Actuarial Statistics 1

Overview

This course provides an introduction to probability and statistics for actuarial students. The first part consists of lectures on random variables and distributions such as uniform and binomial, geometric, negative binomial, Poisson, hypergeometric, continuous uniform, exponential, gamma, Chi-square, beta, normal, log-normal, F, and t distributions. Monte Carlo Simulation is discussed in the last lecture. It is followed by three calculator tutorials (Casio 82 ES+) that focus on detailed features, statistics mode, and table mode. Actuarial Statistics 1 covers probability basics and statistics basics (central tendency, spread, and skewness). R is used to simulate values and data analysis is done in the form of scatter plots. The central limit theorem and maximum likelihood estimation are discussed and derived intuitively.

Syllabus

CS1: Lecture 1: Random Variables.
CS1: Chapter 1- Lecture 1: Uniform and Binomial Distribution.
CS1: Chapter 1- Lecture 2: Geometric, Negative Binomial, Poisson, Hyper-geometric distributions.
CS1: Chapter 1- Lecture 3: Continuous Uniform& Exponential Distribution.
CS1: Chapter 1- Lecture 4: Gamma& Chi-square distributions.
CS1: Chapter 1 - Lecture 5: Beta, Normal and Log-normal Distributions..
CS1: Chapter 1- Lecture 6: F & t distributions.
CS1 - Chapter 1 - Monte Carlo Simulation.
Calculator Tutorial 1: Casio 82 ES+ for Actuarial Students- detailed features.
Calculator Tutorial 2: Statistics Mode on Casio 82ES+.
Calculator Tutorial 3: Table Mode on Casio 82ES+.
CS 1: Actuarial Statistics 1: Probability Basics.
CS1: Actuarial Statistics 1: Statistics Basics (Central Tendency, Spread, Skewness- with logic).
CS1: Simulating Values in R.
CS1: Data Analysis - Scatter Plots.
CS1: Data Analysis - Scatter Plots.
Central Limit theorem - Derived & Explained Intuitively (CS1).
Maximum Likelihood Estimation - Derived & Explained Intuitively.