com/)view/siyangtao  \n@ [tao@bsu.edu](tao@bsu.edu) (the best way to contact me)  \nCourse Info:    \n􀀇 Prereq: MATH 321  \n􀀒 Weekly schedule U TR 2 pm-3:40 pm ½ RB 121  \nDepartment: ~~ ~~  \n􀀒 DEO: Professor Dan Rutherford U Phone: 765-285-8640  \n½ Office: RB 465  \nGA Info:    \ng Ms. Abena Broni @ [abena.broni@bsu.edu](abena.broni@bsu.edu)  \nOverview  \nThe objective of this course sequence is to develop a conceptual grasp of the statistical methodologies encompassed within the Statistics for Risk Modeling (SRM) syllabus for the SOA exam. It is structured into 13 chapters, each escalating in technical complexity:  \nChapter 1 . Simple Linear Regression (Two weeks)  \nChapter 2 . Multiple Linear Regression (Three weeks)  \n*Chapter 3 . Model Diagnostics  \nChapter 4 . Basics of Statistical Learning (Three weeks)  \nChapter 5 . Generalized Linear Models (Two weeks)  \n*Chapter 6 . Basics of Time Series Analysis  \n*Chapter 7 . Time Series Forecasting Chapter 8 . Decision Trees (Two weeks)  \nChapter 9 . Principal Components Analysis (One week)  \nChapter 10 . Cluster Analysis (Two weeks)  \n*Chapter 11 . Selected SOA Sample Questions  \n*Chapter 12 . Selected SOA/CAS Past Exam Questions Chapter 13 . Solutions  \n* optional chapters for Spring 2026 . Supplementary instructional videos will be provided for Chapters 3, 6, and 7, by the instructor.  \nExam SRM  \nExam SRM is a three and one-half hour computer-based testing (CBT) exam that consists of 35 multiple-choice questions. The learning outcome of this exam states: The goal of the syllabus for this examination is to provide an understanding of the basics of several important analytic methods. This exam is a prerequisite for the Predictive Analytics exam, which will go deeper into each of the covered techniques. The Statistics for Risk Modeling Exam assumes knowledge of probability and mathe matical statistics as covered in the Exam P and VEE Mathematical Statistics subjects. More information about Exam SRM (e.g. syllabus) can be found at this link.  \nThis course is comprehensive of all six topics outlined in the SRM exam syllabus:  \n1. Topic 1: Basics of Statistical Learning (7 .5%-12 .5%)  \n2. Topic 2: Linear Models (40%-50%)  \n3. *Topic 3: Time Series Models (12 .5%-17 .5%)  \n4. Topic 4: Principal Components Analysis (2 .5%-7 .5%)  \n5. Topic 5: Decision Trees (10%-15%)  \n6. Topic 6: Cluster Analysis (10%-15%)  \nRecommended Texts / Study Material  \nRequired Texts  \nThere are no required textbooks in this course. We shall follow closely the course lecture notes, created by the instructor, which will be made available on Canvas. The notes address all important topics required in Exam SRM and equip you with lots of intuition to understand the subject matter deeply. There are variety of examples and practice problems for exam preparation. The instructor will print out and distribute all handouts.  \nRecommended Texts  \n• Regression Modeling with Actuarial and Financial Applications, Edward W. Frees, 2010, New York: Cambridge.  \n• An Introduction to Statistical Learning, with Applications in R, James, Witten, Hastie, Tibshirani, 2013, New York: Springer.  \nGrading Scheme  \n19% Homework: Weekly assignments will be given to you by Tuesday  \nof every week. They have to be submitted by the Tuesday class of the following week, and on the same day will post the solution. The homework with the lowest score will be dropped when computing the final grade.  \nA note on collaboration: Discussion with other students on homework problems is encouraged. However, you should always write up your own solutions.  \n1% Participation: There will be an Actuarial Science Speaker Series dur  \ning the semester (date and time to be announced) . Attendance and engagement","cbCaiscEZBlSv8x0","https://ap.wps.com/l/cbCaiscEZBlSv8x0","pdf",114320,"English","# Course Information\n## Overview and Course Structure\n## Exam SRM\n## Recommended Texts / Study Material\n## Grading Scheme and Policies\n## Late Policy and Collaboration","[{\"question\":\"What topics are covered in MATH 454 Statistics for Risk Modeling?\",\"answer\":\"The course spans simple and multiple linear regression, model diagnostics, statistical learning, generalized linear models, time series analysis and forecasting, decision trees, principal components analysis, and cluster analysis, along with selected SOA sample and past exam questions and solutions.\"},{\"question\":\"What is the SRM exam and what prerequisite does it require?\",\"answer\":\"The SRM exam is a three and one-half hour computer-based test with 35 multiple-choice questions. It serves as a prerequisite for the Predictive Analytics exam and assumes knowledge from probability and mathematical statistics subjects.\"},{\"question\":\"How is grading determined in this course?\",\"answer\":\"Homework accounts for 19% (lowest homework score dropped), participation for 1% via an actuarial science speaker series, quizzes for 10%, midterms for 40% (20% each), and the final exam for 30%. Plus-or-minus grading is used and exams are closed-book.\"}]","MATH 454 Statistics for Risk Modeling - Spring 2026 Course Syllabus | PDF",1790489963,13]