Undergraduate Courses

Overview

Welcome to the Undergraduate Statistics and Actuarial Science program! Our courses are designed to provide a strong foundation in statistical theory, data analysis, and risk management, preparing students for dynamic careers in fields like finance, insurance, and data science. Through a blend of rigorous coursework, hands-on experience, and real-world applications, our program equips students with the analytical skills and practical knowledge needed to tackle complex problems and make informed decisions in today's data-driven world. Whether you're interested in pursuing a career as an actuary, a statistician, or a data analyst, our program offers the tools and expertise to help you succeed.

 

Course Code Title
STAT 112 INTRODUCTION TO STATISTICS AND PROBABILITY II

Credit Hours - 3

Overview

This course is aimed at enhancing students understanding of basic principles in Statistics and Probability. Relative frequency function, Introduction to probability distributions, some univariate probability distributions; Bernoulli, Binomial, Poisson, Uniform distributions. Simulation of random variables from probability distributions; Bernoulli, Binomial, Uniform distributions using (R, Minitab and Stata): mean, variance, mode of probability distribution. Writing simple codes  to generate  discrete  random values of  the  Bernoulli, Binomial  and  Poisson distributed  random  variables. One hour Lab session  a  week  will be  organized  for students.                     

 
STAT 111 INTRODUCTION TO STATISTICS AND PROBABILITY I

Credit Hours - 3

Overview

This course introduces students to basic principles in Statistics and Probability. The definition, reduction and interpretation of data. Introduction to basic concepts of Probability; Random Events and Random Variables, and Bayes Theorem. Students will be given overview of computational statistics and an introduction to the computing environment. The statistical software (R, Minitab and Stata) will be used to execute concepts learned in class. Methods of data description and analysis using R, Minitab and Stata: emphasis on learning statistical methods and concepts through hands-on experience with real data. One hour laboratory session  a  week will  be  organized for students.