CT0003-Probability and Statistics for Computing

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:

  1. Present data using appropriate graphs and charts.
  2. 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
(Online Consultation)		16 September - 25 October
Thursday (6:30 pm - 8:30 pm)
Final Exam
(Onsite, NTU Campus)#		26 October 2024 (Saturday)
1pm to 2pm

#Onsite assessment venue at NTU will be announced closer to the final exam date.

Class schedule
(Online Consultation)		15 Apr - 24 May
Thursday (6:30 pm - 8:30 pm)
Final Exam
(Onsite, NTU Campus)#		25 May 2024 (Saturday)
1pm to 2pm

#Onsite assessment venue at NTU will be announced closer to the final exam date.

  • Each module cost S$250.
  • Learners can use their SkillsFuture credits to pay or partially pay for the bridging modules.