The Exam P Preparation Program

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The Exam P Preparation Program offers students a comprehensive 9 week live program with the focus to teach, coach, and guide students to master the required exam syllabus topics and reach an expert level of P/1 problem solving.

Shang Xu passed 5 ASA exams in one calendar year and has been nicknamed The Exam Prodigy. During the program, he will lead students to gain a deep conceptual understanding of P/1 syllabus topics, bridge the gap between understanding the syllabus topics and being able to approach and solve problems, share many valuable strategies, techniques, and shortcuts for solving P/1 problems, and also offer many important exam taking tactics and nuances for passing Exam P.

The Exam P Preparation
Program provides the following:

  1. Weekly 2 hour live online class lectures each Saturday which will integrate concept building and technique practicing with problem solving.  Live classes are interactive in nature and students are encouraged to ask questions of lead instructor
  2. Open Forum following each live class in which students can ask questions related to any category of syllabus topics/problem solving
  3. Weekly problem sets to reinforce topics and problem solving reviewed each week
  4. Weekly email correspondence in which students can email instructor with questions related to any category of Exam P topics/problem solving
  5. Weekly online office hours in which students can schedule times to meet privately with instructor
  6. Recordings of live class lectures made accessible to students following its completion each Saturday

*Email correspondence feature will continue until the next exam sitting

**Online office hours feature will continue until the next exam sitting

Schedule

Live Classes & Subjects

Week 1
5/2
• Discrete random variables/distributions, expected values, variance
Week 2
5/9
• Continuous random variables/distributions, expected values, variances
Week 3
5/16
• MGF, PGF, normal approximation for discrete random variables, univariate transformation
Week 4
5/23
• Conditional univariate probability, law of total conditional prob, Bayes Theorem
Week 5
5/30
• Conditional joint distribution of two variables, law of total probability as expected value, conditional variance
Week 6
6/6
• Generalized Joint distribution and joint moments, MGF, bivariate distributions
Week 7
6/13
• Variance, covariance, independence of multivariate distributions
Week 8
6/20
• Convolution, change of variables
Week 9
6/27
• I.I.D random variables, max, min, Basic Set theory and Venn diagrams

Join The Exam P Preparation Program

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