CT0003-Probability and Statistics for Computing
This course provides the basic mathematical foundations for probability and statistics which are necessary for anyone pursuing a computing degree course.
Intended Learning Outcomes (ILOs)
Upon completion of the course, you should be able to:
- Present data using appropriate graphs and charts.
- Apply probability and statistics to understand random phenomenon and make appropriate inferences.
Course Contents
| Probability Theory Sample space, events, mutually exclusive and independent events, probability rules, conditional probability, Bayes' theorem. |
| Discrete Probability Distribution Random variables, expectation, and variance of random variables. Discrete probability distributions: Bernoulli, Binomial, Geometric and Poisson distributions. |
| Continuous probability distribution Continuous random variables, expectation, and variance. Continuous probability density functions: Uniform distribution, Exponential distribution, Normal distribution. Normal approximation to Binomial distribution. |
| Inferential Statistics Unbiased point estimates, interval estimates, hypothesis testing of means (z and t tests) and proportions, Type I, II errors. |
Class Schedule - 5th Intake
| Class schedule (Online Consultation) | 13 April - 22 May 2026 Thursday (6:30 pm - 8:30 pm) |
| Final Exam (Onsite, NTU Campus)# | 23 May 2026 Saturday (PM) |
#Onsite assessment venue at NTU will be announced closer to the final exam date.
Course Schedule - 4th Intake
| Class schedule (Online Consultation) | 15 Sept - 24 Oct 2025 Thursday (6:30 pm - 8:30 pm) |
| Final Exam (Onsite, NTU Campus)# | 25 October 2025 |
#Onsite assessment venue at NTU will be announced closer to the final exam date.
Course Fees and Funding
- Each module cost S$250.
- Learners can use their SkillsFuture credits to pay or partially pay for the bridging modules.