This course equips students with basic concepts of elementary probability and statistics and their application. The primary focus is probability and its relationship with statistics. The follow-in course MAT212 Mathematical Statistics focuses entirely upon statistics.


  • Statistics: Descriptive and inferential statistics, data representation and graphing, measures of central tendency and variability, univariate and bivariate data
  • Probability: Definition, laws of probability, discrete and continuous probability, conditional probability, independent events, mutually exclusive events
  • Probability Distributions: Distributions and densities, Binomial distribution, Poisson distribution, Normal distribution, Law of Large Numbers and Central Limit Theorem, expected value, variance, generating functions, Markov Chains and random walks
  • Sampling: Definition, Sampling distribution of the mean and proportions, confidence intervals, Hypothesis testing, t-distribution
  • Regression and Correlation: Meaning and use of regression and correlation, linear regression, correlation coefficient

Delivery: 30 lectures, 15 tutorials

Assessment: Course Work: 50% Final Exam: 50%.


Grinstead, Charles M. and J. Laurie Snell, Introduction to Probability (2nd Ed.), American Mathematical Society, The CHANCE Project, 2006. (Electronic version available at



Meery, Brenda, Basic Probability and Statistics- A Short Course, CK-12 Foundation,, 2011.

Web Resources:

Probability and Statistics topic page on this site.

Lane, David M. et al, Introduction to Statistics (Online Edition), Rice University and University of Houston,, 2013.

Lane, David M., HyperStat Online Statistics Textbook,, 1993-2013.

StatSoft, Inc., Electronic Statistics Textbook, Tulsa, OK: StatSoft,, 2013.

Online Statistics Education: An Interactive Multimedia Course of Study developed by Rice University, University of Houston Clear Lake, and Tufts University,, 2013.